Verbatim turns meetings, Slack threads, PRs, and calendar events into a structured, queryable record of every commitment, decision, open question, and blocker — each one sourced to an exact verbatim quote. Then it tells you what's overdue, what's gone stale, and which decisions contradict each other. Open source. Free forever.
$ verbatim ingest standup.txt ✓ Saved 4 items from standup.txt VRB-a1b2c3d4 commitment Qat → ship CULA prototype (Friday) VRB-e5f6a7b8 decision use Kafka for replay cache VRB-9c0d1e2f question who owns the m2w domain config? VRB-3a4b5c6d blocker waiting on Cyren tier-3 JWT $ verbatim show a1b2c3d4 VRB-a1b2c3d4 commitment open high-confidence Actor: Qat Deadline: Friday Quote: "I'll have the CULA prototype shipped by Friday." Source: standup.txt · line 47 · 2026-05-18
Three moving parts: ingest from where work happens, extract with a quote contract, act on what the state graph knows.
Point Verbatim at a transcript, a Slack workspace, GitHub PRs, or a calendar. It runs continuously in daemon mode, or one-shot from the CLI.
verbatim ingest standup.txt
Claude (or a local model) pulls out commitments, decisions, questions, and blockers. Every item must cite the exact quote that produced it — no quote, no claim.
4 items · each sourced
Query it, browse the web UI, project to Linear / Jira / GitHub, or let it nudge you in Slack about what's overdue, stale, or contradictory.
verbatim slack-bot nudge #team
Every extraction must point at the exact words that produced it. No hallucinated action items. No summarized "the team agreed to…" with no receipt.
Actor, deliverable, deadline. Open → confirmed → resolved status flow.
The choice and the alternative it ruled out. Searchable later.
What was asked and not answered. Auto-promotes to a follow-up.
Item, blocked-by, owner. Visible across surfaces until cleared.
Verbatim runs locally as a CLI, daemon, MCP server, or web UI — and bridges into the tools you already use.
Overdue + due-soon tracking, staleness detection, contradiction detection, auto-standup. It tells you — you don't have to ask.
Ask any item to be explained jargon-free. A CEO and an engineer read the same record, each in words they follow.
Typed edges between entities — what resolves what, what answers what — drawn as a visual graph.
Linear-style three-pane browser, dark / light theme, full-text and entity-type filters, per-person views.
Confirm, dismiss, edit, reassign — straight from a Block Kit card. Every action audit-logged.
Watches a folder or Slack, ingests new material, posts digests and nudges. Set and forget.
Plug Verbatim's memory into Claude, Claude Code, or any MCP-aware agent.
Sync commitments to GitHub Issues, Jira, or Linear with one command.
Anthropic Claude by default — or any tool-calling model via Ollama. $0, air-gapped.
Meeting transcripts, Slack (live + export), GitHub PRs, Google & Outlook calendars.
Notetakers summarize one meeting and forget it. Verbatim is a memory layer — continuous, multi-source, and answerable by your agents.
Python 3.10+. One pip install, then run the init wizard.
# install pip install verbatim-ai # interactive setup — picks model, API keys, default surfaces verbatim init # extract from a transcript verbatim ingest meeting.txt # browse the web UI on localhost:8765 verbatim serve # or run fully local on Ollama, no API key required verbatim ingest meeting.txt --model ollama:llama3.1:8b
The questions that come up first.
Is it really free?
Yes — MIT licensed, open source, no paid tier. You bring your own LLM key (or run a local model on Ollama for $0). The only cost is whatever your model provider charges for tokens, and Verbatim ships cost guardrails to cap that.
Where does my data go?
Nowhere you don't control. State lives in a local SQLite file.
Transcripts are sent only to the LLM you configure — and with
--model ollama:… they never leave your machine at all.
Meeting transcripts are the most sensitive corpus a company owns;
Verbatim is built to be self-hosted from day one.
What's the "verbatim quote" contract?
Every extracted item — every commitment, decision, question, blocker — must carry the exact words from the source that produced it. If the model can't quote it, it can't claim it. That's how you trust the output instead of re-watching the meeting.
Do I have to use Claude?
No. Anthropic Claude is the default, but any tool-calling model served
by Ollama works — llama3.1, qwen2.5,
mistral-small. Set VERBATIM_MODEL and go.
How do I get it into my team's workflow?
Run the Slack bot — your team queries state with /verbatim,
triages extractions with Confirm / Dismiss / Edit / Reassign buttons,
and gets deadline nudges. Or wire the MCP server into Claude Code so
any agent can read team state as a tool.
Does it replace Linear / Jira?
No — it projects into them. Your tracker stays the source of truth for work; Verbatim is the source of truth for team state, and pushes the relevant slices into the tools you already use.