A distributed, AI-native architecture designed for petabyte-scale semantic search, real-time verification, and sub-50ms global retrieval across 2.4 million interconnected entries.
Our technology stack combines cutting-edge AI models with battle-tested infrastructure to deliver unmatched reliability and speed.
Custom transformer architecture fine-tuned on academic corpora. Supports dense + sparse hybrid retrieval with contextual re-ranking and zero-shot query expansion.
Entity-resolution pipeline ingesting 12M+ nodes daily. Supports transitive reasoning, temporal versioning, and cross-lingual entity alignment.
Multi-agent fact-checking system cross-referencing primary sources, peer-reviewed journals, and authoritative datasets with confidence scoring.
Global CDN with predictive prefetching. GraphQL federation layer ensures consistent schema across 47 regional nodes with automatic failover.
From raw ingestion to instant retrieval, every millisecond is optimized for accuracy and latency.
Multi-source data pipelines (APIs, web crawlers, academic feeds) pass through schema validation, language detection, and deduplication layers.
Embedding generation, entity extraction, citation parsing, and semantic clustering run on distributed GPU clusters with checkpointing.
Hybrid storage architecture: dense vectors in Faiss, relational metadata in PostgreSQL, and semantic links in Neo4j, synced via CDC.
Unified GraphQL gateway handles routing, caching, rate limiting, and personalization. Results are streamed via WebSocket for live updates.
Our REST & GraphQL APIs give you full programmatic access to the knowledge graph, search endpoints, and verification pipelines. SDKs available for Python, JavaScript, Go, and Rust.
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