Quant Research Platform

A production-scale quantitative research platform demonstrating Vyuh's power: 10TB of financial data made accessible to AI agents through 30+ governed capabilities.

See It In Action →
10TB+
Data Scale
30+
Capabilities
0
Agent Rewrites
5→30
Capability Growth

Making terabytes of financial data AI-accessible

Quantitative research platforms face a unique challenge: massive amounts of complex, time-series financial data that needs to be queried, transformed, and analyzed in sophisticated ways. The data spans multiple domains, each with their own schemas, access patterns, and quality requirements.

Data Complexity

  • Tick-level stock data (sub-second granularity)
  • Options chains with Greeks
  • Fundamental data (financials, ratios)
  • Technical indicators
  • Earnings calendars and transcripts
  • News and sentiment data

Access Requirements

  • Role-based access (analysts vs. traders)
  • Rate limiting on expensive queries
  • Audit trail for compliance
  • Schema validation to prevent errors
  • Smart routing to optimal data sources
  • Cost-aware query planning

Vyuh's capability layer

Using Vyuh's component algebra, we defined 30+ capabilities spanning all data domains. Each capability is typed, validated, and governed—making 10TB of data safely accessible to AI agents.

Market Data
OHLCV pricesTick dataSplits & dividendsMarket hours
Options
Options chainsGreeksImplied volatilityOpen interest
Fundamentals
Financial statementsRatiosAnalyst estimatesInsider trading
Analytics
Technical indicatorsMomentum scoresVolatility modelsCorrelations
Events
Earnings calendarEarnings transcriptsNews feedSEC filings

Zero agent rewrites as the system grew

The key insight: as capabilities were added, the AI agent automatically discovered and used them. No code changes. No retraining. The agent simply became more powerful.

Week 15 capabilitiesBasic price queries
Week 415 capabilitiesScreening + options analysis
Week 830 capabilitiesFull research workflows
Agent code changes:0

What we learned

Capability abstraction works

The agent doesn't need to know about parquet files, database schemas, or API endpoints. It just sees capabilities.

Constraints enable smart routing

The domain layer routes requests to the best source based on timeframe, cost, and latency constraints.

Role-based discovery is powerful

Junior analysts can't even see proprietary capabilities. They don't know to ask for what doesn't exist for them.

Validation prevents disasters

Schema validation catches malformed queries before they hit the database. No more cryptic SQL errors.

Want similar results?

Let's discuss how Vyuh can make your software AI-accessible.