Most AI companies build demos. We ship AI that survives app store review. Our own patent-filed platform runs AI voice in 30+ languages, live on both stores, every single day. This page is the map of everything we build with AI — and an honest note on where AI isn't worth your money.
Nearly every AI project we're asked to rescue died in the same place: the gap between something that impressed in a meeting and something that could face real customers, real money and a store reviewer.
An unconstrained model will invent a refund policy, agree to a discount nobody approved, or answer a question it had no business answering. Guardrails, tool boundaries and human approval on irreversible actions are the difference between a feature and a liability — and they're most of the engineering.
The prototype called the biggest model for every request because it was easy. At ten users nobody noticed. At ten thousand it became the second-largest line item in the business. Model selection per task, caching and hard limits have to be designed in, not bolted on after the first shocking invoice.
Google Play and the App Store treat user-facing AI as a risk surface. Without content moderation, a report-and-block flow and clear AI disclosure, the build is finished and the product still can't launch. We know this one exactly — it happened to us, and we engineered our way out of it.
We're a small team in Pilani that builds and runs its own AI products. That means we've paid for every one of these mistakes ourselves — which is why we design around them from day one instead of discovering them on your budget.
Most businesses need two of these, not four. Each one has its own page with real pricing, real timelines and the honest limits — start wherever your problem actually is.
Underneath all four sits the same safety layer — moderation, abuse prevention, report-and-block pipelines, usage limits and audit logging. We don't price it separately, because AI without it isn't shippable.
We're not describing AI capability from a vendor deck. We built an AI product, filed a patent on it, got rejected by Google Play, engineered the safety layer, got approved, and now run it for real users every day.
A patent-filed child-safety platform (app no. 202631050115) with AI running daily — our money, our risk, our uptime.
We took an AI app from a Google Play rejection to a live listing by building the moderation and reporting layer reviewers demand.
AI voice in 30+ languages with per-user detection — tested against how customers actually speak, not clean sample text.
AI is the new part; shipping software isn't. Payments, apps, backends and security work delivered across seven markets.
Want the detail? Read how we got an AI app past Google Play review or what broke when we shipped AI voice in 30+ languages.
No twelve-week discovery invoice before a line of code exists. You see something working in week one, and every stage after that is a decision point you control.
You describe the task. We tell you whether AI is the right tool, what it would touch in your systems, and roughly what it costs to run each month. Sometimes that call ends with us saying you don't need us.
Scope, timeline, price and the integration surface written down. No hourly-billing surprises, no vague retainers, no "we'll see how it goes" on the invoice.
Real data, your actual use case, running end to end. You judge the direction while it's still cheap to change — not at delivery when changing it costs a rebuild.
Guardrails, moderation, rate limits, cost caps, error handling, audit logging and store-compliance work. This is the unglamorous phase that decides whether the thing survives contact with real users.
Documented prompts, tools and configuration in your repo so another team could take over tomorrow. Or keep a dedicated developer on it monthly. Both are fine — we don't build lock-in.
These are real starting prices, not "contact us for pricing". Final numbers come from the integration surface — how many of your systems the AI has to touch — which is exactly what the scoping call is for.
You don't need a new platform to add AI. Both of our own products had AI added after launch, so retrofitting into a live codebase is the normal case for us, not the exception. We work model-agnostic and put an abstraction layer between your product and the provider — because the best model changes every few months and your architecture shouldn't.
Every AI agency page you'll read today claims everything. Here's the list we'd want if we were the ones buying.
If that list cost us your project, it was the right list. The clients we keep for years are the ones who were told the truth in week one.
We run daily standups with clients across seven markets. Our morning covers Asia-Pacific and the Gulf; our evening covers UK and US East Coast. Everything ships in English, with documentation your in-house team can pick up.
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Free 30-minute call, fixed quote within 24 hours — including the times we tell you plain automation would be cheaper and better than AI.
support@thetechnosquare.com · Pilani, Rajasthan, India · Working worldwide 🌍