LangChain AI Agent
Within the scope of this project, it is necessary to implement an AI agent for processing meeting transcripts. The agent should operate based on the LangChain framework and LLM for analyzing call transcriptions and extracting structured actions from them. These actions may relate to the CRM system (Salesforce) – for example, creating or updating leads, contacts, accounts, opportunities; to the task tracking system (Jira) – for example, creating new tickets or updating statuses / creating comments; as well as preparing follow-up emails to meeting participants based on the discussed topics.
The agent acts as an intelligent assistant: it does not perform any actions directly but only analyzes the meeting text and suggests possible next steps to the user. The agent's output is a list of recommendations in JSON format, where each suggestion includes the platform (Salesforce, Jira, or Gmail), the type of action (e.g., create or update an entity), the model's confidence level, a natural language description, and a structured payload with details. The user reviews these suggestions on an external UI and manually confirms execution – after which external services perform the corresponding integrations.
Full description is available at the link:
https://docs.google.com/document/d/1FG5nRSKtfFg37SBhQfAlxevD6WPKfW_qAN6wccaIYX0/edit?usp=sharing
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