Service
AI SaaS Product Development
Taking an AI product from prototype to something you can sell?
VelvoAI builds AI SaaS products end to end: the application, the AI layer underneath it, the tenancy and permissions model, subscription billing, usage metering, and the infrastructure to run it. Not a prototype — a product you can charge for.
Built by VelvoAI, an independent AI systems studio. One engineer scopes and writes every system.
What the system does
- Tenant isolation
- Multi
- Usage billing
- Metered
- Grade infra
- Prod
- ComponentNext.js
- ComponentNestJS
- ComponentPostgres
- ComponentStripe
- ComponentVercel
The problem
Why this keeps costing you
AI product prototypes are quick. Turning one into something you can charge for is not. Tenant isolation, per-customer usage limits, billing that reflects real consumption, cost control on model calls, and an evaluation process that stops quality regressing — that is where most AI products stall.
What we build
Inside an AI SaaS platform we ship
- Multi-tenant architecture with enforced data isolation per customer
- Subscription billing, plan limits, and usage-based metering via Stripe
- Authentication, roles, team management, and invitations
- The AI layer — retrieval, agents, or generation — engineered for cost and latency
- Admin tooling for support, impersonation, and plan management
- Deployment, observability, and CI so shipping is routine rather than an event
How we approach it
The part most implementations skip
We treat model cost and latency as product constraints from the first architectural decision, not as something to optimise after launch. Tenancy, metering, and evaluation get designed in at the start because retrofitting any of the three means a rewrite.
Deliverables
What you actually receive
Every VelvoAI engagement ends with working software you own, not a slide deck. Here is what ships with an AI SaaS platform.
How a build runs, step by step- D.01Product and technical architecture agreed before build starts
- D.02Working application deployed to staging and production
- D.03Billing integration with plans, trials, upgrades, and dunning
- D.04Cost model showing unit economics per active customer
- D.05Handover documentation and a runbook for your team or ours
By industry
AI SaaS Development in your sector
AI SaaS Development, applied to the workflows and rules of the sectors we work with most.
Common Questions
01Can you take over an existing codebase?
Yes. We start with an audit covering architecture, cost exposure, and the parts that will break under load, then agree what is worth keeping before touching anything.
02How do you keep model costs under control?
Model routing so cheap requests do not hit expensive models, aggressive caching of repeated work, prompt and context budgets, and per-tenant usage caps. Costs are tracked per customer so you can see unit economics rather than one alarming monthly invoice.
03What does a typical build take?
A focused first version with billing usually runs eight to fourteen weeks depending on the AI layer's complexity. We scope to a launchable slice first rather than building the full roadmap before anyone can pay you.
Related services
Often built alongside this
- Written by
- Usman Ali, Founder
- Last reviewed
Next step
Ready to scale operations without more busywork?
Bring the workflow, lead leak, reporting gap or knowledge bottleneck. You talk to the engineer who would build it, and leave knowing what it would take to ship.
Free, no obligation.