Searcly is a neural search platform that understands intent, context, and semantics. Power enterprise search, e-commerce discovery, and RAG pipelines with GPU-accelerated vector retrieval and neural ranking.
From enterprise knowledge bases to e-commerce product discovery — Searcly understands what your users mean, not just what they type.
Transform text into dense vector embeddings using state-of-the-art transformer models. GPU-accelerated ANN retrieval over billions of vectors in under 3ms. HNSW and IVF-PQ indexing.
Cross-encoder models re-score results by reading full query-document pairs. Boost precision by 40%+ over first-stage retrieval. TensorRT-optimized for sub-10ms reranking of 1000 candidates.
Users search the way they think — "show me red dresses under $50" or "documents about thermal management in batteries." LLM-powered query understanding extracts intent, filters, and entities.
Combine BM25 keyword matching with neural vector retrieval in a single query. Best of both worlds — exact matches for SKUs and IDs, semantic understanding for natural language. Tunable fusion weights.
Search with images, text, or both. CLIP-based embeddings for visual product search. Upload a photo, find similar products across your entire catalog. Cross-modal retrieval in real-time.
Built-in search analytics: zero-result rate, click-through rate, mean reciprocal rank. A/B test ranking models and embedding strategies without reindexing. Search quality dashboards out of the box.
From query to ranked results in milliseconds — a three-stage retrieval pipeline optimized with NVIDIA GPUs.
GPU-accelerated approximate nearest neighbor search over billion-scale vector index. HNSW + IVF-PQ hybrid index. Returns top-1000 candidates in <2ms. NVIDIA cuVS library.
Cross-encoder transformer re-scores each candidate against the query. TensorRT-optimized inference, FP16 quantization. Re-ranks 1000 candidates in <8ms. Trained on click data + NLI datasets.
Optional: generate natural language answers from top results. RAG pipeline with citation support. LLM runs on NVIDIA Triton Inference Server. Sub-200ms answer generation.
From e-commerce to enterprise knowledge — Searcly handles any search workload.
Natural language product search across 5M+ SKUs. "comfortable running shoes for flat feet" returns 30 relevant products. 42% increase in conversion rate, 67% reduction in zero-result searches.
Unified search across documents, wikis, Slack, Jira, and emails. Employees find answers in seconds, not minutes. 83% reduction in "where is..." Slack messages. Integrates with SSO.
Retrieval layer for Retrieval-Augmented Generation. Fetch relevant context from your knowledge base, feed to LLM, get grounded answers with citations. Powers 200+ enterprise chatbots.
Search past support tickets, resolution docs, and runbooks. Suggest relevant solutions to new tickets automatically. 38% auto-resolution rate. MTTR reduced by 2.4 hours on average.
Join teams using Searcly to power semantic search, product discovery, and RAG pipelines with GPU-accelerated neural retrieval.