Generative AI is where most enterprise interest sits — but the value isn’t the raw model, it’s what you ground it in. Here’s a practical guide for Indian enterprises. (dgm implements osFoundry, a separate company’s platform — dgm is an independent integration partner, not osFoundry. General information, not professional advice.)

Grounding beats the raw model

A chat model on its own is generic. Enterprise value comes from grounding it in your data — retrieval-augmented generation — so it answers from your real documents and systems, with governance around it. Start with a high-value use case (drafting, support, knowledge search) and measure.

Model-neutral and BYOK

Model-neutral means the platform can use different models, not one vendor; bring-your-own-key means you use your own API keys. Together they let you route per task — including Indian and open models — controlling cost and data, and avoiding lock-in.

Governance is essential

  • Data control — sensitive data in your environment, ideally self-hostable.
  • DPDP — personal-data handling.
  • Output review — generative AI produces confident wrong answers; human review matters in regulated contexts.
  • Access controls — the AI uses only data users may see.

The India edge: language

Indian-language capability is a real advantage — multilingual generative AI lets enterprises serve staff and customers across languages.

How dgm helps

dgm implements generative AI on osFoundry — model-neutral and self-hostable, grounded in your data, with India data control aligned to DPDP — for a $399 assessment and $3,999/month (INR approximate; 18% GST domestic). We route between models per task and keep humans in the loop.

General information, not professional advice.