“You shipped what the others promised.”
Most teams come to us after a stalled pilot. Our job is to ship the production system the previous engagement was supposed to deliver — and ship it in a fraction of the time.
About
A small studio with one job:
ship AI that actually works.
We started Entitybits because most "AI consulting" is decks and pilots that never reach production. We do the opposite — small senior teams, real systems, eval-driven, deployed.
Why we exist
Most AI projects die in the gap between “demo” and “deployed.”
That gap is where we live. It's not a model problem — it's an engineering problem. Eval sets that aren't real. Latency budgets nobody owns. Cost ceilings that get ignored until the bill arrives. Citations that don't actually link. Failure modes nobody pre-mortemed.
We're an IT studio with deep AI expertise — meaning we ship the full system, not just the prompts. Frontend, backend, data, eval, observability, runbook. The boring parts that turn AI features into real products.
If your last AI project was a pilot that didn't survive Q3, we already know why. And we've shipped enough of them to know how to do it differently.
What we believe
Four operating principles. We use them every week.
These aren't poster values. They're how we make trade-offs in real projects.
— 01
Eval-first, always
If we can't measure whether the system is getting better, we can't ship it. Every project starts with the eval set. No exceptions.
— 02
Production over pilots
A demo that doesn't survive real load is a marketing artifact, not a system. We optimize for “in production, serving users” from day one.
— 03
Small teams, senior people
4–6 people who've shipped AI in production. No 30-person waterfalls. No junior engineers learning on your project.
— 04
Honest scoping
If your problem doesn't need AI — or doesn't need us — we'll say so on the first call. We've turned down more projects than we've taken.
How we work
Three habits we don't break.
01
Weekly demos against your team — not slides.
Every week, we put the actual system in front of someone on your team and watch them use it. Not a Loom. Not a deck. The real thing. The bug list comes from real interactions, not our imagination.
02
The eval is owned by us. The eval set is owned by you.
We build the harness, plumbing, and grading. You own the truth set — the examples that define what “right” looks like for your domain. When we hand off, your team can run evals without us.
03
Cost ceiling on day one. Latency budget on day two.
Before we write the agent loop, we know the cost-per-request budget and the latency target. If a design choice blows them, we change the design — not the budget. Most “AI is too expensive” stories trace back to skipping this.
By the numbers
Six years. Twenty-three systems. Four time zones.
6yrs
Building production AI systems
23+
Systems shipped to production
14
Engineers on the team
12M
Monthly requests served
Where our clients are
Studio in Ahmedabad, India. Clients across four time zones — we staff engagements globally and meet you where the work happens.
San Francisco
United States
London
Europe
Dubai
UAE
Riyadh
KSA
Why teams pick us
What we hear most often, after we ship.
“You speak engineering, not vendor.”
We're engineers, not BD. Every conversation is with the people who will write the code, not account executives. CTOs and tech leads find this refreshing.
“You said no to the parts that didn't make sense.”
Half of "AI strategy" is recognizing what shouldn't be AI. We'll tell you which parts of your problem need a model, which need a function, and which need a rethink.
“The handoff was the cleanest we've ever had.”
You get the eval pipeline, the trace viewer, the runbook, and the on-call playbook. Your team can run, debug, and improve the system without us.
Quotes paraphrased and clients anonymized.
Have a real AI system to build?
30-minute scoping call. We'll tell you if it's worth doing — and if not, what to do instead.
Start the conversation →