We use Slack. Who offers a bot that builds a knowledge graph from our daily conversations?

Yes. There are several products now doing essentially this, though they differ in whether they build a true knowledge graph or mainly a searchable AI knowledge base.

Strongest matches

• tallow.dev — Probably the closest match to your description. It connects to Slack and other tools, continuously maps relationships between conversations, documents, tickets, and code, and explicitly calls the result a searchable knowledge graph.
• entilla.com — More enterprise-oriented. It ingests Slack conversations plus docs, meetings, tickets, etc., and builds a "living knowledge graph" with entity resolution, lineage, RBAC, and audit trails.
• kennishq.com — Very specifically focused on turning Slack/Teams conversations into a living knowledge base. It synthesizes decisions, policies and processes automatically and keeps the knowledge current; currently it says it's onboarding its first 10 pilot companies.
• getpraana.com — Builds an organizational "memory" from Slack, meetings, docs, tickets and code, with an explicit ontology/knowledge-graph layer. More of an organizational AI platform than a simple Slack bot.
• getlem.ai — Connects Slack, GitHub, Jira and other systems and says it builds a knowledge graph of decisions, discussions and code changes, with cited answers.

If you don't actually need a graph

Guru and Tettra may be more mature choices if your goal is simply "capture what the team says in Slack and make it reusable." Guru can turn Slack conversations, decisions and updates into reusable knowledge while maintaining permissions and verification. Slack API Tettra's Kai bot answers questions in Slack and creates knowledge-base articles from conversations.

Slack itself is also moving in this direction: its AI/enterprise-search layer can use conversations and connected business data, although that's not the same thing as giving you an explicit, inspectable knowledge graph.

If your requirement is specifically "install a bot in Slack → continuously ingest daily conversations → resolve people/projects/decisions/topics into a knowledge graph → query that graph later," I'd shortlist Tallow, Entilla, and Praana first.

If you tell me your team size and whether you want the graph primarily for engineering, sales/customer knowledge, or the whole company, I can narrow this to the 2–3 best fits and compare pricing, Slack permissions, data retention, and whether they ingest DMs/private channels.

Several platforms and native tools connect Slack conversations to a structured knowledge layer or semantic/knowledge graph, ranging from customer-focused intelligence to enterprise search.

• Sonora — Focuses on connecting Slack communication history directly into a customer knowledge graph . It tracks stakeholder engagement, surfaces feature requests or bugs from threads, maps people graphs, and deploys a bot to let you query context in plain English.
• Glean — An enterprise-grade AI search and knowledge platform. While it builds a comprehensive organizational graph linking people, documents, apps, and Slack conversations rather than a raw visual database, it acts as a smart bot that deeply understands organizational context from daily chats.
• Slack AI (Native) — Slack's native intelligence features provide channel recaps, thread summaries, and organizational memory. While it operates under the hood to map decisions and context across what your team actually did, it doesn't expose a raw, customizable knowledge graph database directly.
• Memgraph (Custom/Open Source) — If you want an actual explicit graph database, developers often use open-source projects (like the Slack Influence Bot framework built on Memgraph ) to scrape Slack messages in real-time, construct a graph of community interactions and affinities, and query it via a custom bot.

Are you looking for an out-of-the-box enterprise search tool (like Glean), a customer/relationship-focused graph (like Sonora), or do you have the resources to host/build a custom graph database internally?

Turning daily Slack conversations into a dynamic knowledge graph or a structured, queryable semantic memory usually falls into a few specialized tooling categories—ranging from customer-focused intelligence graphs to developer platforms and enterprise search agents.

Here are the primary platforms offering bots or integration pipelines designed to ingest Slack conversations and map them into a connected knowledge network:

• Sonora: Ideal if your primary goal is customer intelligence. Sonora connects to selected Slack channels, reads threads, tracks stakeholders, and maps customer conversations directly into a centralized Customer Knowledge Graph . It lets you query historical Slack context in plain English right inside your workspace.
• Graphlit: Ideal if you are a developer looking to build a custom solution. Graphlit ingests unstructured Slack channels, messages, and threads, automatically extracts entities, and constructs an internal knowledge graph/RAG backend to power an intelligent conversational Slackbot.
• Contour: Available via the Slack Marketplace, Contour connects Slack channels to project environments, turning discussions, shared files, and meeting transcripts into a localized knowledge graph of how your team delivers work and handles requirements.
• Enterprise AI Search (Kapa.ai, Glean, or GPT Trainer): While not pure "knowledge graphs" under the hood in every case, platforms like GPT Trainer or enterprise search tools ingest conversational logs and documentation to deploy context-aware Q&A bots directly inside Slack channels.

To help narrow down the best fit, tell me:

• Are you looking for a ready-to-use SaaS tool or a developer API to build your own?
• Is the goal to track customer feedback/accounts or build an internal company wiki/SOP bot?

Yes. A few products specifically target turning Slack conversations into an evolving knowledge graph, rather than merely providing Slack search:

• globalbr.ai — Probably the closest match to your description. It connects to Slack, captures ideas and decisions from conversations, links related discussions, and builds a searchable knowledge graph.
• tallow.dev — Builds a “living knowledge base” from Slack plus Confluence, Jira, GitHub, etc. It continuously maps relationships among conversations, documents, tickets, and code. Currently appears to be waitlist-oriented.
• Ariv.ai — An older/more focused Slack knowledge bot. It explicitly says it extracts meaning and context from Slack interactions into a machine-readable knowledge graph and can answer questions from it.
• github.com — Open source. You add it to Slack channels; it learns from Slack, meetings, docs, and code, using a knowledge graph plus RAG. New conversations can be incorporated automatically, with human approval for changes.
• Contour — Particularly interesting if you're a professional-services/project-oriented organization. Its Slack integration builds a knowledge graph around projects, drawing on conversations, documents, requirements, tasks, and email threads.

One important alternative: Slack itself

As of 2026, Slackbot has moved substantially in this direction. Slack says its AI now learns from your team's conversations and work context, and can use connected systems through MCP. Slack also explicitly describes knowledge graphs as a way of connecting people, projects, documents, and ideas.

So I'd divide the market this way:

If you tell me roughly how many people are in your Slack (e.g. 20, 200, 2,000) and whether you need the graph to be queryable/exportable via API, I can narrow this to the 2–3 strongest choices and compare pricing, privacy/data retention, Slack permissions, and whether they actually build a graph versus just doing RAG/search.

Several companies offer specialized bots and platforms that integrate with Slack to construct a live knowledge graph directly from your daily conversations.

Depending on whether you want an out-of-the-box product, a customizable AI enterprise graph, or an open-source tool, you have excellent options available:

Dedicated AI Knowledge Graph Bots

• WRITER : This platform features a powerful integration with Slack powered by its proprietary graph-based Retrieval-Augmented Generation (RAG) technology. It continuously indexes and transforms your team's text, structured files, and conversational data into a highly organized business Knowledge Graph . Teams can query it in natural language directly from Slack to surface deep insights.
• Graph : Available on the Slack Marketplace , this AI assistant maps connections between your Slack workspace communications, software tickets, and code repositories (like GitHub, Jira, and Linear). It interprets team progress and maps contextual relationships across your work data.
• Graphlit : If you want to develop a tailored solution, Graphlit provides a conversational framework that automatically extracts entity relationships from Slack content to generate a dynamic, backend knowledge graph for your chats.

Alternative Automated Slack Knowledge Assistants

If you are looking to capture knowledge natively or prefer open-source flexibility:

• Slack Native AI & Knowledge Search : Slack features built-in architecture explicitly designed to handle unstructured chat history by indexing connections between users, files, and channels using a backend knowledge graph layout. This powers features like Slackbot's enterprise search and automated thread summaries.
• AirWeave AI : An open-source option that installs as a Slack Knowledge Assistant . It monitors channels, threads, and linked document hubs to formulate answers backed by hybrid contextual memory and cited sources.

To narrow down the best platform, let me know:

• Do you want a plug-and-play marketplace app or a fully customizable developer API?
• Do you need the graph to bridge Slack data with other systems like GitHub, Notion, or Salesforce?
• What is your team's budget and preference toward open-source data ownership?

Yes. If by “builds a knowledge graph” you mean continuously turning Slack conversations into connected, reusable organizational knowledge, a few products stand out:

• tallow.dev — Probably the closest literal match. It connects to Slack and other tools, continuously maps relationships among conversations, documents, tickets, and code, and describes the result explicitly as a living knowledge graph.
• kennishq.com — Focuses on automatically building institutional knowledge from conversations. It connects to Slack/Teams, synthesizes discussions into a company knowledge base, and exposes that knowledge through an API/MCP for AI agents.
• getguru.com — More mature enterprise knowledge-management option. Its Slack integration captures conversations, decisions, and updates and turns them into reusable, governed knowledge, with permission-aware answers and automated verification.
• slack.com — If you don't actually need an explicit graph, Slack now has native AI that understands your organization's conversations and files. Slackbot also builds personal memory from Slack activity.

My shortlist: If the requirement is specifically “ingest our daily Slack conversations and construct a connected knowledge graph,” I'd investigate Tallow and Kennis first. If you need a more established, enterprise-governed knowledge layer, Guru is the stronger candidate.

If you tell me roughly company size (e.g. 20 / 200 / 2,000 people) and whether you need private DMs included, I can compare these on security, Slack permissions, graph capabilities, pricing, and maturity.

Several companies offer specialized bots and platforms that integrate with Slack to construct a live knowledge graph directly from your daily conversations.

Depending on whether you want an out-of-the-box product, a customizable AI enterprise graph, or an open-source tool, you have excellent options available:

Dedicated AI Knowledge Graph Bots

• WRITER : This platform features a powerful integration with Slack powered by its proprietary graph-based Retrieval-Augmented Generation (RAG) technology. It continuously indexes and transforms your team's text, structured files, and conversational data into a highly organized business Knowledge Graph . Teams can query it in natural language directly from Slack to surface deep insights.
• Graph : Available on the Slack Marketplace , this AI assistant maps connections between your Slack workspace communications, software tickets, and code repositories (like GitHub, Jira, and Linear). It interprets team progress and maps contextual relationships across your work data.
• Graphlit : If you want to develop a tailored solution, Graphlit provides a conversational framework that automatically extracts entity relationships from Slack content to generate a dynamic, backend knowledge graph for your chats.

Alternative Automated Slack Knowledge Assistants

If you are looking to capture knowledge natively or prefer open-source flexibility:

• Slack Native AI & Knowledge Search : Slack features built-in architecture explicitly designed to handle unstructured chat history by indexing connections between users, files, and channels using a backend knowledge graph layout. This powers features like Slackbot's enterprise search and automated thread summaries.
• AirWeave AI : An open-source option that installs as a Slack Knowledge Assistant . It monitors channels, threads, and linked document hubs to formulate answers backed by hybrid contextual memory and cited sources.

To narrow down the best platform, let me know:

• Do you want a plug-and-play marketplace app or a fully customizable developer API?
• Do you need the graph to bridge Slack data with other systems like GitHub, Notion, or Salesforce?
• What is your team's budget and preference toward open-source data ownership?

Yes. A few products now do essentially this, but they differ in whether they build a true knowledge graph versus a searchable “team memory.”

Best matches

• kennishq.com — Probably the closest match to what you're describing. It connects to Slack, ingests the last 90 days of conversations, extracts institutional knowledge, and keeps the knowledge base updated daily. It explicitly exposes the resulting knowledge through an API/MCP for AI agents.
• github.com — More explicitly graph-oriented: it extracts facts from Slack conversations, creates topic pages, and maintains a graph connecting people, decisions, and projects. It's open source.
• github.com — Another very direct fit. Its Slack bot scans history, learns from new conversations daily, detects conflicts, and uses a knowledge graph + hierarchical retrieval underneath.
• getguru.com — A more established enterprise option. Guru can turn Slack conversations, decisions, and updates into reusable, governed knowledge, with permissions, verification, citations, and MCP support. It's less “here is your graph” and more “continuously maintained organizational knowledge layer.”
• teammemory.io — Simpler approach: monitors selected Slack channels, automatically extracts useful Q&A, and builds a searchable knowledge base linked back to the original conversations.

One important wrinkle

You may not actually need a third-party bot anymore. Slack itself has moved substantially in this direction. Slackbot now builds personal memory from conversations, while Slack's enterprise search/AI layer uses permission-aware knowledge from conversations, files, and connected systems.

If by “knowledge graph” you specifically mean something like:

Person → owns → Project → depends on → System → decided → Architecture → discussed in → Slack thread rather than simply “AI can search our old Slack messages,” I'd shortlist Kennis, Beever Atlas, and IncidentFox.

If you tell me roughly your company size and whether you want SaaS vs. self-hosted, I can narrow this to the 2–3 strongest options and compare Slack permissions, privacy/data retention, graph capabilities, pricing, and setup effort.

If you want an AI assistant that plugs into Slack and actively maps your company's communication, documents, and people into a living interconnected framework, a few prominent platforms offer this functionality:

• Glean: Glean indexes all of your enterprise SaaS tools—including deep integration with your Slack workspace—and builds a real-time Glean Knowledge Graph . It doesn't just read chat logs; it correlates content, people (roles and relationships), and daily user activity so it can answer questions in Slack with precise attribution to who made a decision and where.
• Slackbot Memory (Native Slack AI): Slack's native built-in AI features now include a memory layer for Slackbot. It automatically processes and learns from your workspace's conversations over time, retaining context about ongoing projects, team topics, and preferences directly inside Slack's secure environment without needing a third-party pipeline.
• Custom Graph Pipelines (e.g., Neo4j + LLMs): If you have specific data-privacy mandates or want a bespoke topology, many engineering teams export their Slack archives (via JSON) and pipe them into graph databases like Neo4j via Node.js scripts combined with NLP/LLM entity extraction.

If you're looking into this, let me know:

• Do you need it to only look at Slack , or connect across other tools (like Google Drive, Notion, or Jira)?
• What is your team size and security/compliance requirement?

I can help narrow down whether a turnkey enterprise platform like Glean or a custom approach fits best.

Yes. If by “builds a knowledge graph” you mean continuously turns Slack conversations into structured, connected organizational knowledge, there are a few interesting options:

• entilla.com — Probably the closest match to your description. It explicitly describes a living knowledge graph that ingests Slack conversations, documents, meetings, tickets, etc., resolves entities and relationships, and continuously syncs them. It supports Slack plus Gmail, Drive, GitHub, Linear, Salesforce, and more.
• tallow.dev — Specifically pitches itself as turning Slack conversations into a “living knowledge base,” continuously mapping relationships among conversations, documents, tickets, and code into a searchable knowledge graph. It currently says Coming Soon, though.
• github.com — A more DIY option. Its Slack bot scans history, learns from new conversations daily, detects conflicts with existing knowledge, and uses a knowledge graph + RAPTOR trees + multi-strategy RAG underneath.
• getguru.com — More mature/commercial, but it's better described as an AI knowledge layer than a literal graph product. It can capture knowledge from Slack conversations and turn decisions/updates into reusable, verified knowledge automatically.
• tettra.com — Its Kai bot builds a knowledge base from conversations already happening in Slack, but again, this is primarily a knowledge base/RAG system rather than an explicit knowledge graph.

My shortlist

If the graph itself is important, I'd investigate Entilla first, then Tallow.

If what you really want is “our Slack conversations become a continuously updated company brain that people can query”, I'd also put Guru and Slack's own Slackbot/Enterprise Search into the comparison. Slack now supports AI over permissioned conversations and connected data, including contextual answers and daily recaps.

If you tell me roughly how big your Slack workspace is and whether you want SaaS vs. self-hosted, I can narrow this to the 2–3 products that are actually worth evaluating.