Advanced RAG for
Business Requirements.

Ingest messy Enron emails, AMI transcripts, and Slack dumps effortlessly via MinerU. Generate premium BRDs instantly powered by a local Qwen 32B model.

500K+ emails processed.
ENRON DATASET
32B parameters of local intel.
QWEN AWQ
8 BRD sections generated.
PARALLEL ASYNC
0 confidential data leaked.
LOCAL FAISS DB

// ARCHITECTURE

Everything you need
to generate specs.

A complete platform for extracting context, resolving conflicts, and drafting Business Requirements Documents automatically.

  ┌───────┐
  │ ◉ ◎ ○ │
  │ ◎ ◉ ◎ │
  │ ○ ◎ ◉ │
  └───────┘

Qwen 32B Local Engine

Inference powered entirely by a Local RTX 4090 GPU for completely private constraint solving with zero API costs.

  ┌─┐   ┌─┐
  │A├──►│B│
  └─┘   └┬┘
        ┌▼┐
        │C│
        └─┘

MinerU Ingestion

Seamlessly parse highly unstructured data with vision encoders from Enron EMLs, AMI Transcripts, and Slack JSON exports.

   ╔═══╗
   ║ ◈ ║
  ┌╨───╨┐
  │░░░░░│
  └─────┘

CRAG Conflict Resolution

Our Cross-Encoder retrieval pipeline autonomously grades context and resolves conflicting requirements across stakeholders.

  │  ▄ 
  │▁ ▄ █ ▄
  │█ █ █ █
  └────────

Traceability Matrices

Generate perfect traceability matrices connecting every generated requirement back to its exact source chunk.

    .--.
   /    \
  | (  ) |
   \    /
    '--'

Instant Generation

Drastically reduce manual documentation time by 80% with instantaneous, high-quality BRD drafting.

  GET /api
  ────────►
  ◄────────
  { data }

Iterative AI Editor

Fine-tune and perfect your BRD sections using our natural-language iterative AI prompt editor.

// PIPELINE

Three steps to
your final BRD.

pipeline.ts
1agent.ingest({
2  source: 'enron_emails.eml',
3  parser: 'MinerU-Vision',
4  chunking: 'RAPTOR-Graph'
5})
Ready

// GLOBAL INFRASTRUCTURE

Built for planetary scale.

Deploy your AI models across our global edge network. Automatic failover, intelligent routing, and sub-100ms latency anywhere in the world.

Lightning Fast CDN

Edge caching and smart routing for optimal performance

Auto-Scaling

Handle traffic spikes with zero configuration

DDoS Protection

Built-in protection against malicious traffic

North America

< 20ms
5 nodes

  ┌───┐
  │ ◉ │
  └─┬─┘
    │

Europe

< 25ms
4 nodes

  ┌───┐
  │ ◉ │
  └─┬─┘
    │

Asia Pacific

< 30ms
3 nodes

  ┌───┐
  │ ◉ │
  └─┬─┘
    │

South America

< 40ms
2 nodes

  ┌───┐
  │ ◉ │
  └─┬─┘
    │

Middle East

< 35ms
2 nodes

  ┌───┐
  │ ◉ │
  └─┬─┘
    │

Africa

< 50ms
1 node

  ┌───┐
  │ ◉ │
  └─┬─┘
    │
17
Data Centers
99.99%
Uptime SLA
1.2B
Requests/day

// LIVE METRICS

Real-time infrastructure
performance.

All systems operational|6:14:22 AM
0
Tokens Embedded
Over the last 24 hours
0%
Data Privacy
Zero external API calls
0t/s
Generation Speed
RTX 4090 Qwen 32B AWQ
0
Parallel Sections
Async WebSocket streams
Live Inference Logs
nowPOST /api/ingestlocal-faiss2001.2s
1sWSS /api/generate/executive_summaryvllm-0STREAM35t/s
2sWSS /api/generate/functional_reqsvllm-0STREAM34t/s
3sGET /api/healthfastapi2002ms

// INTEGRATION ECOSYSTEM

Connect everything.
Build anything.

Pre-built integrations with your favorite tools. No complex setup, just plug and play with our extensive API library.

  ┌─┐
  │#│
  └─┘

Slack

Communication

→
  [█]
  [█]

FAISS CPU

Vector Database

→
  ╔═╗
  ║<║
  ╚═╝

vLLM

Inference Engine

→
  [█]
  [█]

PostgreSQL

Database

→
  ◈◈
  ◈◈

Redis

Cache

→
  ≋≋
  ≋≋

AWS

Cloud

→
  {M}
  ---

MongoDB

Database

→
  ▲
  ─

Vercel

Hosting

→

Fully Extendable Architecture

Our Python FastAPI backend is built to hook into any system. Stream generated markdown directly to your frontend via WebSockets.

// Connect to the Generator Endpoint
const ws = new WebSocket({
url: "ws://localhost:8000/api/generate",
prompt: "Generate BRD based on recent Slack logs"
});

// ENTERPRISE SECURITY

Uncompromising Data Privacy.

Enterprise requirements often contain high-level trade secrets. We never send your data to OpenAI or Anthropic. Everything is processed locally on your own hardware.

  ╔═══╗
  ║ ◈ ║
  ╚═══╝

100% Local Inference

No data ever leaves your servers. Qwen 32B runs entirely on local GPUs.

  ┌───┐
  │ ✓ │
  └───┘

Air-gapped Capable

Operates perfectly without an internet connection after initial model caching.

  ╭───╮
  │ ★ │
  ╰───╯

No OpenAI Tax

Stop paying massive API fees to run giant context windows.

  [===]
  [===]

Supabase JWT

Frontend-to-backend requests secured via Row Level Security.

  ◉─◉─◉
  │ │ │

In-Memory Embeddings

FAISS operates entirely in RAM for zero disk persistence leaks.

  ▪ ▪ ▪
  ▪ ▪ ▪

Source Code Verification

Fully open-source backend for complete transparency.

Technical Validation

Verified local processing capabilities and autonomous privacy controls

Air-GappedVerified
Local LLM32B Params
Zero-TrustArchitecture
FAISSIn-Memory
🔒

Bug Bounty Program

We work with security researchers worldwide to identify and fix vulnerabilities. Report security issues and get rewarded.Learn more →

// FOR DEVELOPERS

Built for developers,
by developers.

A thoughtfully designed SDK that gets out of your way. Ship faster with intuitive APIs and comprehensive documentation.

FastAPI Backend

Asynchronous Python web framework for incredibly high throughput.

WebSocket Streaming

Native support for streaming LLM tokens down to React GUIs instantly.

Local Vectors

Powered by FAISS CPU. No external database dependencies required.

1"text-primary">import httpx
2
3# Send messy emails to the parsing engine
4async with httpx.AsyncClient() as client:
5    response = "text-primary">await client.post(
6        "http://localhost:8000/api/ingest",
7        files={"file": open("enron_dump.eml", "rb")}
8    )
9    print(response.json())
$uvicorn main:app --port 8000
INFO: Application startup complete.
Read the docs|View on GitHub

Stop drafting manual requirements.

Join PMs shipping products faster with auto-generated specifications. Deployed locally on RTX GPUs. No API costs.

No credit card required