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

# 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

Investor Overview

Revenue model and growth strategy

Rust Conversion

Performance improvements for enterprise workloads