For products shipping AI
AI Integration
LLM features, agents, and automation built into real products, with the evaluations and guardrails that make them safe to ship.
Every product has an AI feature on the roadmap now, and most of them are demos: impressive in a screen recording, unreliable the moment a real user asks something the happy path didn’t cover. The gap isn’t the model. It’s the engineering around it: grounding answers in your actual data, handling the cases where the model is wrong, and knowing (with numbers, not vibes) whether the thing is good enough to ship.
We build with these tools every day, and we’ve shipped two AI-built products of our own: Claude Design Skills and Insanity Logs. That’s the difference we bring. Not hype about what AI might do, but the sceptical, measured engineering that turns a promising demo into a feature you can put in front of paying users.
What we build
Chat & answer features
Retrieval grounded in your own data, so answers cite what’s true for you, not what the model half-remembers.
Internal automation
The manual, repetitive work (triage, extraction, drafting) handed to a model and wired into the tools you already use.
Agent workflows
Multi-step agents that call your tools and APIs to finish a job, scoped tightly so they stay predictable.
Evaluations & guardrails
Test sets, scoring, and safety rails, so “is it good enough?” has an answer you can actually see.
Model choice & cost control
The right model for each job, not the biggest one: quality and latency and cost weighed honestly, and revisited as prices move.
Built into real products
Shipped into your codebase and your stack, not stranded in a notebook or a proof of concept.
How it works
- 01
Scope
We pin down the job the AI is actually doing, what “right” looks like, and how we’ll know when it gets there, in writing.
- 02
Prototype
A working version against your real data, early, so we’re arguing about behaviour we can see rather than slides.
- 03
Evaluate
We build the test set and the guardrails, and tune until the numbers say it’s ready, not just the demo.
- 04
Ship
It lands in production instrumented and monitored, so you can watch it behave and catch drift before users do.
Related work
Neelesh has broad experience across games, infrastructure, security, & front end. His ability to apply these skills with insight and creativity make him the perfect WT collaborator - he's resolved to solve whatever we throw at him. Highly recommended.
Dev J
CEO - Whatever Together
Common questions
A lot of it is, which is exactly why we lead with evaluations. We won’t ship a feature we can’t measure, and we’ll tell you plainly when a problem doesn’t need AI at all. The goal is something that works and keeps working, not a launch tweet.
Have something to build?
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