Make AI Know Your Business
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 · pgvector · LangChain · LlamaIndex · Starting at $1,500
How a RAG Pipeline Works
Document Ingestion
We ingest your PDFs, Google Docs, Notion pages, Confluence articles, Slack threads, and CSVs — any format, any source.
Chunking & Embedding
Documents are split into semantic chunks, converted to vector embeddings using OpenAI or Cohere, and stored in a vector database.
Retrieval & Generation
When a user asks a question, the system retrieves the most relevant chunks and passes them to the LLM as context for a precise, cited answer.
RAG Use Cases We Build
- Internal AI assistant trained on company knowledge
- Customer-facing AI chatbot with accurate product answers
- AI support agent that knows your policies and FAQs
- AI sales rep trained on your pricing and case studies
- Due diligence AI that reads and summarises contracts
- Compliance monitoring AI trained on regulatory docs
Our RAG Tech Stack
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
Request your free AI audit
Reach us
Location
Remote team serving US, UK, Europe & Australia
Reply Time
Within 24 hours
Global Coverage
Remote-first agency serving US (EST/PST), UK (GMT), and AUS (AEDT) timezones. We adapt to your schedule.