AI / ML engineering
Practical AI, measured
before it is trusted.
We build AI features the way we build our own products: start from the task, design the evaluation, then choose the model. That is how LLMSlim's context planner and Krishyak's crop-photo classifier were built, and it is how we approach yours.
Deliverables
What you receive
Exact deliverables are listed in your quotation. A typical engagement includes:
- Use-case and feasibility assessment with a clear go/no-go
- Evaluation set and quality gates defined before building
- LLM features: extraction, summarisation, assistants and tool use
- Retrieval-augmented generation over your documents
- Custom model training and a model card where a model is needed
- Cost, latency and context-budget planning
- Monitoring hooks and a written handover
What good looks like.
An honest baseline
Every AI feature is compared against a simple baseline, so you know what the model actually adds.
Bounded cost
Token budgets and context planning keep inference bills predictable.
Safe failure
Systems abstain or escalate when confidence is low, as Krishyak's classifier does below 0.75.
Typical projects
Where this service fits
- Document Q&A and internal knowledge assistants
- Classification and extraction pipelines
- Image classification for a defined domain
- LLM features inside an existing product
- Evaluation harnesses for AI output
A good fit for
- Startups adding AI to a product
- Businesses with document-heavy processes
- Institutions exploring decision-support tools
Not a fit for
- Fully autonomous systems without human review in high-stakes settings
- Projects that require unverifiable accuracy claims
Representative technologies
- Python
- FastAPI
- OpenAI, Anthropic, Gemini, Sarvam APIs
- Self-hosted models via vLLM
- TensorFlow / LiteRT
- PostgreSQL + pgvector
- MongoDB Atlas
- LLMSlim Core
Chosen per project. Free and open-source options are preferred where they fit.
Engagement models
- Feasibility sprint
- One to two weeks to test whether the task is solvable with your data, with a written result.
- Build
- A scoped first release with evaluation, deployed to your infrastructure or ours.
Pricing reference · Build · Custom software and AI solutions: From ₹99,999 (Prices exclude GST. GST at 18% is added on the quotation and invoice where applicable.)
Questions
Asked before every project
The collaboration process is the same for every service: brief, written scope and quotation, advance, milestones, handover. See how payments work.
You do, on your own provider account. We design for predictable usage and can set budgets and alerts.
No responsible engineer can. We define the evaluation together, report results on held-out data and explain the limits.
Yes. Krishyak ships language packs for 22 scheduled Indian languages plus English and uses Sarvam speech services.
Have something difficult to build?
Tell us what you are trying to do. You will get a considered reply from the founder, usually within two working days, with next steps and an honest view of fit.
Or book a free 30-minute call (opens in a new tab) with the founder.
Prefer email? hello@ameyor.in