Shivad AI
shivad ai
AI product studio
We build applications with AI doing a specific job inside them.
Built to run in production. Built to be changed after we hand it over.
Work
How we work
Software that assumed a fixed world stops being useful long before it stops running.
So we build for the opposite condition.
Thinking
We study the operation before we scope the system. The brief is a starting position, not an instruction.
Behaving
Real data from the first week. A system that only works on a clean sample has not been tested, it has been staged.
Attitude
We say so when a model is the wrong tool, or when the smaller build is the better one.
Lifetime impact
The measure is what your team does with it after we leave. Not the launch.
What we build
Three things. Most engagements need more than one.
AI inside the daily work
Someone on your team makes the same judgement forty times a day, from scratch each time.
We build the step that produces the first answer, with the material it came from attached, and a named person who signs it off.
The judgement stays theirs. It starts from a draft instead of a blank screen.
Systems that don’t talk to each other
Two systems hold the same fact and disagree. Which one to trust lives in someone’s head.
We build the layer that reconciles them into one record, and write down what happens when they cannot be reconciled.
Everyone reads the same number.
Systems that hold under load
The pilot worked. Then it met a full day of real volume.
We build the layer underneath: storage that holds the record, ingestion that survives bad input, jobs that can be re-run, and the tooling to see what failed at 3am.
It runs without us.
Articles
Start with a conversation
Tell us what the system has to do and what is currently in the way. We will tell you how we would approach it, what it would take, and whether we are the right studio for it. [Duration] minutes, no deck.
If the answer is that you do not need a build, we will say that too.