pig/README.md

<div align="center">

# 🐷 PIG — Prime Intellect Growth

**An open-source, agent-native CRM for two-sided AI-compute companies.**

[![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](./LICENSE)

*Self-hostable. Auditable. Built for teams that buy compute on one side and sell it on the other.*

</div>

---

## Why this exists

A company that aggregates GPU capacity and resells it does not run one pipeline.
It runs two, and its business is the spread between them.

Generic CRMs — Salesforce, HubSpot, Attio — model a single pipeline of deals
against companies. They have no concept of **inventory**, no concept of a
**commitment you already bought and are paying for**, and therefore no way to
answer the question the business actually turns on:

> Which contracted capacity is sold, to whom, at what margin — and what is idle
> right now?

PIG is built around that question. One table, [`allocations`](./packages/db/src/schema/allocations.ts),
joins a `capacity_commitment` (what you bought from a provider) to a
`demand_deal` (what you sold to a customer). Revenue minus cost is margin per
GPU-hour. Committed capacity with no allocation is money burning. Everything
else in PIG is ordinary CRM plumbing that exists to keep that ledger honest.

## Who it's for

PIG models three teams, because two-sided compute companies have three
constituencies competing for the same scarce capacity:

| Team | Job to be done |
|---|---|
| **Supply** | Source, qualify, price, and contract GPU capacity from providers |
| **Demand** | Sell compute and post-training; renew and expand accounts |
| **Research** | Consume capacity internally — real burn, no revenue |

Research is a first-class tenant rather than an afterthought. Internal research
burn competes with revenue for the same GPUs, and margin math that cannot see it
is wrong.

The team set is configurable. PIG ships with these three because they match the
structure of the company it was designed for, not because they are universal.

## Agent-native, not agent-decorated

PIG is a first-class application for agents *and* for humans, and neither is a
degraded view of the other.

- **An MCP server** ([`apps/mcp`](./apps/mcp)) exposes the CRM over both stdio
  and Streamable HTTP. Any MCP client connects: **Claude Code**, **Codex**,
  **[prime-agent](https://github.com/PrimeIntellect-ai/prime-agent)**, or a
  **[Buzz](https://github.com/block/buzz)** workspace agent via its ACP bridge.
  Each team member points their own agent at PIG and works from the terminal.
- **Piggy**, the in-app agent, drains a leased database queue rather than being
  called over HTTP — so work survives the agent being down, and every action it
  takes is recorded with an idempotency key.
- **Every agent-derived fact carries evidence.** Enrichment writes to a `facts`
  table with a confidence score, a band (verified / probable / possible), a
  source URL, and a status. Strong signals apply automatically; weak ones become
  proposals a human approves. A CRM that lets an agent write unattributed claims
  into the record is a hallucination store, not a database.

### The architectural rule

> **Intelligence never lives in the API.**

The API does HTTP, auth, validation, and sync. All research, enrichment,
scoring, and identity matching lives in the agent. They communicate through a
table, never a direct call. This separation is borrowed from
[Comp AI CRM](https://github.com/trycompai/crm) and it is the single most
load-bearing decision in the codebase.

## What makes it compute-native

- **`inventory_listings`** mirrors the Prime Intellect availability API
  field-for-field — `gpuType`, `socket`, `interconnectType`, `stockStatus`,
  `security` (secure vs community cloud), `prices.onDemand`, `provisioningTime`.
  Sync is a straight mapping, not an ETL project.
- **`capacity_commitments`** records what you bought: term, GPU-hours,
  cost per GPU-hour, floor and ceiling.
- **`contracts`** is polymorphic over party and type — MSA, DPA, SLA, order
  form, capacity commitment — because the supply side negotiates heavyweight
  paper while the self-serve demand side runs on a reliability tier and a
  credits policy instead of a signed uptime guarantee.
- **Two real pipelines**, with stages taken from how this market actually
  operates rather than invented:

  ```
  Demand:  qualification → legal → scoping → proposal → procurement
           → POC → deployment → expansion

  Supply:  sourced → qualifying → technical diligence → financial diligence
           → pricing → contracting → onboarding → live → renewal
  ```

  Note that **legal sits second** in the demand pipeline. MSA and DPA execution
  gates the deal rather than closing it. Most CRMs put contracts at the end and
  are wrong about it for this market.

## Stack

| Layer | Choice |
|---|---|
| Web | React + Vite + TypeScript, Tailwind, shadcn/ui, light + dark |
| API | Hono + tRPC on Node 22+ |
| Database | PostgreSQL 16, Drizzle ORM |
| Auth | Supabase (JWT verification only — PIG stores no passwords) |
| Agent | Piggy — a worker draining a leased task queue |
| MCP | `@modelcontextprotocol/sdk` — stdio + Streamable HTTP |
| Deploy | Docker Compose behind any reverse proxy |

Authorization comes from PIG's own `users` table, never from the mere existence
of an auth account. An identity provider that PIG shares with another
application must not grant access here.

## Quick start

```bash
git clone <this-repo> pig && cd pig
npm install
cp .env.example .env        # then edit it
npm run db:migrate
npm run db:seed             # optional — public, sourced, confidence-graded
npm run dev:api             # :8920
npm run dev:web             # :5173
```

Connect an agent:

```bash
claude mcp add pig -- npx -y @pig/mcp          # stdio
# or point any MCP client at https://<your-host>/mcp
```

## Repository layout

```
apps/
  web/        React + Vite front end
  api/        Hono + tRPC API, Supabase JWT verification
  mcp/        MCP server — stdio and Streamable HTTP
packages/
  db/         Drizzle schema, migrations, seed
  core/       Shared domain types and the ontology
  prime/      Typed client for the Prime Intellect compute API
docs/         Ontology, deployment, seed-data provenance
deploy/       Compose files and reverse-proxy snippets
```

## Documentation

- [Ontology](./docs/ontology.md) — the domain model, and why it is shaped this way
- [Seed data provenance](./docs/seed-data.md) — every claim, graded and cited
- [Agent integration](./docs/agents.md) — Claude Code, Codex, prime-agent, Buzz
- [Deployment](./docs/deploy.md) — self-hosting

## A note on seed data

PIG ships with a roster of publicly documented people so the application is
legible on first run. Every record carries a confidence grade and a source URL.
**No email addresses are included or inferred.** Records that could not be
independently sourced are marked as such rather than quietly presented as fact,
and people who are demonstrably *not* staff — alumni, residency participants —
are labelled accordingly. See [docs/seed-data.md](./docs/seed-data.md).

If you are seeded here and would rather not be, open an issue and it will be
removed.

## Licence

Apache License 2.0 — see [LICENSE](./LICENSE) and [NOTICE](./NOTICE).