AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
Chronicle keeps every Claude Code, Codex, Copilot and IBM Bob session on your Mac, writes down what was learned, and gives it back to you and your agents.
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A searchable memory of every coding-agent session you run.
Claude Code, Codex, GitHub Copilot, IBM Bob and Google Antigravity sessions and your claude.ai and ChatGPT chats, kept and turned into
knowledge on your own machine.
Your coding agents solve problems all day, and then the lesson disappears: Claude Code deletes transcripts after 30
days, and nothing carries a fix from one session to the next. Chronicle keeps every session, uses Claude Code or Codex
to pull out what was learned, and gives it back to you in a dashboard and to your agents through an MCP server.Read the full README ↗Your coding agents solve problems all day, and then the lesson disappears: Claude Code deletes transcripts after 30 days, and what one agent worked out never reaches the next. Interlatch records what actually happened, every session from every agent, on your machine. It pulls out what was learned and gives it back to you in a dashboard and to all your agents through one MCP server. Each lesson stays latched to its source (the session, project and agent it came from) and earns trust as later work confirms it.
Interlatch was called Chronicle. The chronicle command still works, and an existing install moves over by itself
when you update (Moving from Chronicle).
A session on the demo data. Download the one-minute tour (MP4, 6 MB): Home, a session and its transcript, ⌘K search, the glossary Map and a weekly review.
Interlatch reads each finished session and writes down what is worth keeping. A real example, taken word for word from the demo data:
Gotcha · billing-api Stripe webhook signatures need the raw request body
Webhook.construct_eventverifies the signature over the exact bytes Stripe sent. Parsing to JSON first, or postingjson=in tests, fails withSignatureVerificationError. Readawait request.body()and pass that. From the session "Stop double charges when Stripe retries invoice.paid", extracted automatically.
You need macOS 13 or later and something to analyze sessions: a logged-in Claude Code or Codex, IBM Bob with a Bob API key, or a model provider's API with your own key (Model providers).
Install.
uv tool install --python 3.13 interlatch # or: pipx install interlatch
interlatch install
interlatch install finds the coding agents on your Mac, asks which to record, imports their past sessions and
asks whether to run Interlatch from login. For the app instead, download it from the
latest release (Apple silicon) and
choose Connect.
Use your agents as usual. Each session is recorded when it ends and analyzed in the background.
Explore. Open the dashboard at http://127.0.0.1:11524/ (or interlatch ui --open) and press ⌘K, or ask
your agent what it learned last week.
Connect more agents later from Settings › Sources, interlatch connect <agent>, or by re-running
interlatch install. Install covers what each step sets up and how to remove it.
| Agent | Recorded from | Picked up | Search from the agent (MCP) |
|---|---|---|---|
| Claude Code | ~/.claude/projects transcripts | as each session ends, plus every 15 min | ✅ |
| Codex | ~/.codex/sessions rollouts | every 15 min, once idle | ✅ |
| Codex Cloud | tasks at chatgpt.com/codex (via the codex CLI: title, repo, diff) | every 15 min | via Codex |
| GitHub Copilot | Copilot CLI and agent sessions; Copilot Chat logs in VS Code | every 15 min | ✅ VS Code and Copilot CLI |
| IBM Bob | ~/.bob/db/bob.db, read-only | every 15 min | ✅ |
| Google Antigravity | ~/.gemini/antigravity conversation logs, read-only | every 15 min | ✅ |
| OpenCode | ~/.local/share/opencode/opencode.db, read-only | every 15 min | ✅ |
| claude.ai, ChatGPT | data export: interlatch import <zip> | when you import it | – |
All of them share one dashboard, knowledge base, glossary and set of MCP tools; analysis runs through Claude Code or Codex, whichever you choose. Sources has the details for each.
| Home. Active time, sessions, tokens and estimated cost, day by day. | Map. Your glossary as a mindmap; each term opens into the knowledge and sessions behind it. | ⌘K. One search over sessions, knowledge, projects, terms and commands. |
| Group mindmap. A project group's terms and the links between them, each checked and named by the analyzer. | Career path. In game mode, you are the hero: your level, your path and your rank in each of its modules. | Job goal. A pasted job description as a castle; a tower lights when your rank at a gate meets what it asks. |
Screenshots use made-up demo data.
claude -p, Codex's codex exec, IBM Bob or a model provider's API), which returns a summary and
knowledge items. The call runs sandboxed: no tools, hooks or MCP servers.What leaves your machine: only that redacted digest, sent to Anthropic or OpenAI through your own Claude Code or Codex login, to IBM with your Bob API key, or to the model provider you set up with your own key (with Ollama on your computer, not even that). No telemetry, nothing sent to anyone else. Data and privacy lists what is stored where.
What it costs: through Claude Code or Codex, analysis draws from your Claude or ChatGPT plan like any other use
of the agent; Bob and model providers bill your own account, and Ollama costs nothing. With Claude, in
API terms it averages about $0.38 per session with Sonnet; interlatch analyze --pending --dry-run sizes a backlog before you spend
anything. How analysis works has the details.
Will it slow down my agent? No. The session-end hook hands off to a detached process and returns in milliseconds; analysis runs later in the background.
Do I need Claude Code? No. Analysis runs through Claude Code, Codex or IBM Bob, or a model provider's API with your
own key: Anthropic, Amazon Bedrock, OpenAI, Azure OpenAI, OpenRouter, any OpenAI-compatible server, or Ollama on your own
computer. Pick one when you run interlatch install, in Status › Analysis, or with
interlatch config set analysis.backend <name>
(Model providers). Recording and browsing work either way; with none set up,
sessions are archived and wait in the analysis queue.
Windows or Linux? The desktop app is macOS only. On Windows, uv tool install interlatch and interlatch install
work as on a Mac, with Task Scheduler running the sync and the dashboard (Windows); a
Windows computer joining a team hub is untested yet. On Linux, interlatch install runs the sync and the dashboard
as systemd user units, so a Linux box can be the hub for your other computers. A
team's hub also runs in Docker.
Can I keep a project or a session out? Add the project to sources.exclude_projects in the
configuration, or remove a session for good with interlatch forget <id>.
How do I remove it? interlatch uninstall removes the hooks, background agents and MCP registrations and keeps
your data; add --purge to delete the data too.
More questions, on privacy, cost, teams and updating, are answered in the FAQ. Something not working? See Troubleshooting.
Install · Sources · Dashboard, glossary and Map · Command line · MCP server · VS Code extension · Phone and other computers · A hub in Docker · Joining your team's hub · A copy in Postgres · What gets recorded and how analysis works · Configuration · Data and privacy · FAQ · Troubleshooting · Moving from Chronicle · Development
Issues and pull requests are welcome. CONTRIBUTING.md explains how to run the tests and work on the dashboard with demo data instead of your own sessions.
MIT, except the ee/ directory: the features a company needs to run Interlatch across
its teams (single sign-on, policies, audit export) are under the Interlatch Enterprise License and
need a subscription in production. The interlatch package on PyPI is MIT only.
interlatch CLI.