Practical AI features that actually improve products — chatbots, smart search, personalization — and the architecture to ship them reliably.
Start with the problem, not the model
The best AI features are invisible: search that understands typos and intent, support that answers instantly at 3 a.m., onboarding that adapts to each user. The worst are chatbots bolted onto apps that didn't need them. Before any integration, identify a moment where users currently get stuck, wait, or leave — that's where AI earns its cost.
In 2026 you almost never need to train your own model. GPT-class APIs from OpenAI, Anthropic, and Google handle language tasks; on-device models handle vision and speech without privacy concerns. The engineering work is in the integration: grounding, guardrails, latency, and cost control.
The architecture that works
Never call AI APIs directly from the mobile app. Route every request through your backend: it keeps API keys safe, lets you swap providers without an app update, enables caching (which can cut costs 40–60% for repeated queries), and gives you one place to log, rate-limit, and moderate.
For chatbots and support assistants, retrieval-augmented generation (RAG) is the standard pattern: your documents are indexed in a vector database, relevant passages are retrieved per question, and the model answers only from that context. Done right, it eliminates most hallucinations because the bot cites your actual content rather than improvising.
Costs, latency, and the details that bite
Model pricing has fallen dramatically, but costs still scale with usage — a support bot serving 10,000 conversations a month might cost $50–$300 in API fees depending on the model tier. Use smaller, faster models for classification and routing, and reserve premium models for the conversations that need them.
Stream responses token-by-token so users see answers begin instantly, set timeouts with graceful fallbacks, and always provide an escape hatch to a human. AI features are judged by their worst interaction, not their average one.
Where to start
The highest-ROI first projects we see: a support assistant trained on your help docs, semantic search over your catalog or content, and automated summarization of user-generated text. Each ships in two to four weeks and produces measurable wins — deflected tickets, better conversion, longer sessions.
We build AI features into both new and existing apps, with the unglamorous parts — security, caching, fallbacks, cost monitoring — handled properly. If you're wondering whether your product has a genuine AI use case, ask us; we'll tell you honestly.
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