AI features that survive contact with real users.
We add AI where it changes a workflow — retrieval, classification, assistants, document intelligence — with evaluation, guardrails and a path to production.
- Team
- 50+ IT professionals
- Delivery
- Design, build, release, support
- Engagement
- Project or dedicated team
What this covers
Concrete work we take on under ai & ml — not a catalogue of buzzwords.
- LLM-powered assistants and copilots inside your product
- Document extraction and classification pipelines
- RAG over your private knowledge base
- Model evaluation, prompt versioning and cost control
Problems we take on
If one of these sounds familiar, we have likely shipped something close — and we will say so if we have not.
- A demo works in a notebook but fails on real customer data.
- You need AI inside an existing product, not a separate experiment.
- Compliance and auditability matter as much as accuracy.
Technologies
Stacks we use when they fit the product and your team — not a mandatory toolkit for every engagement.
- Python
- OpenAI / Gemini APIs
- LangChain
- Vector DBs
- FastAPI
- AWS/GCP ML
How we work
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Scope before code
We write what is being built, what is excluded, integrations, dates and cost basis before the build starts. Changes get quoted before they get coded.
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Talk to the people doing the work
You meet named engineers and designers. There is no account manager translating technical questions in both directions.
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Working software every two weeks
Increments land on staging you can open and use. Progress you can click on beats progress in a status report.
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You own everything
Repository, cloud account, domains and credentials stay yours. We work in your accounts wherever possible.
FAQ
Do you train custom models?
When the data and problem justify it. Many products ship faster and safer on well-tuned foundation models plus retrieval.
How do you handle hallucinations?
Grounding, evaluation sets, human review loops where stakes are high, and clear UI that shows uncertainty.
Can you add AI to an existing product?
Yes — assistants, document intelligence and retrieval features inside your current stack, not a separate experiment that never ships.
How do you control cost and quality?
Prompt and model versioning, evaluation sets, usage limits and monitoring so accuracy and spend stay visible after launch.
What about private or sensitive data?
We design for your data residency and access rules — private retrieval, audit trails and human review where the stakes require it.
Related
Services that often sit beside ai & ml on the same roadmap.
Why Three Index
Founded in 2020 in Ahmedabad, Gujarat. Fifty-plus IT professionals. More than five hundred projects shipped across product and enterprise work.
We are large enough to staff serious products and small enough that the people who wrote a module can still explain it. See how we operate, browse case studies, or join the team.
Tell us what you are trying to build.
Send a short description of the project. You will get a reply from someone technical — with questions worth answering, not a brochure.