A model with no product is a demo with a login. We build the surface around it: streaming interfaces that make waiting legible, the interruption and error states that decide whether people trust it, and native desktop builds that keep sensitive data and models on the device. The work around the AI, shipped by the team that shipped the AI.
01 / PRODUCT ENGINEERING
For teams who have the model but not the product. The interface around it: streaming, interruption and error states, and desktop builds that keep data local.
Usually shipped with
Not a bundle to buy. Whichever you start from, the engagement covers what the build actually needs.
02 / Scope
03 / Outcomes
04 / Deliverables
05 / Stack
06 / Why us
On AnyTeam we built on-device live-meeting detection, roughly second in the world to ship it, inside a signed, notarized desktop app with an embedded local model. No audio ever leaves the laptop.
When sensitive data cannot go to the cloud, we ship native desktop apps with on-device inference and an encrypted local vault, as we did for AnyTeam and Solarpunk.
The same engineers who build the model build the product around it, so nothing is lost in a handoff between an AI team and a separate frontend shop.
Week 1–2
We shape the interface your customers actually touch, the chat, the copilot, the streaming UI, alongside the AI, so it feels like one product instead of a model with a form bolted on.
Week 2
Web, mobile, or native desktop, decided by where your users are and where the data has to live. Sensitive data stays on the device when it has to.
Week 2–5
Streaming UIs and realtime data so the AI feels immediate instead of laggy, with the API layer that ties product and model together.
Week 5–8
Signed, notarized desktop builds, embedded local models, and the polish that separates a demo from a product people use every day.
SalesIn production
A real-time meeting-intelligence stack for account executives. It notices the call has started, transcribes it on the rep's own machine, guides them while they are still talking, and hands back a structured CRM-ready summary the moment the call ends.
Executive operationsIn production
A 24/7 AI chief-of-staff for founders and leadership teams. The leader states the outcome they want; the agent works the sequence across every system the routine touches, checks its own output, and comes back with finished work or the one thing it could not resolve.
ESG & sustainabilityIn production
An ESG-intelligence pipeline that ingests dense, inconsistent filings at scale, extracts framework-aligned metrics with per-field confidence and source lineage, connects them across reports and years, and serves them through a governed analytics layer where a low-confidence number goes to review rather than into a dashboard.
Production-proven
Built by engineers who've already shipped this in production.
Yes, that is the point. The same team ships the model and the web, mobile, or desktop product around it, so nothing falls through the gap between an AI team and a separate frontend shop.
Yes. We ship native desktop apps with on-device inference and a local vault, so models run and data stays on the device. We did exactly this for a notarized desktop product with an embedded local model.
Not if it is built right. We use streaming UIs and realtime data so responses feel instant, the same approach behind a live-meeting copilot that processes everything on-device in real time.
Yes, and we would rather do both. The interface decisions in an AI product — what shows while it thinks, what happens when it is wrong — are engineering decisions as much as visual ones, and splitting them across two vendors is where these products usually go wrong.
Only when the constraint demands it: local model inference, access to apps with no API, or data that must not leave the device. AnyTeam is desktop because the audio never leaves the laptop. Otherwise web is the right default.
Yes, from the first commit — it is your repository and we work in it. There is no handover event at the end because there was never a wall in the middle.
Multi-step agents for workflows where a wrong action is expensive to undo.
View serviceSub-second voice agents for teams whose customers are waiting on hold.
View serviceDocument extraction and search for teams who have to show their source.
View serviceTell us where you are and what you're trying to ship. We'll come back with a concrete plan, the right engineers, and a path to production, not a generic pitch.