AI CORE
LIVE
v4.8
- TS-1904, 18th Floor, Galaxy Sapphire Plaza, Greater Noida-201306
- +91-9650627408
Architect enterprise vector database clusters and knowledge graphs designed for billion-scale high-dimensional semantic search and real-time AI memory.
Book a direct engineering audit & feasibility estimate with our principal architects.
Architected for high-concurrency enterprise workloads with strict security SLAs.
Configure HNSW, IVF-PQ, and ScaNN indexing strategies for sub-15ms nearest-neighbor retrieval.
Unify vector representations with Neo4j and Memgraph for structural relation reasoning.
Execute complex SQL-like Boolean filters simultaneously with cosine and dot-product vector search.
Build multi-region replicated vector clusters with automated backups and disaster failover.
Every phase is backed by automated test suites, transparent sprint metrics, and executive milestone sign-offs.
Select optimal embedding dimensions, similarity metrics, and compression techniques.
Deploy Kubernetes-managed vector databases with dedicated memory instances.
Stream continuous database changes (CDC) into real-time vector indexes via Kafka.
Optimize HNSW M/efConstruction parameters to maximize recall vs. query latency.
We build on hardened, industry-standard frameworks to ensure zero vendor lock-in and effortless long-term maintainability.
Schedule a confidential technical scoping session with our principal engineers. Receive a detailed architecture blueprint, timeline, and cost estimate within 48 hours.