Launchstack

The TypeScript engine for AI-native Next.js apps. Ingestion, OCR, RAG, knowledge graph, LLM abstractions, and background jobs — ports-based, framework-agnostic, and designed to be wired into the Next.js app you already have.

Quickstart · Packages · Architecture · Reference app · Contributing · Discussions

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Quickstart

pnpm add @launchstack/core

import { createEngine } from "@launchstack/core";

const engine = createEngine({
  db: { url: process.env.DATABASE_URL! },
  llm: { openai: { apiKey: process.env.OPENAI_API_KEY! } },
  embeddings: { indexName: "openai-3-small" },
  ocr: { defaultProvider: "DOCLING" },
  providers: {},
  storage: myStoragePort,        // you implement StoragePort (S3, local, etc.)
  jobs: { dispatcher: inngest }, // or any JobDispatcherPort
});

// Use any subsystem
const { db } = engine;
const results = await engine.rag?.port.search({ query: "What's in my docs?" });
await engine.close(); // graceful shutdown

Core reads zero environment variables at runtime — you supply the config, which makes the engine portable across Next.js, CLIs, workers, and MCP servers.

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What's in the box

Package	Status	What it does
@launchstack/core	published	The engine. DB, LLM, embeddings, OCR, RAG, graph, crypto, guardrails, ingestion. Framework-agnostic.
@launchstack/features/*	internal	Vertical features built on top of core: adeu, client-prospector, company-metadata, doc-ingestion, legal-templates, marketing-pipeline, repo-explainer, trend-search, voice
@launchstack/features/mcp (planned)	roadmap	MCP server factory — expose core capabilities as tools
@launchstack/features/workflow-generation (planned)	roadmap	LLM-authored workflow DSL
@launchstack/features/rules-extraction (planned)	roadmap	Regulatory rule extraction
@launchstack/features/connectors (planned)	roadmap	Third-party connector integrations
apps/web	—	The Next.js reference app — how we wire everything together

Features import core via subpath imports (@launchstack/core/db, @launchstack/core/ocr/processor, etc.). The reference app imports features and supplies the ports (storage, jobs, credits, RAG) that connect to real infrastructure.

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Architecture

Core exposes four ports that the host wires up. Features depend only on these ports; they never reach into the app or the framework.

          ┌───────────── apps/web (Next.js host) ────────────┐
          │  env.ts  →  engine.ts  →  createEngine(config)   │
          │              │                                   │
          │              └─ wires: StoragePort (S3)          │
          │                        JobDispatcherPort (Inngest)
          │                        CreditsPort (DB)          │
          │                        RagPort (hybrid search)   │
          └──────────────────┬────────────────────────────────┘
                             │
          ┌──────────────────▼────────────────────┐
          │   @launchstack/features/*             │
          │   (adeu, marketing-pipeline, ...)     │
          │   import via @launchstack/core/<sub>  │
          └──────────────────┬────────────────────┘
                             │
          ┌──────────────────▼────────────────────┐
          │   @launchstack/core                   │
          │   db · llm · embeddings · ocr · rag · │
          │   graph · guardrails · ingestion      │
          └───────────────────────────────────────┘

• Core reads no env, knows no framework. All config comes through CoreConfig.
• Features can read process.env, but cannot import from the host app.
• Host owns env, auth, routing, and implements the ports.
• ESLint enforces these boundaries — see eslint.config.js.

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Reference app

apps/web is a production-grade Next.js app built on the engine. It demonstrates:

• Clerk employer/employee auth with role-aware middleware
• Document upload + optional OCR (Marker, Docling, Azure, Landing.AI, Datalab)
• PostgreSQL + pgvector semantic retrieval for RAG
• AI chat with agent guardrails (PII filter, grounding, confidence gate)
• Predictive document analysis across 8 document types (contract, financial, technical, compliance, educational, HR, research, general)
• Marketing pipeline for Reddit, X, LinkedIn, Bluesky
• Inngest-backed background jobs
• Optional LangSmith tracing

Run it locally:

git clone https://github.com/launchstack/launchstack.git
cd launchstack
pnpm install
cp .env.example .env          # fill in required keys
pnpm db:push                  # sync Drizzle schema
pnpm dev                      # Next.js + Inngest on :3000 and :8288

Or spin the full stack (Postgres + SeaweedFS + sidecars) with Docker:

# macOS / Linux
make up          # lite (~400MB RAM)
make up-ocr      # with Docling for Office docs (~1.2GB RAM)

# Windows (PowerShell or cmd — requires Docker Desktop)
docker compose --env-file .env up --build                                                      # lite (~400MB RAM)
docker compose --env-file .env --profile ocr -f docker-compose.yml -f docker-compose.ocr.yml up --build -d   # with Docling (~1.2GB RAM)

Or install make on Windows via Chocolatey (choco install make) or Scoop (scoop install make) to use the make up shortcuts.

Stop the stack:

# macOS / Linux
make down         # stop containers (keeps volumes — DB + S3 data persists)
make down-clean   # stop + wipe volumes (fresh DB on next up)

# Windows
docker compose --env-file .env down                     # stop containers (keeps volumes)
docker compose --env-file .env down -v --remove-orphans # stop + wipe volumes (fresh DB)

See CONTRIBUTING.md for the full dev guide.

Supported document sources

The ingestion pipeline reads exports from common tools without requiring OAuth — just drop the files in:

Source	Export	Adapter
Notion	Markdown & CSV / HTML	TextAdapter, HtmlAdapter
Google Docs / Sheets	DOCX / CSV / XLSX	DocxAdapter, SpreadsheetAdapter
Google Drive	Takeout ZIP	DocxAdapter
Slack	Workspace export JSON	JsonExportAdapter
GitHub	Code ZIP, gh issue/pr list --json	TextAdapter, JsonExportAdapter

Plus first-class PDF, DOCX, PPTX, XLSX, MD, HTML, TXT, and image adapters.

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Using core standalone

@launchstack/core is a plain TypeScript library published to npm — you don't need the monorepo to use it. Drop it into any Node-20+ project that has a Postgres database and implement a StoragePort. The reference app is one way to wire it up; it isn't the only way.

See packages/core/README.md for the full API surface and port interfaces.

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Community & support

• Discussions — github.com/launchstack/launchstack/discussions
• Issues — github.com/launchstack/launchstack/issues
• Security — email per SECURITY.md

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Contributing

We welcome PRs — start with CONTRIBUTING.md. A few things to know up front:

• One issue per PR
• Changes to packages/core/ need a Changeset (pnpm changeset)
• ESLint enforces core/features/host import boundaries; don't work around them

License

Licensed under the Apache License 2.0. By contributing you agree your contributions will be released under the same license.