AI Product Studio

BANTER AI STUDIO

Defensible AI products, built by ex-founders.

We're all ex-founders between our own ideas. We grind 24/7 and do every part of building — not just the code.

And we'll give you the no-BS version most dev shops won't: a v1 is easy now — anyone can demo one. Reliable, defensible AI is the hard part, and that's the whole job. We've done it. We're VC-backed founders who've taken startups 0 to 1 and sold them, with real press along the way — not a dev shop of random IT guys.

For founders and teams who want to build something genuinely cool with AI, or automate the mundane. We've done both.

Ex-Uber ML · Berkeley · MIT · IIT · Google · viral-app founders
Selected work

CarynAI

The #1 AI companion in the world. Super viral.
Press ↗

Banter AI

The first AI phone-call product. 1M users.
Press ↗

AI healthcare startup

Built their MVP. They raised a $10M seed from Bain Capital.
Seed · $10M

NightingaleMD

One of 12 companies invited to the White House for our AI care-management product.
White House

A private-equity firm

AI diligence tool that saved them $32M a year.
Saved $32M/yr

Your product

Now booking
As seen in
See it work
DemoCare-management agent
DemoReimbursement agent
DemoCarynAI — companion
How we work
01We observe your workflows for a week.
02We map the inhuman parts — the work that should be automated.
03We tie it to the business bottom line: what this is actually worth.
04We build a working version in 3 days. Free.
05If it's good, we ship reliable AI that actually works.

Custom RAG, proprietary voice AI, and fine-tuned models — optimized for cost and speed. The kind of thing random engineers can't pull off, but founders who've built and sold real startups can. Engineered for fundraising milestones, defensibility, and reliability.

Engineering notes

Sub-250ms, or it isn't a conversation

Why voice-AI latency is the whole game.
Voice AI ↗

Teaching an AI to beat a payer phone tree

IVRs are hostile. We treat them as a control problem.
Voice agents ↗

The double-dose problem

Making clinical AI ask the right question, not just answer one.
Clinical AI ↗

RAG that doesn't fall over in production

Grounding, evals, and cost without cutting quality.
RAG ↗

The listener constellation: one voice, a dozen AIs

A swarm of specialized listeners with priority-queue interrupts.
Voice AI ↗

The nurse is the law

Clinician-supervised AI as architecture, not a checkbox.
Supervision ↗

The data layer: what you own when you own the calls

Own the operator, own every interaction. That's the moat.
Data ↗

The work happens while you're still talking

Background agents that book, refill, notify, and document — silently.
Agents ↗

Documenting into any EHR without an integration project

A browser agent that uses the EHR like a nurse does. Days, not quarters.
RPA ↗
Let's talk

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