01
Document Ingestion
We ingest your PDFs, Google Docs, Notion pages, Confluence articles, Slack threads, and CSVs — any format, any source.
RAG Pipeline Services
Build AI That Knows Your Business Inside Out
Generic AI gives generic answers. We build custom RAG pipelines that make AI fluent in your company's knowledge — your docs, your processes, your products. Accurate. Sourced. Yours.
Pinecone · Weaviate · Qdrant · LangChain · LlamaIndex · Starting at $1,500
01Process
How We Build Your RAG Pipeline
02
Chunking & Embedding
Documents are split into semantic chunks, converted to vector embeddings using OpenAI or Cohere, and stored in a vector database.
03
Retrieval & Reranking
When a query arrives, the system retrieves the most relevant chunks using hybrid search, then reranks with Cohere Rerank for maximum accuracy.
04
Generation with Citations
The LLM uses retrieved chunks as context to generate a precise, cited answer. Every response links back to the source document.
02Use Cases
RAG Use Cases We Build
- 01Internal AI assistant trained on company knowledge
- 02Customer-facing AI chatbot with accurate product answers
- 03AI support agent that knows your policies and FAQs
- 04AI sales rep trained on your pricing and case studies
- 05Due diligence AI that reads and summarises contracts
- 06Compliance monitoring AI trained on regulatory documents
03Tooling
Our RAG Tech Stack
LangChainLlamaIndexOpenAI EmbeddingsPineconeWeaviateQdrantpgvectorAnthropic ClaudeGPT-4oCohere Rerank
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Build Your Custom RAG Pipeline
Tell us your document sources and use case. We'll design the RAG architecture and show you a working prototype — free.
Free consultation • No obligation • Reply within 24 hours
Location
Remote team serving US, UK, Europe & Australia
Reply Time
Within 24 hours
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