Apps & ready solutions

Parses the specification from the customer (e.g. "C45, ø60 h9, 6 m, 8 tonnes"); maps quality to product portfolio (knowledge base), calculates theoretical weight and tonnage DETERMINISTICALLY (not model predicting), checks tolerance class feasibility and produces draft proposal. The three branches work in parallel and come together in Merge. IN LIVE: stock/production/import route is fed from ERP (canias) data source — in demo it is read from portfolio knowledge base.

Translates the material quality between norms (S235JR ↔ St 37-2, C45 ↔ Ck45 ↔ SAE 1045, 16MnCr5 ↔ 5115…). Three expert branches (EN/DIN · SAE-AISI/ASTM · TS/GOST) and chemical composition knowledge base operate in PARALLEL; The REFEREE node overlaps the three opinions. This flow is designed to CATCH the WRONG ANSWER, not the 'right answer': if composition ranges do not match or experts conflict, the result is 'VERIFICATION REQUIRED' and is up to human validation — false equivalence = rejected cargo + return freight.

It takes the output of the spectrometer/casting analysis, configures the element values, compares ELEMENT ELEMENT with the norm limits of the target quality and marks deviations. If appropriate, produces a draft EN 10204 3.1 inspection certificate in the customer's language; If it is non-conforming, a non-conformance report is written and the quality chief approves it. The decision boundary is separated by Switch, the two arms are joined in Merge.

Parallel produces the set of export documents for a shipment: proforma invoice, packing list, ATR/EUR.1 and certificate of origin checklist, and mandatory CBAM (SKDM) embedded emission report fields for sales to the EU. At the end, a file integrity check is performed; If there is any missing document, it is subject to approval by the export officer. ON LIVE: order/batch/tonnage and production route come from ERP (canias), emission factors are replaced with plant data — in demo it works with sample/open data.

It answers the customer's technical questions (material selection, quality difference, corrosion, heat treatment, which product for which application) from the corporate knowledge base and answers in the LANGUAGE OF THE QUESTION (TR/EN/DE/ES). If the intent is 'bid', it passes the question SUB-STREAM into the RFQ flow — the engineer ends up answering the same fifty questions again, the actual RFP falls on the right line. Select your RFQ flow in the sub-flow node.

It classifies the incoming request according to urgency (Switch), searches the knowledge base in the correct branch and generates a response, combines the two branches with Merge and sends it to Slack. Uses Connector + Switch + RAG + Merge + error handling.

It triages the new GitHub issue with AI (summary + tag), prepares the fields with Set, then opens the page to Notion in PARALLEL and reports to Slack (fan-out → Merge). It works automatically with a polling trigger (Trigger=Polling).

Single powerful agent: autonomously investigates a topic with web search, page fetch and calculation tools (agent-first mode → all your skills become tools). Hermes style 'you figure it out' flow.

Answers frequently asked questions from the knowledge base.

It summarizes long texts and documents in the field of Customer Services in 5 articles.

Customer Services separates requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the Customer Services area.

Produces persuasive content text from the topic for Customer Service.

Automatically evaluates the emotion and urgency of Customer Service messages.

Extracts structured data from Customer Service documents (model + Set + expression).

Answers Customer Services questions from the corporate knowledge base (RAG).

Converts the Customer Service knowledge base response into an executive report.

It pulls external API data for Customer Service and analyzes it with AI (with retry/error management).

Agent for Customer Service; It works autonomously with web search, page fetching and skills.

Customer Service forwards requests to human approval (Wait) or processes them automatically, depending on the threshold.

Customer Service scores the records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Customer Services and transforms them into a balanced evaluation with Merge.

Customer Service generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Customer Service texts preserving terminology.

Writes contextually personalized email for Customer Service.

Customer Services automatically responds to frequently asked questions from the knowledge base.

Customer Services creates a summary and action list from meeting/interview notes.

Customer Service monitors their content for quality/compatibility.

Extracts summary + 'responsible — task — date' actions from the raw note.

It summarizes long texts and documents in the field of operations in 5 articles.

It separates operation requests according to urgency and directs them to the correct response branch.

Produces a professional response draft to incoming messages in the operational area.

Generates persuasive content text from the subject for the operation.

Automatically evaluates the emotion and urgency of operational messages.

Extracts structured data from operational documents (model + Set + expression).

It answers operational questions from the corporate information base (RAG).

Converts operations knowledge base response to executive report.

It extracts external API data for operation (with retry/error management) and analyzes it with AI.

Agent regarding the operation; It works autonomously with web search, page fetching and skills.

It directs operation requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores the operation records 1-100 and determines their priority (high/medium/low).

It analyzes the opportunities and risks for the operation in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates the operation response and sends it to Slack (select Slack ID from Identity Vault).

Translates operational texts preserving terminology.

Writes personalized email based on context for the operation.

The operation automatically answers frequently asked questions from the knowledge base.

Prepares summary and action list from operational meeting/interview notes.

Inspects operation contents for quality/compatibility.

It summarizes long texts and documents in the field of Research & R&D in 5 articles.

It separates Research & R&D requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Research & R&D.

Produces persuasive content text from the subject for Research & R&D.

It automatically evaluates the emotion and urgency of Research & R&D messages.

Extracts structured data (model + Set + expression) from Research & R&D documents.

It answers research & R&D questions from the corporate knowledge base (RAG).

Converts the Research & R&D knowledge base response into an executive report.

It extracts external API data for Research & R&D and analyzes it with AI (with retry/error management).

Agent for Research & R&D; It works autonomously with web search, page fetching and skills.

It directs Research & R&D requests to human approval (Wait) or processes them automatically according to the threshold.

It scores Research & R&D records from 1 to 100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for Research & R&D IN PARALLEL and transforms them into a balanced evaluation with Merge.

Research & R&D generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Research & R&D texts by preserving the terminology.

Writes contextually personalized emails for Research & R&D.

Research & R&D automatically answers frequently asked questions from the knowledge base.

Creates summaries and action lists from Research & R&D meeting/interview notes.

Inspects Research & R&D content for quality/compatibility.

Summarizes long texts and documents in the field of banking in 5 articles.

It separates banking requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of banking.

Generates persuasive content text from the topic for banking.

Automatically evaluates the emotion and urgency of banking messages.

Extracts structured data from banking documents (model + Set + expression).

It answers banking questions from the corporate information base (RAG).

Converts the banking knowledge base response into an executive report.

It extracts external API data for banking and analyzes it with AI (with retry/error management).

Agent in banking; It works autonomously with web search, page fetching and skills.

It directs banking requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores banking records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for banking in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates the banking response and sends it to Slack (select Slack ID from Identity Vault).

Translates banking texts by preserving the terminology.

Writes contextually personalized emails for banking.

It provides automatic answers to frequently asked banking questions from the knowledge base.

Creates summaries and action lists from banking meeting/interview notes.

Audits banking content for quality/compliance.

It summarizes long texts and documents in the field of IT & DevOps in 5 articles.

It separates IT & DevOps requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the field of IT & DevOps.

Generates persuasive content copy from the topic for IT & DevOps.

Automatically evaluates the emotion and urgency of IT & DevOps messages.

Extracts structured data (model + Set + expression) from IT & DevOps documents.

It answers IT & DevOps questions from the corporate knowledge base (RAG).

Transforms IT & DevOps knowledge base response into executive report.

It extracts external API data (with retry/error management) and analyzes it with AI for IT & DevOps.

Agent on IT & DevOps; It works autonomously with web search, page fetching and skills.

Routes IT & DevOps requests to human approval (Wait) or processes them automatically, based on threshold.

Scores IT & DevOps records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for IT & DevOps and transforms them into a balanced evaluation with Merge.

IT & DevOps generates the response and sends it to Slack (select Slack identity from Identity Vault).

Translates IT & DevOps texts preserving terminology.

Writes contextually personalized email for IT & DevOps.

Automatically answers IT & DevOps frequently asked questions from the knowledge base.

Creates summaries and action lists from IT & DevOps meeting/interview notes.

Audits IT & DevOps content for quality/compliance.

It summarizes long texts and documents in the field of consultancy in 5 articles.

It separates consultancy requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the field of consultancy.

Produces persuasive content text from the subject for consultancy.

Automatically evaluates the emotion and urgency of counseling messages.

Extracts structured data from consulting documents (model + Set + expression).

It answers consultancy questions from the corporate knowledge base (RAG).

Converts consulting knowledge base response to executive report.

It pulls external API data (with retry/error management) and analyzes it with AI for consulting.

Agent in consultancy; It works autonomously with web search, page fetching and skills.

It directs consultancy requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores consultancy records from 1 to 100 and determines their priority (high/medium/low).

For consultancy, it analyzes opportunities and risks in PARALLEL and turns them into a balanced evaluation with Merge.

Generates the advisory response and sends it to Slack (select Slack ID from Identity Vault).

Translates consultancy texts preserving the terminology.

Writes contextually personalized email for consultation.

Consultancy automatically answers frequently asked questions from its knowledge base.

Creates a summary and action list from consultancy meeting/interview notes.

Checks consultancy content for quality/compliance.

It summarizes long texts and documents in the field of education in 5 articles.

It separates training requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of education.

Produces persuasive content text from the subject for education.

Automatically evaluates the emotion and urgency of training messages.

Extracts structured data from training documents (model + Set + expression).

It answers training questions from the corporate knowledge base (RAG).

Converts the training knowledge base response into an admin report.

It pulls external API data for training (with retry/error management) and analyzes it with AI.

Agent on education; It works autonomously with web search, page fetching and skills.

It directs training requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores training records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for education in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates the training response and sends it to Slack (select Slack ID from Identity Vault).

Translates educational texts by preserving the terminology.

Writes contextually personalized email for training.

It automatically answers frequently asked questions from the knowledge base.

Creates a summary and action list from training meeting/interview notes.

Audits training content for quality/compatibility.

It summarizes long texts and documents in the field of Real Estate & Real Estate in 5 articles.

It separates Real Estate & Real Estate requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Real Estate & Real Estate.

Produces persuasive content text on the subject for Real Estate & Real Estate.

It automatically evaluates the emotion and urgency of Real Estate & Real Estate messages.

Extracts structured data (model + Set + expression) from Real Estate & Real Estate documents.

It answers real estate questions from the corporate knowledge base (RAG).

Converts the Real Estate & Real Estate knowledge base response into an executive report.

It extracts external API data for Real Estate & Real Estate and analyzes it with AI (with retry/error management).

Real Estate & Real Estate agent; It works autonomously with web search, page fetching and skills.

It directs Real Estate & Real Estate requests to human approval (Wait) or processes them automatically according to the threshold.

It scores Real Estate & Real Estate records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Real Estate & Real Estate and transforms them into a balanced evaluation with Merge.

Real Estate & Real Estate generates the response and sends it to Slack (select Slack ID from ID Vault).

Translates Real Estate & Real Estate texts preserving the terminology.

Writes contextually personalized emails for Real Estate & Real Estate.

Real Estate & Real Estate automatically answers frequently asked questions from its knowledge base.

Real Estate & Real Estate prepares summaries and action lists from meeting/interview notes.

Checks Real Estate & Real Estate content for quality/compatibility.

It summarizes long texts and documents in the field of Energy & Public Services in 5 articles.

Energy & Public Services separates requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the field of Energy & Public Services.

Produces persuasive content text from the topic for Energy & Utilities.

Energy & Utilities automatically evaluates the emotion and urgency of messages.

Extracts structured data (model + Set + expression) from Energy & Utilities documents.

It answers Energy & Public Services questions from the corporate knowledge base (RAG).

Energy & Utilities converts knowledge base response to executive report.

It extracts external API data for Energy & Utilities and analyzes it with AI (with retry/error handling).

Agent on Energy & Utilities; It works autonomously with web search, page fetching and skills.

Energy & Utilities routes requests for human approval (Wait) or processes them automatically, based on threshold.

It scores Energy & Utilities records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Energy & Public Services and transforms them into a balanced evaluation with Merge.

Energy & Utilities generates the response and sends it to Slack (select Slack ID from ID Vault).

Translates Energy & Public Services texts preserving the terminology.

Writes contextually personalized emails for Energy & Utilities.

Energy & Utilities automatically answers frequently asked questions from its knowledge base.

Energy & Public Services prepares a summary and action list from meeting/interview notes.

Monitors Energy & Utilities content for quality/compliance.

It summarizes long texts and documents in the field of e-commerce in 5 articles.

It separates e-commerce requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of e-commerce.

Generates persuasive content text from the topic for e-commerce.

It automatically evaluates the emotion and urgency of e-commerce messages.

Extracts structured data from e-commerce documents (model + Set + expression).

It answers e-commerce questions from the corporate knowledge base (RAG).

Converts e-commerce knowledge base response to executive report.

It extracts external API data for e-commerce and analyzes it with AI (with retry/error management).

Agent in e-commerce; It works autonomously with web search, page fetching and skills.

It directs e-commerce requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores e-commerce records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for e-commerce in PARALLEL and turns them into a balanced evaluation with Merge.

Generates the e-commerce response and sends it to Slack (select Slack ID from Identity Vault).

Translates e-commerce texts by preserving terminology.

Writes contextually personalized emails for e-commerce.

E-commerce provides automatic answers to frequently asked questions from the knowledge base.

Creates summaries and action lists from e-commerce meeting/interview notes.

Checks e-commerce content for quality/compatibility.

It summarizes long texts and documents in the field of Event Management in 5 articles.

Event Management separates requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Event Management.

Produces persuasive content text from the topic for Event Management.

Event Management automatically evaluates the emotion and urgency of messages.

Extracts structured data from Event Management documents (model + Set + expression).

It answers Event Management questions from the corporate knowledge base (RAG).

Event Management converts the knowledge base response into an admin report.

It extracts external API data for Event Management and analyzes it with AI (with retry/error management).

Agent in Event Management; It works autonomously with web search, page fetching and skills.

Event Management directs requests to human approval (Wait) or processes them automatically, depending on the threshold.

Event Management scores the records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Event Management and transforms them into a balanced evaluation with Merge.

Event Management generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Event Management texts preserving the terminology.

Writes contextually personalized email for Event Management.

Event Management automatically answers frequently asked questions from the knowledge base.

Event Management creates summaries and action lists from meeting/interview notes.

Monitors Event Management content for quality/compliance.

It summarizes long texts and documents in the field of Finance & Accounting in 5 articles.

It separates Finance & Accounting requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Finance & Accounting.

Produces persuasive content text from the topic for Finance & Accounting.

Automatically evaluates the emotion and urgency of Finance & Accounting messages.

Extracts structured data (model + Set + expression) from Finance & Accounting documents.

It answers Finance & Accounting questions from the corporate information base (RAG).

Converts the Finance & Accounting knowledge base response to an executive report.

It extracts external API data for Finance & Accounting and analyzes it with AI (with retry/error management).

Agent in Finance & Accounting; It works autonomously with web search, page fetching and skills.

It directs Finance & Accounting requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores Finance & Accounting records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Finance & Accounting and transforms them into a balanced evaluation with Merge.

Finance & Accounting generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Finance & Accounting texts by preserving the terminology.

Writes contextually personalized emails for Finance & Accounting.

Finance & Accounting automatically answers frequently asked questions from the knowledge base.

Finance & Accounting creates summaries and action lists from meeting/interview notes.

Audits Finance & Accounting content for quality/compliance.

It summarizes long texts and documents in the field of Legal & Compliance in 5 articles.

Sorts Legal & Compliance requests according to urgency and directs them to the correct response branch.

Drafts professional responses to messages received in the Legal & Compliance field.

Produces persuasive content text from the topic for Legal & Compliance.

Automatically evaluates the emotion and urgency of Legal & Compliance messages.

Extracts structured data (model + Set + expression) from Legal & Compliance documents.

Answers Legal & Compliance questions from the corporate knowledge base (RAG).

Converts the Legal & Compliance knowledge base response into an executive report.

It extracts external API data (with retry/error management) and analyzes it with AI for Legal & Compliance.

Legal & Compliance agent; It works autonomously with web search, page fetching and skills.

It forwards Legal & Compliance requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores Legal & Compliance records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Legal & Compliance and transforms them into a balanced evaluation with Merge.

Legal & Compliance generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Legal & Compliance texts preserving terminology.

Writes contextually personalized emails for Legal & Compliance.

Legal & Compliance automatically answers frequently asked questions from its knowledge base.

Legal & Compliance creates a summary and action list from meeting/interview notes.

Monitors Legal & Compliance content for quality/compliance.

It summarizes long texts and documents in the field of Content & Editing in 5 items.

It separates Content & Editorial requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the field of Content & Editorial.

Produces persuasive content text from the topic for Content & Editing.

Content & Editorial automatically evaluates the emotion and urgency of messages.

Extracts structured data (model + Set + expression) from Content & Editorial documents.

Answers Content & Editorial questions from the corporate knowledge base (RAG).

Converts the Content & Editorial knowledge base response into an executive report.

It pulls external API data for Content & Editorial and analyzes it with AI (with retry/error management).

Content & Editorial agent; It works autonomously with web search, page fetching and skills.

It directs Content & Editorial requests to human approval (Wait) or processes them automatically, depending on the threshold.

Scores Content & Editorial records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Content & Editorial and transforms them into a balanced evaluation with Merge.

Content & Editorial generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Content & Editorial texts preserving the terminology.

Writes contextually personalized emails for Content & Editorial.

Content & Editorship automatically answers frequently asked questions from the knowledge base.

Content & Editorial creates summaries and action lists from meeting/interview notes.

Reviews Content & Editorial content for quality/compatibility.

It summarizes long texts and documents in the field of Human Resources in 5 articles.

It separates Human Resources requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Human Resources.

Produces persuasive content text on the subject for Human Resources.

It automatically evaluates the emotion and urgency of Human Resources messages.

Extracts structured data from Human Resources documents (model + Set + expression).

It answers Human Resources questions from the corporate information base (RAG).

Converts the Human Resources knowledge base response to an executive report.

It extracts external API data for Human Resources and analyzes it with AI (with retry/error management).

Human Resources agent; It works autonomously with web search, page fetching and skills.

Human Resources directs requests to human approval (Wait) or processes them automatically according to the threshold.

It scores Human Resources records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Human Resources and transforms them into a balanced evaluation with Merge.

Human Resources generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Human Resources texts by preserving the terminology.

Writes contextually personalized emails for Human Resources.

Human Resources automatically answers frequently asked questions from the knowledge base.

Human Resources prepares a summary and action list from meeting/interview notes.

Monitors Human Resources content for quality/compatibility.

It summarizes long texts and documents in the field of Public & NGOs in 5 articles.

It separates public & NGO requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the public & NGO field.

Produces persuasive content text on the subject for public & NGO.

Automatically evaluates the emotion and urgency of public & NGO messages.

Extracts structured data (model + Set + expression) from government & NGO documents.

It answers public & NGO questions from the corporate knowledge base (RAG).

Converts public & NGO knowledge base response into executive report.

It extracts external API data for public & NGO and analyzes it with AI (with retry/error management).

Public & NGO agent; It works autonomously with web search, page fetching and skills.

It directs public & NGO requests to human approval (Wait) according to the threshold or processes them automatically.

It scores public & NGO records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for the public & NGOs and transforms them into a balanced evaluation with Merge.

Generates Government & NGO response and sends it to Slack (select Slack ID from Identity Vault).

Translates public & NGO texts preserving the terminology.

Writes contextually personalized emails for government & NGOs.

It automatically answers public & NGO frequently asked questions from its knowledge base.

Creates a summary and action list from public & NGO meeting/interview notes.

Checks public & NGO content for quality/compatibility.

It summarizes long texts and documents in the field of Logistics & Supply in 5 articles.

It separates Logistics & Supply requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Logistics & Supply.

Produces persuasive content text from the topic for Logistics & Supply.

Automatically evaluates the emotion and urgency of Logistics & Supply messages.

Extracts structured data (model + Set + expression) from Logistics & Supply documents.

It answers Logistics & Supply questions from the corporate knowledge base (RAG).

Converts the Logistics & Procurement knowledge base response into an executive report.

It extracts external API data for Logistics & Supply and analyzes it with AI (with retry/error management).

Agent in Logistics & Supply; It works autonomously with web search, page fetching and skills.

It directs Logistics & Supply requests to human approval (Wait) or processes them automatically according to the threshold.

It scores Logistics & Supply records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Logistics & Supply and transforms them into a balanced evaluation with Merge.

Logistics & Supply generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Logistics & Supply texts by preserving the terminology.

Writes contextually personalized email for Logistics & Supply.

Logistics & Supply automatically answers frequently asked questions from the knowledge base.

Creates a summary and action list from Logistics & Supply meeting/interview notes.

Inspects Logistics & Supply content for quality/compatibility.

It summarizes long texts and documents in the field of Media & Publishing in 5 articles.

Sorts Media & Publishing requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Media & Publishing.

Produces persuasive content text from the topic for Media & Publishing.

Media & Publishing automatically evaluates the emotion and urgency of messages.

Extracts structured data (model + Set + expression) from Media & Publishing documents.

It answers Media & Publishing questions from the corporate knowledge base (RAG).

Converts Media & Publishing knowledge base response to executive report.

It extracts external API data for Media & Publishing and analyzes it with AI (with retry/error management).

Media & Publishing agent; It works autonomously with web search, page fetching and skills.

It directs Media & Publishing requests to human approval (Wait) or processes them automatically, depending on the threshold.

Media & Publishing scores 1-100 records and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Media & Publishing and transforms them into a balanced evaluation with Merge.

Media & Publishing generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Media & Publishing texts preserving the terminology.

Writes contextually personalized emails for Media & Publishing.

Media & Publishing automatically answers frequently asked questions from its knowledge base.

Media & Publishing creates summaries and action lists from meeting/interview notes.

Monitors Media & Publishing content for quality/compliance.

Summarizes long texts and documents in the field of marketing in 5 articles.

It separates marketing requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the field of marketing.

Generates persuasive content text from the topic for marketing.

Automatically evaluates the emotion and urgency of marketing messages.

Extracts structured data from marketing documents (model + Set + expression).

It answers marketing questions from the corporate knowledge base (RAG).

Converts the marketing knowledge base response into an executive report.

It pulls external API data for marketing and analyzes it with AI (with retry/error management).

Marketing agent; It works autonomously with web search, page fetching and skills.

It directs marketing requests to human approval (Wait) or processes them automatically, depending on the threshold.

Scores marketing records from 1 to 100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for marketing in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates and sends marketing response to Slack (select Slack ID from Identity Vault).

Translates marketing texts while preserving terminology.

Writes contextually personalized email for marketing.

It automatically answers marketing frequently asked questions from its knowledge base.

Creates summary and action list from marketing meeting/interview notes.

Monitors marketing content for quality/compliance.

Summarizes long texts and documents in the field of retail in 5 articles.

It separates retail requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the retail field.

Generates persuasive content copy from the topic for retail.

Automatically evaluates the emotion and urgency of retail messages.

Extracts structured data from retail documents (model + Set + expression).

It answers retail questions from the corporate knowledge base (RAG).

Converts retail knowledge base response to executive report.

It pulls external API data for retail (with retry/error management) and analyzes it with AI.

Agent in retail; It works autonomously with web search, page fetching and skills.

It forwards retail requests to human approval (Wait) or processes them automatically, based on a threshold.

It scores retail records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for retail in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates the retail response and sends it to Slack (select Slack ID from Identity Vault).

Translates retail texts preserving terminology.

Writes contextually personalized email for retail.

It automatically answers retail frequently asked questions from its knowledge base.

Creates summaries and action lists from retail meeting/interview notes.

Monitors retail content for quality/compliance.

It summarizes long texts and documents in the field of Project Management in 5 articles.

Project Management separates requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Project Management.

Produces persuasive content text on the topic for Project Management.

Automatically evaluates the emotion and urgency of Project Management messages.

Extracts structured data from Project Management documents (model + Set + expression).

It answers Project Management questions from the corporate knowledge base (RAG).

Converts the Project Management knowledge base response to an executive report.

It extracts external API data (with retry/error management) and analyzes it with AI for Project Management.

Agent in Project Management; It works autonomously with web search, page fetching and skills.

Project Management directs requests to human approval (Wait) or processes them automatically according to the threshold.

Project Management scores the records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Project Management and transforms them into a balanced evaluation with Merge.

Project Management generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Project Management texts preserving the terminology.

Writes contextually personalized email for Project Management.

Project Management automatically answers frequently asked questions from the knowledge base.

Project Management creates a summary and action list from meeting/interview notes.

Monitors Project Management content for quality/compliance.

It summarizes long texts and documents in the Restaurant & Food field in 5 articles.

It separates Restaurant & Food requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the Restaurant & Food field.

Produces persuasive content text from the topic for Restaurant & Food.

Automatically evaluates the emotion and urgency of Restaurant & Food messages.

Extracts structured data (model + Set + expression) from Restaurant & Food documents.

It answers Restaurant & Food questions from the corporate knowledge base (RAG).

Converts Restaurant & Food knowledge base response to executive report.

It extracts external API data for Restaurant & Food (with retry/error management) and analyzes it with AI.

Agent for Restaurant & Food; It works autonomously with web search, page fetching and skills.

It directs Restaurant & Food requests to human approval (Wait) or processes them automatically according to the threshold.

It scores Restaurant & Food records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Restaurant & Food and transforms them into a balanced evaluation with Merge.

Restaurant & Food generates the response and sends it to Slack (select Slack ID from ID Vault).

Translates Restaurant & Food texts preserving the terminology.

Writes contextually personalized emails for Restaurant & Food.

Restaurant & Food automatically answers frequently asked questions from its knowledge base.

Creates a summary and action list from Restaurant & Food meeting/interview notes.

Inspects Restaurant & Food content for quality/compatibility.

Summarizes long texts and documents in the field of health in 5 articles.

It separates health requests according to urgency and directs them to the correct response branch.

Produces a professional response draft to messages received in the field of health.

Produces persuasive content text on the topic for health.

Automatically evaluates the emotion and urgency of health messages.

Extracts structured data from health documents (model + Set + expression).

It answers health questions from the corporate knowledge base (RAG).

Converts the health knowledge base response into an executive report.

It extracts external API data for health and analyzes it with AI (with retry/error management).

Agent on health; It works autonomously with web search, page fetching and skills.

It directs health requests to human approval (Wait) or processes them automatically according to the threshold.

It scores health records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for health in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates the health response and sends it to Slack (select Slack ID from ID Vault).

Translates health texts by preserving terminology.

Writes contextually personalized emails for health.

It automatically answers health frequently asked questions from its knowledge base.

Creates a summary and action list from health meeting/interview notes.

Inspects health ingredients for quality/compatibility.

It summarizes long texts and documents in the field of sales in 5 items.

It separates sales requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the sales area.

Produces persuasive content text from the topic for sales.

Automatically evaluates the emotion and urgency of sales messages.

Extracts structured data from sales documents (model + Set + expression).

Answers sales questions from the corporate knowledge base (RAG).

Converts the sales knowledge base response into an executive report.

It extracts external API data for sales (with retry/error management) and analyzes it with AI.

Agent in sales; It works autonomously with web search, page fetching and skills.

It directs sales requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores sales records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for sales in PARALLEL and turns them into a balanced evaluation with Merge.

Generates the sales response and sends it to Slack (select Slack ID from Identity Vault).

Translates sales texts while preserving terminology.

Writes contextually personalized email for sales.

Automatically answers sales frequently asked questions from the knowledge base.

Creates summaries and action lists from sales meeting/interview notes.

Monitors sales content for quality/compatibility.

Summarizes long texts and documents in the field of insurance in 5 articles.

It separates insurance claims according to urgency and directs them to the correct response branch.

Produces professional response drafts to incoming messages in the field of insurance.

Generates persuasive content text from the topic for insurance.

Automatically evaluates the emotion and urgency of insurance messages.

Extracts structured data from insurance documents (model + Set + expression).

It answers insurance questions from the corporate knowledge base (RAG).

Converts the insurance knowledge base response into an executive report.

It extracts external API data for insurance and analyzes it with AI (with retry/error management).

Insurance agent; It works autonomously with web search, page fetching and skills.

It forwards insurance claims to human approval (Wait) or processes them automatically, based on a threshold.

It scores insurance records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for insurance in PARALLEL and transforms them into a balanced evaluation with Merge.

Generates the fuse response and sends it to Slack (select Slack ID from ID Vault).

Translates insurance texts preserving terminology.

Writes contextually personalized email for insurance.

Insurance provides automatic answers to frequently asked questions from its knowledge base.

Creates a summary and action list from insurance meeting/interview notes.

Inspects insurance contents for quality/compatibility.

It summarizes long texts and documents in the field of Social Media in 5 articles.

It separates Social Media requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Social Media.

Produces persuasive content text from the topic for Social Media.

Automatically evaluates the emotion and urgency of Social Media messages.

Extracts structured data from Social Media documents (model + Set + expression).

It answers Social Media questions from the corporate knowledge base (RAG).

Converts Social Media knowledge base response into executive report.

It extracts external API data for Social Media and analyzes it with AI (with retry/error management).

Agent on Social Media; It works autonomously with web search, page fetching and skills.

It directs Social Media requests to human approval (Wait) or processes them automatically, depending on the threshold.

It scores Social Media records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for Social Media IN PARALLEL and turns them into a balanced evaluation with Merge.

Social Media generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Social Media texts by preserving the terminology.

Writes contextually personalized emails for Social Media.

Social Media automatically answers frequently asked questions from its knowledge base.

Creates summaries and action lists from Social Media meeting/interview notes.

Checks Social Media content for quality/compatibility.

Summarizes long texts and documents in the field of agriculture in 5 articles.

It separates agricultural requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of agriculture.

Generates persuasive content text from the topic for agriculture.

Automatically evaluates the emotion and urgency of agricultural messages.

Extracts structured data from agricultural documents (model + Set + expression).

It answers agricultural questions from the corporate knowledge base (RAG).

Converts agriculture knowledge base response to executive report.

It extracts external API data for agriculture and analyzes it with AI (with retry/error management).

Agent on agriculture; It works autonomously with web search, page fetching and skills.

It directs agricultural requests to human approval (Wait) or processes them automatically according to the threshold.

It scores agricultural records from 1 to 100 and determines their priority (high/medium/low).

It analyzes opportunities and risks for agriculture in PARALLEL and transforms them into a balanced evaluation with Merge.

Agriculture generates the response and sends it to Slack (select Slack ID from ID Vault).

Translates agricultural texts preserving terminology.

Writes contextually personalized emails for agriculture.

Agriculture provides automatic answers to frequently asked questions from its knowledge base.

Prepares summary and action list from agricultural meeting/interview notes.

Inspects agricultural ingredients for quality/compatibility.

Summarizes long texts and documents in the field of Tourism & Hotel Management in 5 articles.

It separates Tourism & Hospitality requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Tourism & Hotel Management.

Produces persuasive content text on the subject for Tourism & Hotel Management.

It automatically evaluates the emotion and urgency of Tourism & Hospitality messages.

Extracts structured data (model + Set + expression) from Tourism & Hospitality documents.

It answers Tourism & Hospitality questions from the corporate knowledge base (RAG).

Converts the Tourism & Hospitality knowledge base response into an executive report.

It extracts external API data for Tourism & Hospitality and analyzes it with AI (with retry/error management).

Agent in Tourism & Hotel Management; It works autonomously with web search, page fetching and skills.

It directs Tourism & Hospitality requests to human approval (Wait) or processes them automatically according to the threshold.

It scores Tourism & Hospitality records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Tourism & Hotel Management and transforms them into a balanced evaluation with Merge.

Tourism & Hospitality generates the response and sends it to Slack (select Slack ID from the ID Vault).

Translates Tourism & Hospitality texts by preserving the terminology.

Writes contextually personalized emails for Tourism & Hospitality.

Tourism & Hotel Management automatically answers frequently asked questions from its knowledge base.

Tourism & Hotel Management creates a summary and action list from meeting/interview notes.

Checks Tourism & Hospitality content for quality/compatibility.

It summarizes long texts and documents in the field of Production & Manufacturing in 5 articles.

It separates Production & Manufacturing requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the Production & Manufacturing field.

Produces persuasive content text from the topic for Production & Manufacturing.

Automatically evaluates the emotion and urgency of Production & Manufacturing messages.

Extracts structured data (model + Set + expression) from Production & Manufacturing documents.

It answers Production & Manufacturing questions from the corporate knowledge base (RAG).

Converts the Production & Manufacturing knowledge base response into an executive report.

It extracts external API data for Production & Manufacturing and analyzes it with AI (with retry/error management).

Agent for Production & Manufacturing; It works autonomously with web search, page fetching and skills.

It directs Production & Manufacturing requests to human approval (Wait) according to the threshold or processes them automatically.

It scores Production & Manufacturing records from 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Production & Manufacturing and transforms them into a balanced evaluation with Merge.

Production & Manufacturing generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Production & Manufacturing texts while preserving the terminology.

Writes contextually personalized emails for Manufacturing & Manufacturing.

Production & Manufacturing automatically answers frequently asked questions from the knowledge base.

Creates a summary and action list from Production & Manufacturing meeting/interview notes.

Inspects Production & Manufacturing contents for quality/compatibility.

It summarizes long texts and documents in the field of Product Management in 5 articles.

Product Management separates requests according to urgency and directs them to the correct response branch.

Produces professional response drafts to messages received in the field of Product Management.

Produces persuasive content text from the topic for Product Management.

Product Management automatically evaluates the emotion and urgency of messages.

Extracts structured data from Product Management documents (model + Set + expression).

It answers Product Management questions from the corporate knowledge base (RAG).

Converts the Product Management knowledge base response to an executive report.

It extracts external API data (with retry/error management) and analyzes it with AI for Product Management.

Agent on Product Management; It works autonomously with web search, page fetching and skills.

Product Management directs requests to human approval (Wait) or processes them automatically, depending on the threshold.

Product Management scores the records 1-100 and determines their priority (high/medium/low).

It analyzes opportunities and risks in PARALLEL for Product Management and transforms them into a balanced evaluation with Merge.

Product Management generates the response and sends it to Slack (select Slack ID from Identity Vault).

Translates Product Management texts preserving the terminology.

Writes contextually personalized email for Product Management.

Product Management automatically answers frequently asked questions from the knowledge base.

Product Management creates a summary and action list from meeting/interview notes.

Monitors Product Management content for quality/compatibility.

It classifies the incoming request according to urgency (Switch), searches the knowledge base in the correct branch and generates a response, combines the two branches with Merge and sends it to Slack. Uses Connector + Switch + RAG + Merge + error handling.

It triages the new GitHub issue with AI (summary + tag), prepares the fields with Set, then opens the page to Notion in PARALLEL and reports to Slack (fan-out → Merge). It works automatically with a polling trigger (Trigger=Polling).

Single powerful agent: autonomously investigates a topic with web search, page fetch and calculation tools (agent-first mode → all your skills become tools). Hermes style 'you figure it out' flow.

It gathers information from three sources simultaneously — enterprise knowledge base (RAG), web search (agent), and an API — and combines it all with Merge into a single synthesis report. Shows fan-out/fan-in power.

It extracts fields from the invoice text (JSON), reads the amount with Set, redirects it according to the threshold with expression (Switch): high amount requires HUMAN APPROVAL (Wait node), low amount is processed automatically; the result is saved in Airtable. Set + statement + Switch + Wait + connector.

Generates a professional email draft from the incoming context, translates it to English and sends it via SendGrid (retry + error handling). Multi-step model + connector.

If the primary API call fails, it switches to the backup source by following the 'error' branch (onError=branch + retry). The two branches are merged in Merge and rendered with the model. Demonstrates the power of per-node error handling.

Scores the prospective customer 1-100, reads the score with Set; In other words, if it is above 70, it opens a contact in HubSpot and reports it to Slack; if it is below 70, it archives it. Set + expression + condition + two connectors.

It pulls a source, summarizes the day's highlights, and sends it to Slack. It works automatically with a scheduled trigger (Trigger=Scheduled, cron e.g. 'every day at 09:00'). HTTP + model + connector.

It works automatically for EVERY ITEM on a set of records (JSON array) input: Adds field with set, model processes each record. Demonstrates the item/array data model and per-item execution. Input e.g.: [{"name":"..."}, ...].

It determines the sentiment of the comment (positive/negative/neutral) and switches to THREE different branches: escalation in negative, thanks in positive, follow-up in neutral. The three branches join at Merge. Multi-path Switch + Merge.

Screens the contract according to corporate rules (RAG), flags risks; If the risky phrase passes, it waits for human approval and escalates to Slack, otherwise it auto-approves. RAG + condition + Wait + connector.

It triages the error notification received on a webhook with artificial intelligence and opens an issue on GitHub. Webhook trigger (signed) + model + connector. Automates events from external systems.

It pulls the current weather forecast of a city (OpenWeather connector), selects the campaign theme based on the temperature (Switch) and produces the appropriate marketing message. Connector + emoticon + Switch.

In PARALLEL to the new customer record, creates a Stripe customer, opens a record in Notion, and notifies Slack; the three merge into Merge. Multi-connector + fan-out/Merge.

It calls a 'Clean/Normalize Text' stream that you publish separately as a SUB-STREAM, then processes the result. Modularity + reuse (A8). Select your own published stream in the sub-stream node.

Parses the specification from the customer (e.g. "C45, ø60 h9, 6 m, 8 tonnes"); maps quality to product portfolio (knowledge base), calculates theoretical weight and tonnage DETERMINISTICALLY (not model predicting), checks tolerance class feasibility and produces draft proposal. The three branches work in parallel and come together in Merge. IN LIVE: stock/production/import route is fed from ERP (canias) data source — in demo it is read from portfolio knowledge base.

Translates the material quality between norms (S235JR ↔ St 37-2, C45 ↔ Ck45 ↔ SAE 1045, 16MnCr5 ↔ 5115…). Three expert branches (EN/DIN · SAE-AISI/ASTM · TS/GOST) and chemical composition knowledge base operate in PARALLEL; The REFEREE node overlaps the three opinions. This flow is designed to CATCH the WRONG ANSWER, not the 'right answer': if composition ranges do not match or experts conflict, the result is 'VERIFICATION REQUIRED' and is up to human validation — false equivalence = rejected cargo + return freight.

It takes the output of the spectrometer/casting analysis, configures the element values, compares ELEMENT ELEMENT with the norm limits of the target quality and marks deviations. If appropriate, produces a draft EN 10204 3.1 inspection certificate in the customer's language; If it is non-conforming, a non-conformance report is written and the quality chief approves it. The decision boundary is separated by Switch, the two arms are joined in Merge.

Parallel produces the set of export documents for a shipment: proforma invoice, packing list, ATR/EUR.1 and certificate of origin checklist, and mandatory CBAM (SKDM) embedded emission report fields for sales to the EU. At the end, a file integrity check is performed; If there is any missing document, it is subject to approval by the export officer. ON LIVE: order/batch/tonnage and production route come from ERP (canias), emission factors are replaced with plant data — in demo it works with sample/open data.

It answers the customer's technical questions (material selection, quality difference, corrosion, heat treatment, which product for which application) from the corporate knowledge base and answers in the LANGUAGE OF THE QUESTION (TR/EN/DE/ES). If the intent is 'bid', it passes the question SUB-STREAM into the RFQ flow — the engineer ends up answering the same fifty questions again, the actual RFP falls on the right line. Select your RFQ flow in the sub-flow node.

The most basic flow that asks a question to a model and returns the answer.

Summarizes a long text in 5 items.

Professionally translates the input into the target language.

Determines the emotion (positive/negative/neutral) of a text.