> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clypt.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# B2B Quant Solutions

> Enterprise quant infrastructure — Quant DB, LLM agent teams, and white-label engine

## Overview

Clypt's B2B offering provides **institutional-grade quantitative infrastructure** for hedge funds, prop trading firms, and fintech companies. Built on the same ClyptQ engine that powers the consumer platform, B2B solutions add enterprise features: dedicated databases, LLM-powered research automation, and white-label deployment.

## Products

### Quant DB

A purpose-built database optimized for quantitative research:

| Feature                 | Description                                                       |
| ----------------------- | ----------------------------------------------------------------- |
| **Time-series storage** | Columnar Parquet-based storage optimized for OHLCV and tick data  |
| **Factor library**      | Pre-computed factor exposures (momentum, value, volatility, etc.) |
| **Alternative data**    | News, on-chain analytics, social sentiment, funding rates         |
| **API access**          | REST and Python SDK for direct integration                        |
| **Cross-asset**         | Crypto, equities, prediction markets in unified schema            |

```python theme={null}
# Planned API (subject to change)
from clyptq.enterprise import QuantDB

db = QuantDB(api_key="...")
data = db.query(
    symbols=["BTC/USDT", "ETH/USDT"],
    fields=["close", "volume", "funding_rate"],
    start="2024-01-01",
    end="2024-12-31",
    timeframe="1h",
)
```

### LLM Agent Teams

Autonomous LLM-powered agent teams that accelerate the quant development lifecycle:

| Agent               | Role            | What It Does                                               |
| ------------------- | --------------- | ---------------------------------------------------------- |
| **Research Agent**  | Ideation        | Scans academic papers, generates alpha hypotheses          |
| **Builder Agent**   | Implementation  | Writes ClyptQ strategies from natural language specs       |
| **Backtest Agent**  | Validation      | Runs backtests, analyzes results, suggests improvements    |
| **Risk Agent**      | Risk Management | Reviews strategies for risk exposure, suggests constraints |
| **Optimizer Agent** | Tuning          | Hyperparameter optimization across strategy parameters     |

These agents collaborate in a pipeline:

```
Research → Builder → Backtest → Risk Review → Optimization → Deploy
```

### White-Label Engine

License the ClyptQ engine for proprietary use:

| Feature                 | Description                                           |
| ----------------------- | ----------------------------------------------------- |
| **Self-hosted**         | Deploy on your own infrastructure                     |
| **Custom operators**    | Extend the operator library with proprietary logic    |
| **Private marketplace** | Internal strategy sharing without public exposure     |
| **Custom integrations** | Connect to internal data sources and execution venues |
| **Dedicated support**   | SLA-backed technical support and onboarding           |

## Enterprise Pricing

| Tier            | Features             | Model                        |
| --------------- | -------------------- | ---------------------------- |
| **Quant DB**    | Data access + API    | Usage-based (query volume)   |
| **Agent Teams** | LLM agents + compute | Subscription + compute costs |
| **White-Label** | Full engine license  | Annual contract              |
| **Custom**      | Tailored solutions   | Negotiated                   |

## Target Customers

| Segment                | Use Case                                       |
| ---------------------- | ---------------------------------------------- |
| **Crypto funds**       | Replace in-house backtesting infra with ClyptQ |
| **Prop trading firms** | LLM agents for strategy generation at scale    |
| **Fintech startups**   | White-label trading engine for their products  |
| **Research labs**      | Quant DB for academic/commercial research      |

## Timeline

B2B solutions launch in **Phase 4** of the roadmap:

1. **Phase 3**: Quant DB beta (data marketplace foundation)
2. **Phase 4**: LLM Agent Teams + White-Label Engine
3. **Ongoing**: Custom enterprise solutions

## Related Pages

<CardGroup cols={2}>
  <Card title="Investor Overview" icon="chart-pie" href="/platform/investor-overview">
    Revenue model and growth strategy
  </Card>

  <Card title="Rust Conversion" icon="bolt" href="/roadmap/rust-conversion">
    Performance improvements for enterprise workloads
  </Card>
</CardGroup>