NerqonPro—The AI Search Engine

NerqonPro is an enterprise AI search platform tool that eliminates hallucinations in RAG (Retrieval-Augmented Generation) applications through a hybrid tri-source search architecture and built-in confidence scoring, built for production development teams. Rather than guessing when results are uncertain, NerqonPro uses a Confidence Engine with Platt-scaled calibration to detect low-confidence answers and trigger deterministic fallbacks — returning an honest "I don't know" instead of a fabricated response.

The platform combines three parallel search methods — FAISS vector search, BM25 keyword matching, and a semantic Knowledge Graph — with adaptive query fusion that the homepage claims delivers 3x better recall than single-method approaches. The Knowledge Graph encodes typed relationships such as prerequisite, supersedes, and contradicts, enabling multi-hop reasoning across connected documents.

NerqonPro is engineered for production reliability: search latency is under 5ms, uptime is backed by a 99.9% SLA, and the system includes performance guardrails such as rate limiting, circuit breakers, and graceful degradation. It supports GPU acceleration and product quantization for billion-vector search workloads. Embedding flexibility covers 384, 768, and 1536+ dimensions with any embedding model.

Governance and compliance features are also built in — document versioning works like git branching with rollback and full audit trails, and multi-tenancy is enforced through namespace isolation with SSO, SAML, LDAP, and OIDC support. The platform is SOC 2 Type II certified and uses AES-256 encryption. Developers integrate through streaming APIs (SSE), an MCP server, LangChain and LlamaIndex connectors, and Kubernetes Helm charts. A 30-day free trial requires no credit card.

Enterprise development teams building production RAG applications who need hallucination elimination through hybrid tri-source search and confidence-scored deterministic fallbacks.