Enterprise RAG Platform for Business
Retrieval-augmented generation (RAG) connects your enterprise knowledge with large language models — delivering accurate, source-cited answers without fine-tuning or hallucinations.
What is retrieval-augmented generation?
RAG is an AI architecture that retrieves relevant information from your own data before generating a response. Instead of relying solely on what a language model was trained on, RAG grounds every answer in your actual documents — making responses accurate, up-to-date, and traceable back to the source.
For enterprises, this means you can use generative AI without exposing sensitive data for model training, without expensive fine-tuning, and without worrying about hallucinated answers. Your knowledge stays private, and every answer comes with citations.
How Buildgrid Implements RAG
Our platform handles the full RAG pipeline — from data ingestion to answer generation — so you can focus on results, not infrastructure.
Vector Database & Embeddings
Your documents are converted into embeddings and stored in a high-performance vector database. This enables semantic search that understands meaning, not just keywords.
Semantic Search & Retrieval
When a user asks a question, Buildgrid searches your entire knowledge base semantically — finding the most relevant passages across all your data sources in milliseconds.
AI Answer Generation
Retrieved context is fed to the language model along with the question. The model generates a natural-language answer grounded in your data, with source citations for verification.
RAG vs Fine-Tuning
Two approaches to making AI work with your data — here's why RAG wins for most enterprise use cases.
RAG (Buildgrid)
- No model training required — deploy in minutes
- Data stays private — never used for training
- Always up-to-date as documents change
- Source citations for every answer
- Works with any LLM (OpenAI, Claude, Gemini, Llama)
- Transparent, predictable pricing
Fine-Tuning
- Requires expensive model training cycles
- Training data may be retained by providers
- Must retrain when data changes
- No built-in source attribution
- Locked to a specific model version
- Costs scale unpredictably with data volume
Deploy Anywhere Your Team Works
Buildgrid's RAG platform integrates with the tools your team already uses — no workflow changes needed.
Web Chat
Embed on your website or use a private URL for internal teams
Slack
Ask questions and get AI answers directly in Slack channels
Microsoft Teams
Integrate with Teams for seamless enterprise workflows
Reach users on mobile with WhatsApp-based AI assistants
See RAG in action with your own data
Start building your enterprise RAG platform today — upload documents and get AI-powered answers in minutes.