High-fidelity pipelines for onchain activity across 125+ networks. Structured outputs feed directly into BI, risk, and trading systems. Institutions gain auditable, consistent, and query-ready data without the internal indexing overhead.
The Indexing Company operates The Neighborhood, a distributed data network designed for institutions that require reliable, performant, and tailored blockchain data infrastructure.
Our system ingests raw onchain activity from 125+ blockchains and transforms it into normalized, query-ready streams delivered directly to enterprise databases, reporting systems, or compliance environments. The Indexing Company provides highly configurable pipelines that merge onchain and off-chain data into a single, controlled environment.
Built for mission-critical use cases, our infrastructure offers:
Our infrastructure can be used for transaction monitoring, compliance, portfolio analytics, and user insights. We save companies engineering costs while gaining faster time-to-market.
The Indexing Company brings institutional standards to blockchain data, ensuring that payment companies, trading desks, asset managers, and enterprises can operate with confidence.
High-fidelity pipelines for onchain activity across 125+ networks. Structured outputs feed directly into BI, risk, and trading systems. Institutions gain auditable, consistent, and query-ready data without the internal indexing overhead.
Cross-chain visibility into stablecoin supply, transfers, and liquidity flows including USDC, EURC, and other major stablecoins. Risk, compliance, and treasury teams need trusted metrics to monitor adoption, exposures, and flows.
Low-latency feeds for swaps, lending, liquidations, and staking. Funds and trading firms require accurate, real-time pricing and exposure data to protect execution quality and manage risk.
Merge blockchain data with off-chain data (RWAs, social, identity, AI datasets) in the same pipelines. Enterprises can build comprehensive intelligence systems, uniting compliance, user behavior, and market data into one framework.
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