GenAI development that knows your business, not just the internet.

RAG, or retrieval-augmented generation, means the AI first searches your own documents for the relevant passages, then writes its answer from them and shows where each point came from. It keeps answers current without retraining a model, and when the answer is not in your documents, the assistant says so.

By grounding every answer in your verified data, requiring citations, limiting the scope, testing against sets of known answers and routing uncertainty to a person. Accuracy is measured before launch and monitored after it, never assumed. If the answer is not in your data, the assistant says so.

Yes, with the right set-up. The main providers' business plans keep your data out of model training by default, but free personal accounts can work differently. We set up business accounts, check the data settings, control who sees what, and write a short policy on what must never be pasted in.

Where you decide. We can host in Indian cloud regions, such as AWS Mumbai or Azure Pune, choose AI providers with no-training terms and keep sensitive data out of prompts altogether. Some AI services process data outside India, so we tell you which ones and name every provider in the Data Processing Addendum before work starts.

A grounded assistant built on existing documentation usually reaches a working pilot in 4 to 6 weeks. A custom GPT or a staff roll-out is often quicker. Testing, hardening and roll-out follow, with the full timeline set out in your fixed quote, and you see it working every week.

With a fixed, itemised quote in rupees after a short discovery, with any GST shown separately, paid in milestones. It covers the pilot, testing and roll-out. Running costs such as AI model usage, licences and hosting are estimated up front and shown separately, so there are no surprises on the monthly bill.