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orionfold-relay

v0.38.0

Published

Orionfold Relay — a local-first, multi-agent orchestration runtime and builder scaffold for AI-native work.

Readme

Orionfold Relay

Run a forward-deployed AI agency on one cockpit. Every client a workspace, every vertical a profile, every service a workflow, every model a switch — on one governed, cost-controlled board you own.

npx orionfold-relay

Open localhost:3000. Zero config, local SQLite, your data stays on your machine.

npm Next.js 16 React 19 TypeScript Claude Agent SDK OpenAI Codex App Server License

Orionfold Relay is the operations layer for AI builders, consultants, and forward-deployed services teams — the missing layer between "run one agent" and "run a managed service for a roomful of clients." You point it at your client work, run multi-step workflows across local and cloud models, route every client-facing deliverable through human approval, and watch per-client cost roll up automatically. It's local-first, open source (Apache-2.0), and ships as one command.

Relay is the third product in the Orionfold line — Proof answers "which AI can I trust?", Arena answers "which build wins?", and Relay answers "now make the trusted AI do the actual work." It's the only one whose value compounds after evaluation stops.


Describe a pack — Relay builds it

The proof is in what Relay composes, not what it benchmarks. You describe a client module in plain language, and Relay assembles it from its primitives — an agent profile, a workflow blueprint, a schedule, and a table or two — into one installed pack. No new code, no deploy.

A "receipt photo → bookkeeping" module for a property-management client is one prompt away; the next client who needs the same thing reuses it in minutes. The installed pack runs as a first-class instance with its own KPIs, and every agent run under it meters real cost back to that customer — the hardcoded billing line is gone, replaced by live per-client attribution from the usage ledger.

| Compose a pack | Packs gallery | Inside an installed pack | |:-:|:-:|:-:| | Plain-language prompt → a profile + blueprint + schedule + tables, wired into one running module | Installed packs run as first-class instances alongside ready-made starters | Live KPI tiles plus every service workflow as a one-click run — a whole vertical, composed not coded |


The five gaps every AI agency hits

AI agents can already abstract a lease, research a grant, or categorize a receipt. The gap is everything around that — and for an agency, every gap multiplies by the number of clients you serve.

  1. Orchestration — Real client work is multi-step: ingest, abstract, verify, deliver. Relay runs sequences, checkpoints, and planner→executor pipelines without glue code you'd maintain.
  2. Strategy → execution — You think in clients, services, and deliverables; agent tools think in prompts and tokens. Projects, profiles, and blueprints give you a shared language between the engagement and the execution.
  3. Lifecycle — A deliverable needs scheduling, retries, resume-from-checkpoint, cost tracking, and an audit trail. Relay carries the whole operational lifecycle; recurring statements and deadline watches run themselves.
  4. Trust & governance — Agents that read client files and draft client-facing output need guardrails. Relay routes every deliverable through human approval and keeps the audit trail funders and stakeholders ask for.
  5. Distribution — Standing up an agent workspace shouldn't mean cloning a repo and wiring a database. Relay is npx orionfold-relay — one command, zero config, your data stays local.

Built for an agency

| Your operating model | Relay primitive | |---|---| | Clients → one workspace per client, with scoped reference docs the agents consult automatically | Projects | | Verticals → CRE underwriting, listing analysis, grant research, impact reporting — each a tuned agent | Profiles (21 built-ins) | | Services → a repeatable, packaged service you instantiate per client with their variables | Blueprints (15 templates) | | Deliverables → weekly digests, monthly statements, deadline watches running on a cadence | Schedules | | Billing → per-client spend allocation that maps to the retainer, with a real margin you can see | Cost & Usage | | Governance → every client-facing deliverable through human approval with a full audit trail | Inbox |


The three pillars

1 · One cockpit, your whole client book

Every client is a project with its own scoped documents, tasks, and working directory. One Kanban board replaces a wall of browser tabs and a "who's doing what" spreadsheet: lease abstraction, an offering memo, a grant narrative, receipt intake — across clients, every status, on one screen. Drag-and-drop columns or a sortable table.

2 · Multi-vendor, no lock-in

Different work wants different models, and the best model changes every few months. A shared runtime registry lets you switch providers per task, per schedule, or per workflow step without redefining how your agents behave. Run reasoning on Claude, code generation on Codex, document work on Gemini, and route low-stakes or sensitive work to a local Ollama model at $0 compute. The cost dashboard shows the blended mix so you can prove the savings.

3 · Zero-code apps

Profiles, blueprints, schedules, and tables are the Lego bricks. Describe what you want and Relay composes a running app from them — the fastest way an agency ships a new client module. Package a whole vertical (profiles + workflows + a table + KPIs) as one pure-config bundle and install it in one click.


Customers — now first-class

The customer dimension is shipped. Each account you run ops for is a first-class customer record — not a naming convention on a project. Link a customer's projects, and every agent run under them attributes its spend back automatically, so per-client cost is a real rollup from the usage ledger rather than a number you reconcile by hand. That foundation is the seam every pack seeds customers through, and the base for retainer-vs-cost margin.

| The customer book | A customer detail view | |:-:|:-:| | | |


Orchestration — simple to governed

A workflow is how a repeatable service runs itself. The same screen runs six patterns:

  • Sequence — a clean chain of steps an agent works top to bottom
  • Planner→Executor — one agent plans, another executes each step
  • Human-in-the-Loop Checkpoint — pauses at approval gates so nothing client-facing ships without sign-off
  • Parallel — 2–5 concurrent branches followed by one synthesis step
  • Loop — iterative execution with configurable stop conditions
  • Swarm — mayor → worker pool → refinery orchestration

The governance is in the workflow, not bolted on. A blueprint is a fixed step shape plus a Configure form — fill in a client's variables and it becomes a ready-to-run workflow, the same service instantiated for the next client in minutes.


Why it stays trustworthy

  • Local-first — SQLite database, no cloud dependency, npx orionfold-relay and go
  • Relay never sends your data to Orionfold — no telemetry, no update checks, no license server; the complete outbound-network inventory is documented and code-linked in docs/trust/data-flow.md
  • Your rules, enforced — tool permissions, inbox approvals, and audit trails for every agent action
  • Your AI team — 21 specialist profiles ready to deploy, each with instructions, tool policies, and runtime tuning
  • Know what you spend — usage metering, budgets, and per-provider/per-model spend visibility on governed runs
  • Open source & verifiable — Apache-2.0, read the engine and run it yourself; every npm release ships with a provenance attestation and a CycloneDX SBOM (docs/trust/supply-chain.md)

Evaluating Relay for an enterprise? The full trust pack — security packet, data-flow disclosure, supply-chain verification, plain-language license terms, and continuity statement — lives in docs/trust/. Vulnerability reports: SECURITY.md.


Free vs paid

The engine is free. Everything above — orchestration, governance, runtimes, profiles, tables, workflows, the full app — is Apache-2.0 open source with no tiers, no seat gates, and no feature locks. What's paid is premium packs: ready-to-run vertical bundles (profiles + workflows + tables + seed data) that materialize a specific business on top of the free engine.

Buying one takes a license file, redeemed once:

relay license add <path-or-url from your fulfilment email>   # verify + save + unlock
relay license status                                         # who's licensed, what's unlocked, until when
relay license remove <license-id>                            # forget a license (packs stay installed)
  • Verification is 100% offline — an Ed25519 signature check against keys embedded in this repo (src/lib/licensing/verify.ts). Relay never sends your data to Orionfold: no activation server, no telemetry, no network call of any kind. Works air-gapped.
  • Your packs are yours forever. Renewal gets you the year's new and updated packs + priority support. An expired or removed license never re-locks content you already installed — it only gates new premium installs and updates.
  • What's free stays free. Capabilities never move from the free engine into a paid pack. Paid packs are new content, not repossessed features.

The full terms in plain language — seats, transfer, what expiry does and doesn't do — are in docs/trust/license-terms.md. The gating philosophy behind the boundary — and the never-regress promise that binds us to it — is published at orionfold.com/promise. Browse and buy premium packs at orionfold.com/relay.


Runtime bridge

Run the same business process on different AI providers without changing a line of configuration. Relay's shared runtime registry routes tasks, schedules, and workflow steps through Claude Code (Anthropic Claude Agent SDK) and OpenAI Codex App Server, landing everything in the same inbox, monitoring, and cost surfaces. Switching providers is a settings change, not a rewrite.


Tech stack (boring on purpose)

| Layer | Technology | Why | |-------|-----------|-----| | Framework | Next.js 16 + React 19 | Server Components for zero-API reads, Turbopack for fast dev | | Language | TypeScript (strict) | End-to-end type safety from DB schema to UI | | Styling | Tailwind CSS v4 + shadcn/ui | Utility-first CSS with accessible component primitives | | Database | SQLite (WAL) + Drizzle ORM | Zero-config embedded DB, type-safe queries, concurrent reads | | AI Runtime | @anthropic-ai/claude-agent-sdk + codex app-server | Governed Claude and OpenAI execution behind a shared runtime layer | | CLI | Commander + tsup | Familiar CLI framework, fast ESM bundling | | Testing | Vitest + Testing Library | Fast test runner with React component testing | | Validation | Zod v4 | Runtime type validation at system boundaries |

npm distribution name: orionfold-relay (CLI commands relay / orionfold-relay).


Development

git clone https://github.com/orionfold/relay.git && cd relay && npm install

# Set up one or both runtime credentials
cat > .env.local <<'EOF'
ANTHROPIC_API_KEY=your-anthropic-key
OPENAI_API_KEY=your-openai-key
EOF

npm run dev            # Next.js dev server (Turbopack)
npm run build:cli      # Build CLI → dist/cli.js
npm test               # Run Vitest
npm run test:coverage  # Coverage report
npm run test:e2e       # E2E integration tests (requires runtime credentials)

Pull requests

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/your-feature)
  3. Make your changes and add tests
  4. Run npm test and npx tsc --noEmit
  5. Submit a pull request

See AGENTS.md for architecture details and development conventions, and CHANGELOG.md for release history.


All 14 MVP features shipped (CLI bootstrap, database schema, app shell, project management, task board, agent integration, inbox notifications, monitoring, homepage dashboard, workflow engine, AI task assist, content handling, session management). 197 more shipped post-MVP:

| Category | Highlights | |----------|-----------| | Documents (5) | File attachments, preprocessing (5 formats), agent context injection, document browser, output generation | | Agent Intelligence (6) | Multi-agent routing, autonomous loops, multi-agent swarm, AI assist→workflows, agent self-improvement, workflow context batching | | Agent Profiles (2) | Agent profile catalog (21 profiles), workflow blueprints (15 templates) | | UI Enhancement (13) | Ambient approvals, learned-context UX, micro-visualizations, command palette, accessibility, kanban operations, board persistence, playbook docs, workflow UX overhaul | | Platform (8) | Scheduled prompt loops, tool permissions, provider runtimes, OpenAI Codex runtime, cross-provider profiles, parallel fork/join, tool permission presets, npm publish | | Runtime Quality (2) | SDK runtime hardening, E2E test automation | | Governance (3) | Usage metering ledger, spend budget guardrails, cost & usage dashboard | | Chat (12) | 5-tier context engine + CRUD tools, SSE streaming, tool catalog, skill composition, #key:value filters, saved searches, conversation branching/rewind (⌘Z/⌘⇧Z), chat-driven app builder | | Packs (10) | /packs browser, compatible /apps installed-pack surface, starters showcase, 6 layout kits (Tracker, Coach, Ledger, Inbox, Research, Workflow Hub), manifest authoring tools, atomic writes, KPI ratio composition | | Onboarding (2) | First-launch runtime preference modal (Best quality / Balanced / Lowest cost / Best privacy), instance bootstrap with dev-mode gate | | Customers (first-class) | Hard customers table, write-time cost attribution, per-customer rollup, /customers list + detail | | Plugin Platform (5) | Chat-tools plugin kind, MCP plugin spec, plugin tools registry, plugin spec tools, schedule spec tools | | Platform Hardening (2) | Runtime validation hardening, upgrade detection (hourly upstream poll + guided merge sessions) | | Environment (11) | Scanner, cache, dashboard, git checkpoint manager, sync engine, project onboarding, templates, cross-project comparison, skill portfolio, health scoring, profile-from-environment |

See features/roadmap.md for the full inventory and features/stats/snapshot.json for canonical counts.


License

Licensed under the Apache License 2.0.

Copyright 2025–2026 Manav Sehgal