AI features that fit your app
You don't need to reinvent your product to add AI. The useful additions are usually specific: summarize what's on the screen, draft the message the user is about to write, extract fields from an upload, or let users find things by describing them.
We work inside your existing stack — web or mobile — and add these as real features that respect your app's data model, auth, and design.
- In-app assistant scoped to what the current user can see and do
- Summarize, draft, rewrite, or translate content in context
- Smart search over the user's own data in the app
- Extract structured data from uploads or messages
- Works with your current backend, auth, and design system
Built right for mobile and web
AI calls belong on your server, not baked into the app binary where keys can be extracted. We route requests through your backend, stream responses so the UI stays responsive, and handle offline and error states so the feature degrades gracefully.
For mobile especially, we watch latency, battery, and data use, and add per-user limits so cost stays tied to real usage.
- API keys and prompts handled server-side, never shipped in the app
- Streaming responses for a responsive UI
- Sensible offline and error handling
- Per-user usage limits to keep costs predictable
- Consistent behavior across web, iOS, and Android where relevant
More on ai integrations
Frequently asked questions
Can you add AI without disrupting our existing app?
Yes — we integrate into your current codebase and ship the feature incrementally. The AI additions respect your existing data model, auth, and design rather than requiring a rewrite.
Should the AI calls happen on the device or the server?
For most apps, the server. That keeps API keys out of a binary users can inspect, centralizes cost controls, and lets you update behavior without an app-store release. We route calls through your backend by default.
How do you keep it fast and affordable on mobile?
By streaming responses, right-sizing the model to the task, and capping usage per user. We also mind latency, battery, and data so the feature feels native rather than bolted on.