Advanced RAG Systems - Enhance AI with contextual knowledge
Our advanced Retrieval Augmented Generation (RAG) systems supercharge your AI applications with the ability to access, process, and leverage your organization's specific knowledge.
- Improved response accuracy
- 95%
- Reduction in hallucinations
- 76%
- Faster knowledge retrieval
- 5x
Beyond conventional RAG approaches
Our advanced RAG systems go beyond simple document retrieval to provide AI applications with deeper context, more relevant information, and sophisticated reasoning capabilities.
- Multi-Vector Retrieval. We implement sophisticated multi-vector retrieval systems that capture different aspects of your content for more accurate and nuanced search results.
- Hybrid Search. Our RAG systems combine semantic search, keyword matching, and other techniques to ensure comprehensive and relevant information retrieval.
- Context-Aware Chunking. We use advanced document chunking strategies that preserve context and coherence for improved retrieval performance.
- Knowledge Graph Integration. Our RAG systems leverage knowledge graphs to enrich retrieval with structural understanding and relationship awareness.
- Query Transformation. We implement query rewriting, expansion, and decomposition to improve retrieval performance for complex and ambiguous queries.
- Self-Reflection & Validation. Our systems incorporate self-verification mechanisms that validate responses against retrieved information for greater accuracy.
Our RAG implementation process
Building effective RAG systems requires careful planning, sophisticated engineering, and continuous refinement based on real-world usage and feedback.
- Knowledge Base Assessment. We analyze your existing data and knowledge sources to determine the optimal ingestion and processing approach.
- Vector Store Architecture. Our team designs and implements the ideal vector database infrastructure for your specific needs and scale requirements.
- Retrieval Strategy Design. We develop customized retrieval strategies that balance accuracy, speed, and cost for your specific use cases.
- Integration with LLMs. We integrate your RAG system with the most appropriate Large Language Models to achieve optimal performance for your applications.
- Evaluation & Benchmarking. We implement comprehensive evaluation frameworks to measure performance and identify opportunities for improvement.
- Continuous Optimization. Our team continuously monitors and optimizes your RAG system to improve performance as your data and requirements evolve.
Technologies we use
We leverage cutting-edge RAG technologies to build systems that are accurate, fast, scalable, and tailored to your specific needs.
- LlamaIndex
- LangChain
- Chroma
- Pinecone
- Weaviate
- Qdrant
- FAISS
- OpenAI Embeddings
- HuggingFace
- Vector Search
- Semantic Caching
- Hybrid Search
- BERT
- PGVector
- Knowledge Distillation
Tell us about your project
Our offices
- Singapore
68 Circular Road #02-01
049422, Singapore - Bali
Bwork Jl. Nelayan No.9C
Canggu, Kec. Kuta Utara
Kabupaten Badung, Bali 80361
Indonesia