MindT
AI solutions

AI that speaks your customers' language — and knows your business

We build AI that answers from your own data, in Telugu, Hindi, Tamil and other Indian languages. Not a generic chatbot — an assistant grounded in your catalogue, your policies and your records, with the questions it can't answer handed to a human.

For: Businesses drowning in repeat questions, teams doing manual data entry, anyone sitting on documents nobody can search

The problem we usually walk into

Most 'AI' offered to Indian businesses is a keyword chatbot with a new label, or a raw ChatGPT wrapper that confidently invents your prices. Both damage trust with the customer who was ready to buy.

See what this costs \u2192
Fixed scope and fixed price, quoted in writingYou own the code and the dataSupport and training in all major Indian languages

What's included

  • Assistants grounded in your data

    Answers come from your catalogue, price list, policies and records — with a clear hand-off to a human when it doesn't know.

  • Voice and text in Indian languages

    A farmer or shopkeeper speaks in Telugu; the assistant understands and replies in Telugu.

  • WhatsApp, web or in-app

    Deployed where your customers already are, not on a page they have to find.

  • Document AI

    OCR and extraction from scanned files — proven on 70,000 PDFs and 10 lakh+ records.

  • Data extraction & entry automation

    Invoices, forms, bills and registers into your database without typing.

  • Your data stays yours

    Processed on our infrastructure in India. Nothing is used to train public models.

How we work

In this order, because each step depends on the one before it.

  1. Step 1

    Find the expensive question

    We look for the task actually costing you hours — usually repeat enquiries or data entry, not the flashy idea.

  2. Step 2

    Prove it on your data

    A working prototype on a sample of your real content, with measured accuracy. Free.

  3. Step 3

    Build with guardrails

    Grounding, refusal behaviour and human hand-off defined before launch, so it never invents an answer.

  4. Step 4

    Measure and improve

    We review real conversations monthly and tighten what's weak.

Questions we get asked

Will it make up answers?
That's the main thing we engineer against. The assistant answers only from your approved content, and says 'let me connect you to our team' when it doesn't know. We show you the refusal behaviour during the prototype.
Which AI models do you use?
Whatever fits the job and the budget — commercial models via API, or open models on our own servers when data must stay in-house. We'll explain the trade-off in plain language.
Is my data used to train anyone's model?
No. Processing runs on our infrastructure in India, and we don't send your documents to third-party AI services without your written agreement.
Can it work offline or on weak signal?
The assistant needs a connection, but we design for slow 4G, and field apps we build queue data offline and sync when signal returns.

Where we work

We are based in Andhra Pradesh and work across India, on site where it helps and remotely where it doesn't. Nearest to you: