Denser.ai
Open-source hybrid RAG with state-of-the-art retrieval architecture
Denser.ai is a developer-focused RAG platform built by former Amazon Kendra principal scientist Zhiheng Huang, combining open-source retrieval technology with no-code deployment. Its hybrid architecture fuses Elasticsearch, Milvus vector search, and XGBoost ML reranking to achieve 75.33 NDCG@10 (vs 73.16 for pure vector search) and 96.50% Recall@20 on benchmarks. Trade-offs: no SOC2/HIPAA certifications, limited native integrations, ~4-person team size impacts enterprise support.
Overall Rating
reviews
Company Information
Founded
2023
Headquarters
Silicon Valley, CA
Company Size
1-10 employees
Pros
- State-of-the-art hybrid retrieval (75.33 NDCG@10) outperforms pure vector search with published benchmarks
- Open-source MIT-licensed core (denser-retriever) enables transparency, validation, and self-hosting
- SQL database chat capability unique differentiator for business intelligence use cases
- Strong multilingual support (80+ languages) with automatic detection
- Founded by ex-Amazon Kendra principal scientist with deep neural IR expertise (14K+ citations)
Cons
- No compliance certifications (SOC 2, HIPAA, ISO 27001) - major enterprise procurement barrier
- Limited native integrations - no Teams, Discord, direct WhatsApp; relies heavily on Zapier
- Small team (~4 employees) impacts enterprise support capacity and SLA guarantees
- Query limits restrictive for high-volume use (user reviews: 'credit limits reached quite sooner')
- Documentation fragmented across multiple sites (docs.denser.ai, retriever.denser.ai, GitHub)
Key Highlights
Best Use Cases
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