AI product cost estimator Price your AI product. Get it built at $0.

With Axionry, a clickable demo starts around $1,000, a launch-ready MVP with sign in, billing, admin and one AI feature starts around $3,600, and an AI-first product with an agent and RAG at its core starts around $5,500. US agencies quote $50,000 to $150,000 for a production MVP. What moves the price is scope: surfaces, AI depth, integrations and compliance. No launch-ready build goes over $10,000, enterprise-grade work is priced on a call, and the exact price is always decided once we connect, based on the actual work.

A demo you can click through costs from about $1,000 and takes 3 to 5 working days. A launch-ready MVP runs $3,600 to $5,500 over 2 to 3 weeks. For the same production MVP, US agencies quote $50,000 to $150,000, offshore agencies $20,000 to $60,000 and freelancers $5,000 to $25,000.

A demo takes 3 to 5 working days. A launch-ready MVP takes 2 to 3 weeks, an AI-first product 3 to 4 weeks, and a private AI platform 3 to 4 weeks, including a week of assessment. A demo ships within two weeks and a launch-ready build within four; bigger scope gets more engineers in parallel, not more weeks. Timelines can be discussed.

At launch, hosting and a database start around $45 a month at list price: Vercel Pro at $20 and Supabase Pro from $25. Model usage is usually the line that grows fastest. A thousand users on Claude Sonnet 5, each making a few AI requests a working day, runs a few hundred dollars a month, and a small model like GPT-5.6 Luna cuts that roughly tenfold. A private model on one A100 80GB costs about $1,150 to $1,350 a month around the clock.

Usually not. Self-hosting makes sense when data legally or contractually cannot leave your network, when inference already costs five figures a month, or when you need a model version pinned for years. Otherwise an API is cheaper and simpler, and we will say so.

Below about 20,600 minutes a month, a managed platform like Retell or Vapi is usually the right call. Above it, a custom LiveKit stack at 2.5¢ a minute, against 11 to 12¢ on the managed platforms, pays for its build quickly.

No. The build is split into checkpoints with acceptance criteria agreed before work starts, and each checkpoint is invoiced only after you have seen it and accepted it. Your first payment follows the first piece of work you have accepted.

No. It is a range built from our published prices. Your price is fixed in writing after a 20-minute call, before any work starts.

Yes. Frameworks, databases and models are included because the choice rarely changes the build price. Scope is what moves it. If a choice will cost you later, we will say so on the call.

Our AI in your product package runs from $3,100 to $5,500 over 2 to 3 weeks. It is built inside your codebase and includes an assistant grounded in your data, with evals and guardrails. Working in an existing product starts with a codebase review, integration and release, estimated at $2,000 to $3,500, in place of the setup line a new build carries.

The Voice AI agent package runs from $2,800 to $3,600 and takes 2 to 3 weeks. It covers inbound calls 24 hours a day, warm transfer to a person, and recordings, transcripts and QA. Running costs are separate: our production voice stack costs 2.5¢ a minute, and below about 20,600 minutes a month a managed platform is usually the better call.

Running around the clock, a small 8B to 14B model on one L4 costs about $360 to $640 a month, a 27B to 32B model on one A100 80GB about $1,160 to $1,370, and a 70B class model on two H100s about $4,200 to $4,900. Frontier open weights on eight H100s run $16,900 to $19,500. Running only in working hours cuts that by about 70%.

After a call and a written plan with acceptance criteria, which cost nothing, payments follow four checkpoints: architecture and a first working flow, the core product, AI on your real data or the rest of v1, and launch with handover. The estimator shows the amount for each one. Every checkpoint is invoiced only after you have seen it working and accepted it.

A demo is clickable and real where it matters, on test data, and costs about an eighth of a launch-ready build. Launch-ready adds production architecture, tests on the risky paths, monitoring and a handover your team can run. Enterprise-grade adds load testing, high availability, auditing and documentation for a larger team. Switch between them in the estimator to see the price move.

The ones that grow after launch. Model usage is usually the fastest-growing monthly line, and agents multiply it because each task makes several model calls. Integrations with systems like Salesforce, NetSuite or an EHR are among the largest build lines. Compliance such as SOC 2, HIPAA or data residency is best planned from the start. A private model adds a monthly GPU bill.

The estimator answers that for your exact scope. It prices two in-house engineers at the US median software developer wage of $135,980 a year for the weeks your build takes, before benefits, recruiting and the months hiring takes. Your Axionry price appears beside it, along with US agency, offshore agency and freelancer marketplace ranges for the same scope.