How do I choose an AI development company?

Judge execution, not slides. Ask who writes the actual code, how soon you'll see working software on your real data, the single business number the build is judged against, whether you own the code and data at the end, and how they handle security. A company that answers with a deck and a roadmap instead of a demo is the one to walk away from. Finzarc's founders build and sell, ship a first production version in about three weeks, and hand over code you own outright.

What questions should I ask an AI vendor before hiring them?

The seven that matter: Who writes the code? When do I see working software on real data? What one metric is the build judged against? Do I own the code, models and data? How is my data secured? Is pricing fixed-scope or an open-ended meter? And can you show a delivered build with the number attached? Vague answers to these are the warning sign.

What's the difference between an AI consultancy and an AI studio?

A consultancy sells strategy, decks and roadmaps and often hands delivery to a separate team; an AI studio like Finzarc builds and ships the software itself. If the people who scope your system are not the people who write the code, you're buying advice, not a system. Working software over promises of future.

How long should an enterprise AI project take to show results?

You should see working software on your real data within weeks, not quarters. Finzarc demos every week and ships a first production build in about three weeks. If a vendor's plan front-loads months of strategy and discovery before anything runs, that's where most enterprise AI quietly dies.

How to Choose an AI Development Company: 7 Questions to Ask Before You Hire

Most AI vendors sell decks; a few ship software. The seven questions that separate builders from deck-makers before you sign — from who codes to who owns it.

Picking an AI development company is mostly an exercise in telling builders from deck-makers. Every vendor will claim production experience, an elite team and a proven process. Very few will show you working software on your data inside a month. This is the checklist we’d use — the same standard Finzarc is built to pass: the founders build and sell, first delivery is about three weeks, and every claim ships with a log attached.

Why does choosing the wrong AI partner cost so much?

Because the failure is quiet and expensive. The usual pattern is a long strategy phase, a promising pilot, and then nothing that reaches production — where AI pilots quietly fail inside organizations is rarely the model and almost always the handoffs, ownership gaps and integration work no one scoped. Roughly 80–85% of enterprise AI projects never make it from pilot to production, and most of that budget is spent before anyone can tell whether the thing works. The right partner de-risks that by shipping something real, fast, that you can judge and stop.

Who will actually write the code?

Ask this first, and listen for a straight answer. On many engagements the senior people who win the deal are not the people who deliver it — the work is handed to a junior bench or a subcontractor once the ink is dry. At an AI studio where the founders build and sell, the engineers on your first call are the ones who write the code. Fewer handoffs means fewer things lost in translation, and the person answering your hard question is the person doing the work.

How soon will I see working software on my own data?

A demo on curated sample data proves nothing; the enterprise reality is messy, and that mess is where projects die. The test that matters is: how quickly do I see a working version running on my real data? If the answer is measured in quarters, that’s a red flag. Finzarc demos working software every week and ships a first production build in about three weeks — see how long it actually takes to build an AI system and the delivered builds behind those timelines.

What single metric will the build be judged against?

A good AI partner ties the work to a business number before it starts — hours returned, revenue surfaced, forecast accuracy, cycle time — not a vague “efficiency gain.” That anchor is what makes ROI provable instead of estimated. Across Finzarc’s delivered builds, that framing has meant a revenue-maximisation platform that lifted revenue +27% and margin from 30% to 38% and GRN reconciliation that cut roughly ₹10 crore a year in write-offs by ~90%. If a vendor won’t name the number, they’re not accountable to it.

Do I own the code, models and data at the end?

Read the IP clause before you sign. Some vendors retain rights to the models, reuse your data to train systems for other clients, or lock you into a platform you can’t leave. Insist on full ownership and handover: the code, models and data are yours, running in your environment, with your team able to take over whenever they choose. Ownership is the difference between hiring a builder and renting one indefinitely.

How is my data secured — and will you sign an NDA?

Enterprise data is the whole risk surface. A serious partner works inside your security boundary, builds on your infrastructure and cloud accounts, signs an NDA before the scope call on request, and scopes agent access to exactly what a build needs — with every action logged and reversible. If security is an afterthought in the conversation, it will be an afterthought in the build.

Is the price a fixed scope or an open-ended meter?

For a first build, fixed scope protects you: you agree what ships, the timeline and the number it should move before work starts. Open-ended time-and-materials on a first engagement is a red flag — see how much it costs to build a custom AI system and why pricing to the metric beats billing by the hour. And before you shortlist anyone, the practical checklist for teams that care about execution turns these questions into a scorecard.

The one test that beats the whole checklist

Ask any vendor to show you a delivered build with the number attached, then ask to see working software on your data in three weeks. The ones who can are the ones worth hiring. If you want to run that test with us, bring one problem to a 30-minute scope call and leave with a scope, a timeline, and the metric it should move — from the founders who build it. Working software over promises of future.