AI App Development

Service overview

AI app development is product work. We scope the job the model is allowed to do, the data it may see, and the fallback when inference is slow or wrong. The app still needs onboarding, permissions, analytics and a backend. We already ship that as a mobile app development company; the AI slice is designed as a feature with evaluation, not a demo reel.

Problems we solve

• A pitch deck ‘AI app’ with no source of truth, so answers drift and support tickets explode.
• Inference that looks fine in a notebook and fails on mid-range Android or a slow hotel Wi-Fi.
• Store and privacy copy that does not match what the model actually does.
• A first release that tries to ‘add AI everywhere’ and ships nothing users finish.

What we build

• In-journey AI (score, try-on, summarise, route) with a visible fallback
• Mobile and web clients sharing one API and one evaluation set
• Permission, consent and logging appropriate to the data
• Latency budgets and offline or degraded modes
• Play Store and App Store packaging when the product is mobile
• Post-launch monitoring of failures, not only happy-path demos

Benefits

• An AI feature operators can explain to a customer, not a black box slogan.
• The same delivery bar as our other apps: milestones, QA, store hygiene.
• Honest scope: we will say when a rule engine beats a model.

Use cases

• Resume or listing quality scores with an explanation, as on JobForge.
• Visual try-on and style discovery, as on Try Ware.
• Summaries of readings or tickets that a human still owns.

Technologies

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Relevant case studies