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Workforce Intelligence & Deployment Platform

AI-native recruiting operating system targeting GSI/FSI cleared contract staffing and enterprise sales/SE recruiting.

Status: under active construction. Built from ~/.openclaw/agents/sapor/memory/PLATFORM-BLUEPRINT.md (the canonical product spec). See docs/SPRINT-STATUS.md for what is done, what is stubbed, and what requires real third-party credentials to enable.

Repository layout

services/        Python FastAPI services + Temporal workers (one dir per agent / domain)
  rules/           Sprint 2 — OPA-backed rules engine API
  screening/       Sprint 3 — screening agent
  outreach/        Sprint 4 — outreach + close protection
  pipeline/        Sprint 5 — Temporal pipeline orchestration
  client-advisory/ Sprint 6 — client advisory + client development
  interview/       Sprint 7 — voice/chat interview agent
  capture/         Sprint 8 — pre-award capture intelligence
  outcomes/        Sprint 9 — outcome loops + predictive ML
  bench/           Sprint 10 — bench management + compliance
  market/          Sprint 11 — market intelligence + data products

packages/        Shared libraries
  schemas/         Pydantic + TypeScript shared schema definitions
  rules-sdk/       Client SDK for the rules service
  audit/           Audit-log writer (ClickHouse)
  events/          Kafka/Redpanda event publisher + consumer helpers
  llm/             Model router + prompt-cached Anthropic client

apps/
  command-center/  Sprint 6 — Next.js client/internal dashboard
  candidate-portal/ Sprint 12 — Next.js candidate-facing portal

infrastructure/
  docker/          docker-compose.yml for local dev (PG+pgvector, ClickHouse, Redis, Temporal)
  terraform/       AWS production stack (RDS, ElastiCache, ECS Fargate, ALB, Secrets, alarms)
  k8s/             Kubernetes manifests (alternative deployment)
  migrations/      SQL migrations for ClickHouse
  schema/          Prisma schema (PostgreSQL operational DB)

rules/           OPA policy bundle (.rego files + tests)

docs/            Architecture decisions, sprint status, runbooks

Getting started

Prerequisites

  • Node 20+, pnpm 9+
  • Python 3.12+, uv
  • Docker + Docker Compose
  • (For OPA dev) opa CLI: brew install opa

One-command bootstrap

make bootstrap     # installs all deps, brings infra up, runs migrations, generates clients
make test          # runs all test suites
make dev           # starts every service in dev mode (uses overmind/foreman)

Individual services

Each services/<name> and apps/<name> has its own pyproject.toml / package.json and can be run standalone. Run make help for the catalogue.

Tech stack at a glance

Layer Tech
Operational DB PostgreSQL 15 + pgvector
Analytical DB ClickHouse
Workflow Temporal
Streaming Redpanda (Kafka-compatible)
Rules Open Policy Agent (OPA)
Backend Python 3.12 / FastAPI
Frontend Next.js 14 + React 18 + Tailwind
ML scikit-learn (Sprint 9), Feast (feature store)
LLM Anthropic Claude (model router: Opus / Sonnet / Haiku) with prompt caching
Auth Clerk-shaped adapter (works with Clerk; mock for dev)
Email SMTP (free) primary, SendGrid adapter for production
SMS Twilio adapter (no free tier — interface only by default)
Voice AI Vapi/Retell adapter interface (no free tier — see docs/INTEGRATIONS.md)
Object storage S3-compatible (MinIO in dev)

Regulatory invariants enforced in code

  1. Every AI decision is audit-logged to ClickHouse with input summary, decision, reasoning, model, confidence — see packages/audit.
  2. Rules engine handles process; LLMs handle judgment. Every endpoint that calls an LLM first runs deterministic guards. See services/rules.
  3. Candidate ownership (exclusivity, RTR, DNC, non-compete) is enforced before any submission action — services/rules ownership policies.
  4. Human escalation triggers are first-class — VP+ candidates, $350K+ comp, mixed signals, etc. — never silenced.
  5. EEOC/OFCCP traceability: every screen / submit / offer recommendation has a permanent reasoning record.

Build status

See docs/SPRINT-STATUS.md for per-sprint completion + what requires real credentials to graduate from interface-only to production.

About

Autonomous AI recruiting platform. recruiters post jobs, candidates submit resumes, and the system parses those resumes and matches candidates to open roles.

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