natural language to smart contract query translation
Converts natural language questions into executable smart contract queries using LLM-based semantic parsing and contract ABI schema mapping. The system analyzes user intent, maps it to contract function signatures, and generates optimized query parameters without requiring developers to write low-level blockchain code. This reduces friction for Web3 developers unfamiliar with contract ABIs and RPC call semantics.
Unique: Uses contract ABI schema-aware LLM prompting with parameter validation against function signatures, ensuring generated queries are syntactically valid before execution — unlike generic LLM-to-SQL approaches that require post-hoc validation
vs alternatives: Faster developer onboarding than The Graph's GraphQL schema learning curve, and more flexible than hardcoded query templates since it adapts to arbitrary contract ABIs
real-time blockchain data indexing with caching layer
Maintains a distributed cache of frequently-accessed blockchain state (balances, allowances, contract storage) with automatic invalidation on new block finality. Uses event-driven architecture to subscribe to contract logs and update cached state incrementally rather than re-scanning the entire chain. Implements multi-level caching (in-memory, Redis, persistent) with configurable TTLs to balance freshness vs query latency.
Unique: Event-driven incremental indexing with multi-level cache hierarchy (in-memory → Redis → persistent) and automatic reorg detection, rather than full-chain rescans like traditional RPC-based approaches or static snapshot indexing like The Graph
vs alternatives: Significantly faster query response times than direct RPC calls (10-100x improvement), and more cost-effective than running dedicated indexing nodes while maintaining real-time freshness guarantees
blockchain data lineage and audit trail tracking
Maintains immutable audit logs of all blockchain data queries and modifications, tracking who accessed what data, when, and for what purpose. Links query results back to source transactions and blocks, enabling data lineage tracing. Integrates with compliance frameworks (SOX, HIPAA) to generate audit reports for regulatory purposes.
Unique: Immutable audit logs with data lineage tracing back to source transactions and compliance report generation, rather than basic query logging or manual audit trail maintenance
vs alternatives: Provides regulatory-grade audit trails that raw blockchain data access lacks, and automates compliance reporting that would otherwise require manual effort
zero-knowledge proof validation for sensitive blockchain data
Validates zero-knowledge proofs embedded in blockchain transactions to verify sensitive data (private balances, confidential transactions) without exposing the underlying plaintext. Implements proof verification circuits compatible with major ZK frameworks (Circom, Cairo, Noir) and validates proofs against on-chain commitment roots. Enables querying encrypted blockchain state while maintaining cryptographic privacy guarantees.
Unique: Integrates multiple ZK proof verification backends (Groth16, PLONK, custom circuits) with on-chain commitment validation, enabling privacy-preserving queries across heterogeneous ZK protocols rather than single-protocol support
vs alternatives: Enables privacy-preserving analytics on encrypted blockchain data that traditional indexers like The Graph cannot access, while maintaining cryptographic guarantees stronger than application-level encryption
automated smart contract data validation and schema enforcement
Applies declarative validation rules to blockchain data before returning query results, ensuring type correctness, value bounds, and business logic invariants. Uses a schema definition language to specify expected data types, ranges, and relationships across contract state. Validates decoded contract storage and function outputs against these schemas, catching data corruption or contract bugs before they propagate to applications.
Unique: Declarative schema-based validation with automatic type binding generation for multiple languages, combined with on-chain state verification — unlike generic JSON schema validators that lack blockchain-specific invariant checking
vs alternatives: Catches contract state anomalies that raw RPC queries would miss, and provides stronger guarantees than application-level validation by validating at the data ingestion layer
multi-chain query aggregation with unified api
Abstracts away chain-specific differences (RPC endpoints, block times, finality rules) and provides a unified query interface across Ethereum, Polygon, Arbitrum, Optimism, and other EVM chains. Handles chain-specific quirks (different block confirmation times, reorg depths) transparently and returns results with consistent schemas. Supports cross-chain state queries by coordinating requests across multiple chains and merging results.
Unique: Unified query abstraction with automatic chain-specific RPC routing and result schema normalization, handling finality and reorg semantics per-chain rather than exposing raw RPC differences to applications
vs alternatives: Eliminates boilerplate for multi-chain applications compared to managing separate RPC connections, and provides more consistent semantics than chain-specific indexers like The Graph (which requires separate subgraphs per chain)
query optimization and cost estimation for blockchain data access
Analyzes incoming queries and recommends optimizations (batching, caching, index selection) to minimize RPC calls and associated costs. Estimates gas costs and RPC provider fees before query execution and suggests alternative query patterns with lower costs. Uses historical query patterns and chain state analysis to predict optimal execution strategies.
Unique: Combines query analysis with RPC provider pricing models and historical execution patterns to generate cost-aware optimization recommendations, rather than generic query optimization that ignores blockchain-specific economics
vs alternatives: Provides cost visibility and optimization that raw RPC calls lack, and more accurate estimates than generic database query planners since it understands blockchain-specific cost drivers (block finality, reorg handling)
encrypted data storage and retrieval for blockchain metadata
Stores sensitive blockchain metadata (private keys, transaction signing data, user identifiers) in encrypted vaults with encryption-at-rest and encryption-in-transit. Uses envelope encryption with key derivation from user credentials, ensuring PublicAI cannot access plaintext data. Integrates with hardware security modules (HSMs) for key management in enterprise deployments.
Unique: Envelope encryption with user-controlled key derivation and optional HSM integration, ensuring PublicAI cannot access plaintext even with database compromise — unlike application-level encryption that requires key management by users
vs alternatives: Provides stronger security guarantees than unencrypted storage, and more operational simplicity than client-side encryption since encryption/decryption is handled transparently by PublicAI
+3 more capabilities