vexa

Why Vexa

Every meeting-AI tool you can buy sends your conversations to *their* cloud and rents you

access back. Vexa inverts that: run the stack yourself, point it at your own models, own what

your meetings become.

No one else has all three:

1. **Vexa is *in* the meeting.** A real bot joins Meet, Teams and Zoom — Jitsi offline-proven, live

validation pending — and streams speaker-attributed transcripts live. That bot fleet is the

genuinely hard part — every "chat with your docs" tool starts *after* a transcript exists. Vexa

produces it.

2. Your knowledge is files you own. Meetings compile into Markdown in a git repo —

portable, diffable, greppable. Knowledge as code.

3. Agents work it, safely. Sandboxed coding agents read and write that repo like

developers — isolated ephemeral containers, no egress, thousands in parallel, on Docker

or your Kubernetes.

> Only here for the transcription API? It's a complete standalone product — send a bot,

> read the stream, ignore the agent lane entirely.

⚡ Quickstart

Just want a bot in a meeting? Use the hosted service — no install. Sign in at

vexa.ai/signin, copy your key from your account page,

and send a bot:

curl -X POST "https://api.cloud.vexa.ai/bots" \
  -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"platform":"google_meet","native_meeting_id":"abc-defg-hij","bot_name":"Vexa"}'

New accounts get $5 of free bot credit, no card required — about 16 hours of bot time at

$0.30/hr (pricing). More calls: Send a bot.

Or self-host the whole stack

That is also how you get the agent plane, which is not part of the hosted service.

Self-host on one host, then explore it in the Terminal or drive it over the API.

Linux (Ubuntu 24.04) is the production target; a Mac with Docker Desktop works fine for a local

evaluation — everything runs in containers either way.

Prerequisites — `make`, Docker engine ≥ v26 (`make all` checks), and transcription: a free token at

vexa.ai/account, or self-host the (GPU) transcription unit for a fully

air-gapped setup. By default `POST /bots` requires STT and answers 503 when it is missing

(`make all` warns when the credentials block in `.env` is empty). Capture-only is an explicit opt-out:

`{"transcribe_enabled": false}` on the spawn (or set `TRANSCRIBE_ENABLED=false` for the deployment).

> Build machine: `make all` pulls the published, release-validated images — no build, so a

> modest box is fine. `make lite` (the single-container all-in-one image) is lighter still. Building

> from this checkout instead (`make dev`, for contributors) wants 8 vCPUs and 16 GB RAM.

git clone https://github.com/Vexa-ai/vexa.git && cd vexa
make all      # full Docker Compose stack — seeds .env, pulls the images (bot included),
              # prints your API key + URLs. Contributors: `make dev` builds from this checkout.

When `make all` finishes it prints your key and URLs:

Terminal UI : http://localhost:13000     # the web workbench
  API gateway : http://localhost:18056     # the API
  API key     : vxa_…

Explore in the Terminal (the fast path)

The Terminal is the way to see what Vexa can do. Open `http://localhost:13000` — you're

already signed in to a self-host account. From the

workbench you can, with no curl:

• Send a bot — paste a Meet / Zoom / Teams / Jitsi URL; a bot joins as a participant.
• Watch the transcript stream in live, speaker-attributed, draft-then-confirmed.
• Chat with your workspace — ask an agent that has every captured meeting as context, and watch it

commit what you decide.

Or drive it over the API

export API_KEY=vxa_...
export API_BASE=http://localhost:18056

# WIN 1 — send a bot into a live call, then read the transcript as it streams
curl -X POST "$API_BASE/bots" \
  -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"platform":"google_meet","native_meeting_id":"abc-defg-hij","bot_name":"Vexa"}'

curl -H "X-API-Key: $API_KEY" "$API_BASE/transcripts/google_meet/abc-defg-hij"

# WIN 2 — ask an agent that has your whole workspace as context (answer streams back as SSE)
curl -N -X POST "$API_BASE/agent/chat" \
  -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"prompt":"What did we decide in my last meeting?"}'

`platform` is `google_meet` · `teams` · `zoom` · `jitsi`; `native_meeting_id` is the code from the join URL. The

agent reply streams as Server-Sent Events — `message-delta` frames carry the text, `commit` frames mark

anything it recorded into your workspace.

🧩 How it works

One gateway, two domains — Meetings (capture) and Agents (work the knowledge) — both running on

the same runtime: the engine that spawns every bot and every agent in its own sandboxed container.

A bot and an agent are the same `runtime.v1` workload — isolated, ephemeral, reaped on idle — so the

machinery already proven by thousands of meeting bots is exactly what runs your agents. Every arrow stays

inside your network.

⚙️ The agentic runtime

A CLI coding agent is just a process on Linux. The runtime makes that a multi-tenant,

sandboxed execution layer safe to point at real business data — the same engine that already

spawns Vexa's meeting bots in production.

• Isolated. Every dispatch gets its own container: no egress except brokered tools, and

only its granted workspaces exist in its filesystem — enforced by the substrate, not by the

agent. Agents never run in the control plane.

• Ephemeral. A container lives while it works and is reaped on idle; continuity is a

session file in the workspace. Sub-second starts, thousands in parallel.

• Orchestration-agnostic. One `runtime.v1` lifecycle, pluggable substrate — the same

dispatch runs identically across:

Same control plane, same worker — only how the container is created changes. One laptop to a

Kubernetes/OpenShift cluster, inside your walls.

🧠 Agents & your workspace

Capture is the front door; agents make the knowledge compound. Every meeting compiles into

your workspace — a git repo of Markdown (an Open Knowledge Format

`kg/` bundle) that agents (Claude Code, Codex, …) read and write like developers work a codebase.

> This is Andrej Karpathy's **LLM Wiki**

> pattern, run as a team service. The idea: don't RAG over raw documents — where the model

> rediscovers everything from scratch on every question — have agents compile sources into

> structured, interlinked markdown entity pages (people, companies, projects, decisions) so

> knowledge compounds. Vexa builds that wiki for you from the richest source there is: your

> meetings. Each call is ingested into entity pages; agents keep them current between calls; every

> answer starts from what your team already knows — on your own servers.

Agents work *any* workspace; a meeting is just one trigger of four — chat, schedule

(cron), event (e.g. incoming email), finished meeting. Meetings themselves are scheduled

work: connect your calendar (ICS) and planned meetings appear with attendees — bots

auto-join, agents prepare before the call and process after it.

• Multiplayer. Team-shared, attributed workspaces — not one person's private notes.
• Automated. The bot captures the call; the transcript compiles itself in.
• Safe by design. Agents are untrusted and enforce nothing themselves. You, in chat, write

directly (git is the undo); untrusted input — an email, a web page — runs propose-only:

the agent suggests, a human approves, trusted code applies. Irreversible effects are always gated.

> Status (honest): capture, transcription, and speaker attribution are production; the

> agent dispatch core is built and proven live end-to-end. What's still landing is tracked in

> Status.

🖥️ The Terminal: AI-augmented meetings

0.12 ships a new Terminal UI built to put the backend's scale — thousands of bots and

agents — to work on your actual week. It opens on your meetings: coming up, live now, to review.

• An agent in your meeting, with your knowledge. Open a live call: the transcript streams

speaker-attributed, and the agent has the live conversation *and* your workspace in context.

Ask mid-call "what did we promise them last time?" — or research a person, company, or

contract the moment it comes up, grounded in your wiki.

• Knowledge built on meetings — and between them. Every planned meeting gets an agent that

prepares the brief before (who's coming, history, open threads — it interviews *you* for

what it can't know) and processes the transcript after. Arrive prepared, leave with the

wiki updated.

• Sharing. Invite colleagues into a workspace — same wiki, attributed. Share a meeting with

its attendees — they get the real-time feed, not a recording link after the fact.

• Collaborative, AI-augmented meetings. Prep a shared workspace together; during the call,

humans edit the brief while agents stream the transcript in and work the knowledge — one room,

human and AI participants on the same files.

📖 How-to recipes

Each is a complete path to one outcome over the Agent API. Full guides at

docs.vexa.ai.

💬 Chat with your workspace — ask an agent that has every meeting, email, and note as context; trusted

chat can also record a decision (a git commit).

curl -N -X POST "$API_BASE/agent/chat" -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"prompt":"Brief me on the Acme account: every meeting, the open decisions, and the next step."}'

🌅 Brief me every morning — an unattended agent on a cron schedule that commits to your workspace.

curl -X POST "$API_BASE/agent/routines" -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"name":"Morning brief","cron":"0 8 * * 1-5",
       "prompt":"Brief me from overnight activity — new meetings, decisions, follow-ups due. Write brief/today.md.",
       "run_now":true}'

📝 Report after every meeting — dispatch a one-shot agent when a call ends (or a routine that sweeps

recent meetings).

curl -X POST "$API_BASE/agent/invocations" -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"runner":"claude-code","workspaces":[{"id":"u_jane","mode":"rw"}],"trigger":"scheduled",
       "start":{"entrypoint":{"inline":"Write a report for the meeting that just ended: summary, decisions, action items with owners."}}}'

📧 Triage incoming email (safely) — an event-triggered agent that gets the mailbox read-only and can

only *propose* actions as cards; a human approves before anything is written or sent.

curl -X POST "$API_BASE/agent/events" -H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
  -d '{"name":"email.received","source":{"uri":"mailbox://u_jane/INBOX/AB12CD"},
       "plan":{"prompt":"Triage this email into tasks; propose a record for each action item and a draft reply."}}'

> Live-meeting copilot — cards for people, decisions, and action items *during* the call

> (`POST /agent/meeting/start` → stream `GET /agent/meeting/stream`) — is on the roadmap; see

> Status.

🚀 Deployment options

Two ways to run Vexa, one codebase:

1. Personal / dev — Docker on your Mac, Linux, or Windows machine.

Single container (`make lite` — the all-in-one Vexa Lite image) or the full Compose stack

(`make all`). Reuse your Claude subscription: workers run the official `claude` CLI against

your own Pro/Max credential, which is a covered, credit-metered use under Anthropic's terms for a

personal deployment — your subscription, your turns, your machine. See

Model credentials & licensing for the exact

terms mapping (Anthropic's Agent SDK plan-usage article

is the primary source). You get the full service — bots, transcripts, agents, Terminal — on the

subscription you already pay for.

2. Cloud — Helm on Kubernetes / OpenShift, scalable to thousands of users.

The chart in `deploy/helm` deploys the same control plane with

`RUNTIME_BACKEND=k8s`: every bot and every agent is its own Kubernetes workload (a bare Pod

per dispatch), so capacity is your cluster's scheduler, not a bigger box — built multi-tenant and

multiuser from the start. One compliance rule when you go multiuser: other users' turns must run

on an API key (Commercial Terms), never a personal subscription credential — the

licensing page spells out the boundary, and

Settings → Models enforces per-user/global credential resolution. K8s backend status is tracked

honestly in Status.

🏠 Deploy & configure

`make all` brings up the full stack via Docker Compose on one Linux host — each service in its own

container, bound to loopback:

• Runtime backend — `RUNTIME_BACKEND=docker` (default) or `k8s` (a Pod per dispatch).
• Transcription is a separate GPU unit — `make all` runs GPU-free; stand up the STT service

(faster-whisper, OpenAI-compatible) from `deploy/transcription` on any GPU box and point `.env` at it.

Or use a free hosted token at vexa.ai/account while testing.

• Bring your own inference — point the agent at your own LLM endpoint; no inference leaves the network.
• Air-gapped — everything in-VPC, zero egress — the posture the regulated verticals require.
• Targets — `make all` (pulls) · `make dev` (builds from this checkout) · `make lite` ·

`make probe` (full-journey smoke) · `make down` · `make help`. Expose the Terminal via a TLS reverse proxy for

production; full guide in the docs.

🆚 How Vexa is different

The crowded "AI second brain / self-hosted knowledge base" space is full of excellent tools for

reasoning over documents you *already have*. None of them join a live meeting — they consume

transcripts other tools produced. That's the whole point: **capture is the moat, and it sits

upstream of where a document-RAG tool's architecture even starts.**

Against the tools developers actually weigh for meeting capture:

Vexa is the one combination the others don't offer: a **permissively-licensed (Apache-2.0)

meeting-bot-API server that is self-hosted × real-time × multi-platform × knowledge-you-own.**

And it's *complementary* to the document-RAG and "second brain" tools — feed them Vexa's clean,

attributed transcripts and let them do what they're good at.

The full field — including Attendee (the other

meeting-bot API, source-available under the Elastic License 2.0, which does not permit providing

it to third parties as a hosted or managed service) and the local-notetaker tools — is mapped

honestly, trade-offs and all, in How Vexa compares.

🏦 For regulated enterprises

For banks, healthcare, government, and anyone in a regulated industry, the meeting-AI question

isn't "which cloud" — it's "how do we get this without a cloud." Vexa is **air-gapped meeting

intelligence** — the sovereign alternative to Microsoft Copilot — built for exactly that buyer.

You don't compete with a notes app here — you replace Microsoft 365 Copilot and **Zoom AI

Companion** on the axes they structurally can't move:

What that means in practice:

• Air-gapped — fully offline, your infrastructure, your models. Nothing phones home.
• Adaptive — your engineers implement requirements directly: domain vocabulary, underserved

languages, custom workflows. No vendor feature queue.

• Owned, not rented — deploy once, extend without asking permission. No per-seat tax.
• Scales inside your walls — thousands of isolated agents in parallel on Docker or your

Kubernetes/OpenShift cluster.

Evaluate it for your org — the artifacts a security review asks for, in this repo:

Full review page: Security & compliance in the docs.

> Regulated banks and Fortune-500s run Vexa fully air-gapped on their own OpenShift and local LLMs today.

📡 API reference

Two APIs behind the gateway, authenticated with `X-API-Key`. Base URL: `http://localhost:18056`

(self-host) or `https://api.cloud.vexa.ai` (hosted).

Meetings API — capture; usable standalone:

Agent API — the control plane, under the `/agent/*` prefix (identity is derived from your key, server-side):

`platform` ∈ `google_meet` · `teams` · `zoom` · `jitsi`. The gateway also serves an MCP endpoint

at `/mcp` for agent clients (docs). Full reference:

**docs.vexa.ai**.

> v0.12 note: live bot-control — `PUT /bots/{…}/config` (change language/task mid-call) and

> `POST /bots/{…}/speak` (TTS into the call) — plus the live-meeting copilot (`/agent/meeting/*`) and

> WebSocket streaming are not yet wired in the open-core stack and return `404` today. Send-a-bot, stop,

> status, transcripts, recordings, agent chat, routines, and events are live.

🗺️ Status & roadmap

Honest state of the 0.12 line (mirrors the status page — never aspirational):

✅ Production · 🟡 In progress · 🔵 Planned

🤝 Community & contributing

• Docs — docs.vexa.ai
• Discord — discord.gg/Ga9duGkVz9
• Roadmap — the board, grouped by contributor

lane, with milestones as the version gates.

• Contributing — how delivery works: prepared issues

with acceptance tables that *guarantee* merge, and human validation credited as a first-class

contribution (one page, law and how-to together).

• Contributor rights — one rights choice plus DCO for individuals;

private, head-bound authorization when an employer or client owns the work.

• Issues & PRs — welcome. See `SECURITY.md` to report vulnerabilities.
• Obsidian: obsidian-vexa-bridge turns completed meetings into Obsidian notes or a knowledge graph, a third-party adapter; see the docs.

Vexa is built in the open. If you self-host it, extend it, or run it air-gapped somewhere interesting,

we'd love to hear about it.

📄 License

Apache-2.0. Own it, run it, fork it, ship it. It's an investment, not a rental.