---
title: "Agentic Slack Chatbot with RAG Search – Cognilium AI"
canonical_url: "https://cognilium.ai/solutions/genai-agentic-intelligent/agentic-workflow-slack-chatbot-rag-search"
slug: "solutions/genai-agentic-intelligent/agentic-workflow-slack-chatbot-rag-search"
section: "solutions"
page_type: "pillar"
date_modified: "2026-09-29"
description: "A multi-agent Slack bot that searches meeting history with RAG, extracts action items, and syncs tasks with your project tool. Every answer carries its source."
publisher: "Cognilium AI"
author: "Mudassir Marwat"
person_same_as:
  - "https://www.linkedin.com/in/mudassir-marwat/"
  - "https://orcid.org/0009-0008-1927-2598"
  - "https://github.com/mudassirmarwat"
  - "https://medium.com/@mudassir-marwat"
  - "https://www.youtube.com/@mudassir-marwat"
  - "https://dev.to/mudassirmarwat"
  - "https://hashnode.com/@mudassirmarwat"
  - "https://huggingface.co/mudassirmarwat"
  - "https://bsky.app/profile/mudassir-marwat.bsky.social"
  - "https://substack.com/@mudassirmarwat"
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  - "https://www.facebook.com/mudassir.marwat"
  - "https://www.reddit.com/user/mudassirmarwat/"
  - "https://www.f6s.com/member/mudassir-marwat"
  - "https://cognilium.ai/founder"
answers:
  - "Decisions were being made, then lost"
  - "Three specialised agents, working together"
  - "A decision you can check"
  - "Built with"
entities: []
related:
---

# Agentic Slack Chatbot with RAG Search – Cognilium AI

**Conversation agent** Handles natural language interactions in Slack, understanding context and intent — intent recognition, context management and multi-turn dialogue.


## In short

**Conversation agent** Handles natural language interactions in Slack, understanding context and intent — intent recognition, context management and multi-turn dialogue.

**RAG search agent** Performs semantic search across all indexed meeting transcripts — vector similarity, context retrieval and result ranking.

**Task automation agent** Extracts action items and creates tasks in project management tools — action extraction, task prioritisation and assignment.

A fast-growing tech company was drowning in meetings, losing track of decisions, and spending hours creating tasks by hand.

We built a multi-agent Slack chatbot that searches meeting history with RAG, extracts action items, and syncs them into the team's project tool.

answers given without the meeting they came from


## Decisions were being made, then lost

The meeting happens, the decision gets made, and then it lives in a recording nobody re-watches. The work after the meeting was where the team's time went.

Long post-meeting work, creating and assigning tasks by hand

Lost meeting context — important decisions buried in recordings

Action items getting forgotten between one meeting and the next

Disconnected tools: Slack, the call recorder and the task board not talking

Tasks created and assigned from the decision itself

Any decision findable by asking a question in the channel

Action items tracked rather than remembered

One workflow: the tools stay, the syncing stops being somebody's job


## Three specialised agents, working together

One agent that talks, one that finds, one that files. Splitting them means each can be tested, replaced and reasoned about on its own.


## A decision you can check

Ask a question in the channel and the answer comes back with the meeting, document or ticket it came from, so the decision can be checked rather than taken on trust.

That matters most when the answer is inconvenient. A bot that cannot show its source is a bot the team stops believing the first time it is wrong.


## Built with

A working session on your own transcripts: we take a real meeting, show what the agents pull out of it, and where the answer comes from. If the recordings are not good enough to work from, we will tell you that instead.


---

Canonical HTML: https://cognilium.ai/solutions/genai-agentic-intelligent/agentic-workflow-slack-chatbot-rag-search