AI Product Strategy
Use case selection, the product brief, the architecture and the roadmap, before the first commit.
AI Development
AI Product DevelopmentFrom AI Use Case to AI Product.
AI product development for the journey from a successful AI use case to a product with users, billing and a roadmap — the multi-tenant architecture, the API, the admin, the evaluations at scale and the go-to-market, built with the engineering rigour the product needs to last.
10+Years Experience
100+Projects Delivered
50+Expert Developers
20+Industries Served
AI Product Strategy
Multi-Tenant AI
AI API & SDK
AI Admin & Console
AI Pricing & Billing
AI GTM & Launch
Overview
An AI product is a SaaS product with intelligence at the core
An AI product is a SaaS product that happens to use a model. The model is one component. The other components — the multi-tenant architecture, the auth, the billing, the admin, the API, the evaluation suite at scale, the go-to-market — are the same as any other SaaS product, with the AI twist on top.
We build AI products against the same engineering rigour as any other SaaS product, with the AI components (model, data, evaluation, guardrails) designed as part of the architecture from sprint one. The output is a product that lasts, not a demo that breaks the day after launch.
This is the wrong engagement if the goal is a one-off AI use case, not a product. For a use case, the right answer is a custom AI solution, not an AI product.
- Built to Last — Multi-tenant, API-first, with the evaluation suite that scales with the product.
- Cost-Defensible — Per-tenant cost, the token budgets and the metering that keep the margin honest.
- Evaluated at Scale — An evaluation suite that runs per-tenant, with the regressions caught early.
- GTM Ready — The docs, the SDK, the landing pages and the launch the AI product needs.
What we deliver
Everything included in our ai product development
Multi-Tenant AI
Multi-tenant AI with the isolation, the per-tenant evaluation and the per-tenant cost controls.
AI API & SDK
A public API and an SDK so customers can build on the AI product.
AI Admin & Console
The admin console, the usage dashboard, the per-tenant cost and the eval view.
AI Pricing & Billing
Usage-based pricing, the metering, the billing integration and the dunning.
AI GTM & Launch
The go-to-market, the landing pages, the docs and the launch the AI product needs.
Our process
A proven process for successful delivery
01
Discover
We agree the use case, the product brief, the architecture and the roadmap.
02
Plan & Design
We design the multi-tenant architecture, the API, the admin and the evaluation suite.
03
Develop
We build in two-week sprints with a working slice every Friday.
04
Deploy
We ship to production with the billing, the metering and the observability live.
05
Optimize & Grow
We read the data, the cost and the evaluations, and ship the next iteration.
Technology
Built with a stack that stays maintainable
Models
- OpenAI
- Anthropic
- Google Gemini
- Open source LLMs
Backend
- Python
- Node.js
- Laravel
Database & Search
- PostgreSQL
- Pinecone
- Weaviate
- Elasticsearch
Billing & API
- Stripe
- Razorpay
- Kong
- Tyk
What you can expect
- To First Production Release
- 12-20 wksTo First Production Release
- Target Uptime
- 99.9%Target Uptime
- Cost & Eval
- Per-TenantCost & Eval
- Architecture
- Multi-TenantArchitecture
Industries we serve
Delivered for teams in your sector
A custom AI solution solves one business problem for one customer. An AI product is a product with many customers, billing, a roadmap and a go-to-market. The engineering rigour is the same as a SaaS product, with the AI components on top. The investment is worth it when the use case is reusable across many customers.
It depends on the value, the cost and the competitor landscape. Usage-based pricing (per token, per request, per outcome) is a common default. Seat-based pricing works for products where the AI is a feature of a workflow. Outcome-based pricing is the most ambitious, and the hardest to operate. We will say so on the call.
Per-tenant cost, the token budgets, the caching, the batching, the model routing. The cost is a non-functional requirement, not an afterthought. We design against the cost from the first sprint, and the dashboards show the per-tenant cost against the budget.
The evaluation suite runs per-tenant, with a baseline test set that the product ships with and the per-tenant evals that the customer can add. The regressions are caught early, and the eval results are surfaced in the admin console. The product gets smarter with each tenant, without leaking data across tenants.
Related services
More in AI Development
Business software
ERP, CRM, HRMS & custom software we build
Ready to start your ai product development project?Let’s scope it together.
Tell us the outcome you need. We’ll come back with an approach, a timeline and a written estimate.