Become Our Customer

API Bricks works with organizations and individuals who build, use, and analyze financial market data. We collaborate with banks, fintech companies, trading platforms, research teams, infrastructure providers, and startups. If your work involves crypto, stocks, FX, or prediction markets data, there is likely an opportunity to work together.
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Reach Out to Us If…

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You need specific market data
  • You’re looking for crypto market data APIs (spot, futures, or perpetuals)
  • You need historical stock market data or T+1 equities data
  • You work with FX rates, currency exchange data, or crypto-to-fiat pricing
  • You need access to SEC filings data or structured regulatory disclosures
  • You want prediction markets data from platforms like Kalshi or Polymarket
You care about data quality and consistency
  • You need normalized financial data across multiple sources
  • You care about clean schemas, stable identifiers, and reproducible datasets
  • You want the same data models for real-time and historical analysis
  • You prefer working with raw or minimally transformed data, not black boxes
You want to reduce integration and maintenance work
  • You want one API instead of many exchange or data provider integrations
  • You want to avoid maintaining exchange-specific quirks and breaking changes
  • You’d rather consume ready-to-use market data than build ingestion pipelines
  • You want to focus on your product logic, not data infrastructure
You’re building or scaling a data-driven product
  • You’re building a trading platform, analytics tool, or research product
  • You’re integrating market data into internal systems or client-facing apps
  • You need data that can scale with usage, volume, and new markets
  • You want a provider that supports custom data or integration requirements
You work with AI, analytics, or research workflows
  • You’re feeding financial data into AI or LLM-based applications
  • You need structured data compatible with MCP or similar frameworks
  • You run backtesting, modeling, or large-scale historical analysis
  • You care about traceability and methodology, not just raw numbers