A distributed, AI-native architecture designed for real-time semantic retrieval, multi-lingual reasoning, and academic-grade verification.
Built on a microservices mesh with event-driven communication, optimized for low-latency knowledge retrieval and high-throughput indexing.
Neo4j & TigerGraph clusters store 2.4M+ entities with multi-hop relationship mapping for contextual discovery.
Cypher / GremlinHigh-dimensional semantic search using custom fine-tuned transformers for cross-lingual concept matching.
Pinecone / Weaviate30+ global regions with auto-scaling Kubernetes clusters ensuring sub-50ms response times worldwide.
K8s / TerraformKafka-backed stream processing for real-time content updates, citation verification, and cache invalidation.
Kafka / RedpandaOur proprietary LLM stack validates claims, resolves contradictions, and generates structured knowledge graphs in real-time.
PDF, HTML, and academic corpus parsing with entity extraction and language detection.
Multi-hop reasoning against primary sources with confidence scoring and citation linking.
Vector embedding generation and graph node creation with relationship weighting.
Intent classification + hybrid search (BM25 + Vector) with result re-ranking.
Enterprise-grade SLAs, redundant failover systems, and transparent uptime monitoring.
Access our full knowledge graph, AI reasoning endpoints, and real-time update streams via REST or GraphQL.
Flexible endpoints with auto-generated OpenAPI specs and TypeScript clients.
SDK AvailableReal-time event streaming for content updates, citation additions, and model re-ratings.
SSE / KafkaFree tier with 10K requests/month. Full dataset access with rate limiting and usage analytics.
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