AI development
AI features that work on your data.
You get search, chat, summarization, or automation inside your product. Answers come from data you approve, and we test quality on that data before launch. Two live products we built, Khoj and Recap, show how it works.
WHAT WE BUILD
Five AI features we can build for you.
Search and retrieval over your content
Users ask in their own words and get answers drawn from your documents, listings, or records, with the source shown next to each answer.
Conversational interfaces
Chat that sits inside your product and can look things up or take actions for your users. It answers from your approved data.
Summarization
Long material such as calls, tickets, code changes, and reports, turned into short text a person can check against the original.
Document extraction
Structured fields pulled from PDFs, forms, and emails into your database, with low-confidence results sent to a person for review.
Agents for internal workflows
Multi-step tasks your team repeats every day, run by a model that uses your tools, with approval steps where a mistake would be costly.
AI DISCOVERY SPRINT
Test one AI feature before you commit.
One to two weeks to prototype and assess one AI feature on your own data. If AI is not the right answer, we say so. You get a written quote after a first call.
Book a 30-minute call- A scoped use caseOne feature, one user task, and a written definition of a good result.
- A data checkWhether your content is complete and clean enough for the feature.
- A working prototypeRunning on your data, so you can try it yourself.
- A build estimateScope, timeline, and expected running cost for the full version.
HOW WE APPROACH IT
How we make AI reliable in your product.
Start from the user task
We agree on what the user is trying to get done and what a good answer looks like before we choose a model. We also agree on what the AI should not do.
Evaluate on your data
We build a test set from your real content and questions, and rerun it every time a prompt or model changes.
Track cost and latency
We measure what each request costs and how long it takes from the first prototype, so you know the running cost before launch.
Keep a fallback
When the model is wrong, slow, or unavailable, the feature falls back to a plain result or a person instead of failing.
PROOF YOU CAN TRY
Two live AI products you can try.
We built and run both. Try them before you talk to us and judge the quality yourself.
- khoj.me
Khoj
Conversational property search for UK home hunters.
THE PROBLEMProperty sites make you search with filters, but what people want from a home rarely fits a set of checkboxes.
Try it: khoj.me →WHAT THE AI DOESYou describe what you want in plain English. Khoj matches listings to that description and answers follow-up questions about them.
- recap.nilede.tech
Recap
An AI changelog writer for GitHub.
THE PROBLEMChangelogs get written late or not at all, and commit messages are not written for the people who use the product.
Try it: recap.nilede.tech →WHAT THE AI DOESWhen a pull request merges, Recap reads the diff and publishes a readable changelog entry.
YOUR DATA
Clear answers about your data, in writing.
You get these answers before we touch your content.
Where is data stored?
In your own cloud account wherever possible. We tell you in writing where your data is hosted before work starts.
Which model providers do you use?
We name every model provider in the written scope, and nothing is sent to a provider you have not approved.
What do you sign?
An NDA before any detailed discussion. A data processing agreement is available on request. The code belongs to you. It lives in your GitHub and cloud accounts from day one.
Have an AI feature in mind?
Tell us what you want it to do. You'll talk directly with Swapnil, our founder. We reply within one business day.