AI-native startups
Your core value proposition depends on an LLM or model doing something genuinely useful, and it has to work reliably in front of real users.
AI MVP development
Custom AI MVP development services that ship real GenAI features, not demos
Anyone can wire a chatbot to an API. Shipping AI into a production product that customers trust is a different job. BuildAID builds GenAI features, LLM integrations, RAG systems, and AI agents into real MVPs, with senior engineers and review gates that keep AI output out of production unchecked.
Who it's for
AI MVP development is for founders building a product where the AI is the product, not a bolt-on gimmick.
Vertical AI tools
You're bringing AI to a specific industry (commerce, hospitality, ops) and need domain data, not just a generic wrapper around a public model.
Products adding a GenAI layer
You have an idea for an AI feature inside a larger product and need it built by a team that knows where AI helps and where it quietly breaks.
What's included
Everything in a standard MVP build, plus the AI engineering that makes GenAI features dependable.
- LLM integration with swappable models
- Retrieval-augmented generation (RAG) pipelines
- Chatbots and conversational interfaces
- AI agents and automated workflows
- Knowledge base ingestion and versioning
- Human-in-the-loop approval gates
- Full-stack development around the AI layer
- Cloud deployment, CI/CD, and hosting setup
- Complete documentation and 30 days support
- 100% code ownership & IP transfer
How we build GenAI features that hold up
The difference between an AI demo and an AI product is engineering discipline. Here's what that looks like on a BuildAID build.
LLM integration, done model-agnostically
We integrate LLMs behind an abstraction so you can swap models as price and quality change, rather than hard-coding a single provider you can never move off.
- Model routing and fallback
- Prompt management and versioning
- Cost and latency monitoring
RAG over your own data
Retrieval-augmented generation grounds the model in your documents and data, so answers reflect your product's reality instead of the model's training set.
- Chunking and embedding pipelines
- Vector search and retrieval tuning
- Source citations and freshness handling
Chatbots and AI agents
From support chatbots to multi-step agents that take actions, we build conversational and agentic features that are scoped, observable, and safe to ship.
- Tool and API calling
- Guardrails and input validation
- Conversation state and history
Human review gates
On RoomSome, every AI response suggestion and every translation is previewed and approved by a person before it reaches the guest. That gate is how a senior team ships AI into a customer-facing surface.
How it works
From first call to production in four steps
Free consultation
A 30-minute call to understand your idea, goals, and technical requirements. No sales pressure.
Fixed-price proposal
Within 24 hours you get a detailed proposal: scope, timeline, tech stack, and a transparent price.
Build in weekly sprints
Development starts immediately. You see a working demo every week, not a surprise at the end.
Launch & 30 days support
We deploy to production, hand over code and docs, and stay with you for 30 days after launch.
Fixed price, agreed upfront
Every project gets a fixed price, agreed in writing before we start, based on scope. The price we agree is the price you pay, with no scope creep. For a fast, no-commitment ballpark, run your idea through the estimator, or tell us your budget on the intro call and we'll shape scope around it.
Related work
Risko
LiveA cash-on-delivery risk scanner for Shopify. Risko scores every incoming order in real time and surfaces explainable risk tags so merchants stop shipping to customers who never collect.
RoomSome
Delivered in 14 weeksA multi-tenant, multi-channel guest communication platform for hotels, built for Morgens Design Kft. One inbox for every guest conversation, with an AI layer that drafts and translates replies behind a human approval gate.
Frequently asked questions
Can AI really build production software?
AI doesn't build it alone; senior engineers do, faster. We use AI-assisted workflows to compress weeks of work into days, and every line is owned and reviewed by an experienced engineer before it ships. The AI is the method; the senior engineer is accountable for the output.
What AI features are worth building at MVP stage?
The ones that are core to your value proposition and can be made reliable. We help you cut features that sound impressive but add cost and fragility without moving your validation forward. Risko, for example, uses a model trained on 250,000+ local orders to score risk, because that scoring is the product.
How do you stop AI from shipping bad output to users?
Review gates. AI output never reaches production or a customer unchecked: PR-based review on every change, human approval before anything customer-facing, and automated tests on every merge. This is what separates AI-assisted engineering from vibe coding.
How is an AI MVP priced?
The same way as any BuildAID project: one fixed price for the agreed scope, in writing, before we start. We scope the AI work explicitly so there are no surprises. Try the estimator for a fast ballpark.
Ready to build it?
Tell us what you're building and we'll come back within 24 hours with scope, timeline, and a fixed price.