AI Chat App (White-Label)
Your own branded AI assistant app with subscriptions, chat history, voice input and a model of your choosing behind it.
Result: A shippable product in weeks, not a year of platform work.
06 · AI Android Apps
Android is where India actually is
Over 95% of Indian smartphones run Android. If you are building an AI product for this market, Android is not the second platform — it is the platform. We build apps where the intelligence is the reason someone downloads it.
- Starting at
- ₹3,50,000
- Typical timeline
- 8–16 weeks
- Services in this line
- 8
The problem
Adding a chatbot to an existing app is not an AI app. An AI app is one where removing the model would remove the point.
What we build
8 services in AI Android Apps
Each one is a page of its own — pick the closest match, or tell us your problem and we'll point you at the right one.
Camera + AI App
Point the camera and the app identifies, counts, measures or inspects — plants, parts, defects, inventory, whatever your domain needs.
Result: Expert judgement in the hands of every field worker.
OCR & Document Scanner App
Scans Aadhaar, PAN, cheques, invoices and forms, extracts the fields, validates them and syncs them to your backend.
Result: Onboarding that takes a minute instead of a week.
AI Photo Editor App
Background removal, object erase, upscaling, retouching and generative fill in a fast, monetisable consumer app.
Result: A category with proven willingness to pay.
Voice Note & Transcription App
Records, transcribes and summarises in Indian languages, then turns the result into notes, tasks or CRM entries.
Result: Talking replaces typing.
AI Fitness & Diet App
Photo-based calorie estimation, adaptive workout plans and a coaching chat that remembers the user's history.
Result: Personal-trainer economics at app scale.
AI Tutor & Learning App
Explains, quizzes, adapts to the student's level and marks their work — aligned to CBSE, ICSE or state boards.
Result: One-to-one attention for every student.
Field Staff Reporting App
The rep speaks for thirty seconds after a visit; the app writes the structured report, updates the CRM and files the photos.
Result: Reports that actually get filed, because filing them is effortless.
What you get
Included in every engagement
- Native Kotlin app, or Flutter where cross-platform makes sense
- On-device inference where privacy or offline use demands it
- Play Store listing, assets and submission handled
- Analytics and crash reporting configured
- Backend, auth and payments if the app needs them
- Post-launch support window
How it's built
Typical stack
- Kotlin
- Jetpack Compose
- Flutter
- TensorFlow Lite / MediaPipe
- Firebase
- Play Billing
We pick tools per project rather than forcing every client onto the same stack. If something in your business already works, we build around it instead of replacing it.
In depth
AI Android Apps: what you should know before you commit
Android carries the volume in India and a fraction of the app spending. That single fact should shape everything about an Android AI app — what you charge, what you give away, and how much a free user is allowed to cost you.
The economics you are building inside
Android has the overwhelming majority of Indian handsets and a much smaller share of app revenue. Users expect free, tolerate ads, and convert to paid at rates well below iOS.
For an AI app, where every interaction has a real compute cost, that combination is dangerous. A free user on a conventional app costs you almost nothing. A free user running twenty model requests a day costs you money every day.
So the first design question is not what the app does. It is which operations are free, which are metered, and what a heavy free user costs you in a month. We build that spreadsheet before the wireframes, and it has changed the product concept more than once.
The eight apps in this category
| App | Who buys it | The commercial model that works |
|---|---|---|
| White-label AI chat app | Brands with a specific niche | Subscription, narrow audience |
| Camera + AI app | Agriculture, industry, retail ops | B2B licence or per-seat |
| OCR & document scanner | Businesses drowning in paperwork | B2B, per-user |
| AI photo editor | Consumers | Freemium, metered generation |
| Voice note & transcription | Field staff, doctors, journalists | Subscription or B2B |
| AI fitness & diet | Consumers, gyms | Subscription; B2B2C via gyms |
| AI tutor & learning | Parents, schools | Subscription or institutional |
| Field staff reporting | Sales and service organisations | B2B, per-seat |
B2B Android apps are the underrated opportunity
Five of the eight above are business tools, and that is deliberate. Consumer Android apps in India compete against free alternatives with enormous budgets, and the conversion economics are punishing.
A tool sold to a company for its field staff has none of those problems. The buyer is a business with a measurable cost to remove, the users are given the app rather than choosing it, churn is annual rather than monthly, and nobody expects it to be free.
The same technology, sold to a distributor for their forty sales reps, is a viable business at a scale where the consumer version would not cover its model costs.
On-device processing is a business decision, not a technical one
Recent Android hardware runs useful models locally. That matters here for a reason beyond privacy: an operation that runs on the device costs you nothing per use.
The pattern we build towards is a split. Cheap, common operations run locally — basic background removal, short transcription, simple classification, image quality checks. Expensive operations go to the cloud and are metered or paid.
This makes the free tier defensible. You are giving away the things that cost you nothing, rather than subsidising strangers' compute and hoping enough of them convert.
Play Store rules that catch AI apps
Rejections in this category are predictable and avoidable, and they cluster in a few places.
- Undisclosed AI processing. Users must be told their content is processed by AI, and where it goes.
- No reporting route for generated content. Any app that generates images or text needs a way for users to report output.
- Privacy policy mismatch. The data-safety declarations on your listing must match what the app actually does — this is checked.
- Training on user data without separate consent. Bundling it into general terms is not sufficient under the DPDP Act.
- Screenshots that are not from the app. A surprisingly common rejection, and an easy one to avoid.
Language is a feature, not a translation task
An Android app targeting the Indian mass market that only works in English is addressing a fraction of its potential users.
The distinction that matters is between an interface translated into Hindi and an app that actually works in Hindi — where speech input handles Hinglish code-switching, where the AI reasons and replies in the user's language, and where the vocabulary includes the terms that trade actually uses.
The second one is meaningfully more work and it is where the growth is, particularly outside metros where English-only apps have the least competition and the least traction.
What a build involves
Eight to eighteen weeks depending on the app, from ₹3,00,000 to ₹5,50,000. That includes the app, the backend on your cloud, Play Store submission, subscription or licensing where relevant, and full source.
We publish under your Play Console account, not ours, so you own the listing, the reviews and the user relationship. And we hand over the cost model alongside the code, because in an AI app the per-user economics are part of the product, not an afterthought.
FAQ
Questions people actually ask
Native Kotlin or Flutter?
Kotlin when the app leans on camera, on-device models or platform features. Flutter when you need Android and iOS from one codebase and the AI runs server-side. We will tell you which your app is.
Do you handle Play Store publishing?
Yes — listing copy, screenshots, data safety declarations, policy compliance and submission. Play Store rejections over AI content policies are common and we build to avoid them.
Can the AI work offline?
For many use cases yes, using on-device models. Anything needing a large language model generally needs connectivity, though we cache aggressively for patchy networks.
Other AI service lines
Next step
Let's work out what's worth building.
A 30-minute call. We'll tell you what we'd do, roughly what it costs, and whether it's worth doing at all.