AI Product Development: Build Your AI App, SaaS or MVP
Zunaki designs and builds AI-powered products — from a first working prototype to a production app your users pay for. Web, iOS and Android, built on large language models, your data and a clean, scalable stack.
- Idea to launched product
- Web, iOS & Android
- LLMs, RAG & AI agents
- You own the code
AI Products Tailored to Your Vision
We work with founders, startups and enterprises to build revenue-generating AI applications from the ground up.
AI SaaS Platforms
Subscription web apps with AI at the core — user accounts, billing, dashboards and admin tools included.
AI Assistants & Copilots
Chat and copilot experiences that help users write, plan, analyse or get answers inside your product.
Knowledge & Search Apps (RAG)
Apps that answer questions from your documents, help centre or database with sources users can check.
AI Mobile Apps
iOS and Android apps with AI features — and we publish them to the stores for you too.
Document & Image AI
Extracting data from invoices, forms, IDs and images, and turning it into structured, usable information.
AI Features for Existing Products
Smart search, summaries, recommendations and automation added to the app you already have.
Our AI Product Development Process
A structured 5-stage engineering lifecycle designed to validate early, minimize risk, and ship fast.
Discovery & Scoping
We clarify user personas, core workflows, and the primary AI value driver, delivering a fixed architecture spec and timeline.
AI Prototype
A fast interactive prototype tests model accuracy, prompt chains, and guardrails against real customer edge cases.
Production MVP
Full-stack development: modern frontend, secure API endpoints, auth, billing, analytics, and admin dashboards with regular demos.
Launch & Publish
Cloud infrastructure deployment and complete Google Play / iOS App Store publishing with ASO listings.
Evaluate & Scale
Continuous telemetry monitoring model latency, token costs, and user retention to fine-tune retrieval and expand capabilities.
Technology We Use
We pick proven, production-grade tools so your product is fast, secure, easy to maintain, and ready to scale.
React & Next.js
Blazing fast server-rendered interfaces with TypeScript, modern styling, and seamless user experiences across devices.
iOS & Android Apps
Cross-platform Flutter / React Native or native builds tailored to your app store targets and native hardware features.
Node.js, Python & FastAPI
Robust asynchronous microservices, streaming endpoints, and hardened APIs designed for real-time AI workloads.
State-of-the-Art LLMs
Direct API integration with Claude 3.5, OpenAI GPT-4o, Google Gemini 2.0, or self-hosted open weights like Llama 3.
Vector DBs & Embeddings
Pinecone, Qdrant, Chroma or pgvector paired with dense semantic embeddings for hallucination-free retrieval.
Your Cloud Accounts
Deployed directly into your AWS, GCP, or Azure subscription so your team retains 100% data ownership and billing control.
What Affects the Cost of an AI Product
Transparent scoping with zero surprises. We help you launch an MVP first to validate before scaling up.
Screen & Feature Count
The total user journeys, authenticated role tiers, and custom workflow logic included in the initial launch version.
Web, iOS & Android
Whether you need a web app only, or unified releases across the Apple App Store and Google Play Store.
Model & RAG Complexity
Single prompt wrappers vs autonomous multi-agent tool loops and retrieval over gigabytes of private internal documents.
Third-Party Ecosystems
Direct connections to payment gateways (Stripe/Razorpay), CRMs, ERPs, WhatsApp Cloud API, and internal databases.
Usage & Running Costs
Calculated upfront so your per-user inference costs remain predictable, cacheable, and highly profitable as you grow.
Enterprise Readiness
SOC 2 compliance needs, strict data isolation, specialized SLAs, and high-availability backup systems.
Frequently Asked Questions
It depends on scope. A focused prototype that proves the core AI feature can often be built in a few weeks, while a production-ready MVP with user accounts, payments and admin tools takes longer. After the discovery call we give you a timeline for your specific feature list.
Cost depends mainly on the number of features, platforms (web, iOS, Android), integrations, and how much AI processing each user needs. We recommend starting with a small first version that proves the idea, and we give a fixed quote for it after scoping.
We choose per project. Hosted large language models from providers such as OpenAI, Anthropic and Google are usually fastest to ship with, while open-source models can make sense when you need to run everything on your own infrastructure. We design the product so the model can be swapped later.
We ground answers in your own data using retrieval-augmented generation (RAG), constrain outputs with structured formats and validation, add guardrails for sensitive topics, and test the product against a set of real example questions before launch.
Yes. You own the code, designs and data we create for your product, and everything is delivered to your own repositories and cloud accounts.
Yes. Many projects are about adding AI to an existing web or mobile app — for example a support assistant, smart search over your content, document processing, or AI-generated content features.