Ship your AI product in 6 weeks
Greta is an MVP development agency that builds production-ready AI products for startups and scale-ups. We handle LLM integrations (that means connecting your app to AI brains like ChatGPT or Claude), RAG pipelines (a way to let AI read your own documents), and vector databases — all shipped in 6 weeks.
Think of your MVP as the first working version of your idea — like a first pancake to test a recipe. We make sure that pancake actually tastes good. From OpenAI and Anthropic API integrations to semantic search with Pinecone and custom fine-tuning workflows, we handle the full AI stack. Your team stays focused on the business, not wrestling with model infrastructure.
6 weeks
Delivery timeline
LLM APIs
OpenAI · Anthropic · Gemini
Vector DB
Semantic search ready
£15k
Starting price
Why building an AI MVP is different from a standard web app
Normal apps do exactly what you tell them, every single time. AI products are different — the AI makes judgment calls. A prompt (think of it as a set of written instructions to the AI) that works brilliantly in testing may give odd answers in production when real users ask unexpected questions. Latency (how long it takes to get a response), token costs (you pay per word the AI reads or writes), and hallucinations (when the AI confidently says something wrong) all need active management from day one — not as afterthoughts.
The infrastructure layer is also more involved. Connecting an LLM API (an API is like a waiter — it carries your order to the kitchen and brings the food back) is straightforward. But building a reliable RAG pipeline — a system that lets the AI read thousands of your own documents and give accurate answers — is a serious engineering challenge. Most first-time AI builders underestimate this by a factor of three or four. The gap between a demo that impresses investors and a product that retains real users lives almost entirely here.
Greta has built AI-powered products across document intelligence, conversational assistants, AI-powered search, automated content generation, and workflow automation. We know where the traps are. Our 6-week process is built around the AI development cycle — including evaluation sprints and prompt versioning that standard web app processes never consider. If you want to understand what a minimum viable product really means before we start, we can walk you through that too.
Ready to build?
Let's bring your idea to life. Fast, affordable, and production-ready.
What we build for AI MVPs
Every AI MVP we scope is shaped around your specific use case. These are the 6 core things we deliver across our AI projects. Whether you need a single feature or the full stack, we get started with a free scoping call.
LLM API Integration
We connect your product to AI models — OpenAI GPT-4o, Anthropic Claude, and Google Gemini. This includes streaming responses (text appears word by word, like ChatGPT), function calling (the AI triggers actions in your app), and multi-turn conversation (the AI remembers what was said earlier). We pick the right model based on your cost, speed, and quality needs.
RAG Pipelines & Vector Databases
RAG stands for Retrieval-Augmented Generation. Think of it as giving your AI a personal library. We index your documents, PDFs, or database records into a special searchable format (a vector database), so when a user asks a question, the AI finds the most relevant pieces of your content first — then answers based on that, not just its general training.
Prompt Engineering & Evaluation
Prompts are the written instructions that tell the AI how to behave — like a job description for your AI employee. We design, version, and test these carefully. We set measurable quality baselines before building anything, then keep improving to cut wrong answers and reduce the cost per query.
AI Feature Layers on Existing Products
You don't always need to start from scratch. We add intelligent features to products you already have: AI-powered search, automatic summaries, smart form filling, automated tagging, and conversational chat windows — all wired into your existing data and connected via your existing API (the behind-the-scenes connector between different parts of your software).
Fine-Tuning & Custom Models
Sometimes the off-the-shelf AI isn't specialised enough for your industry. Fine-tuning is like sending the AI to a specialist training course using your own data. We manage the whole process — preparing your dataset, running training, checking quality, and deploying the tuned model to production.
AI-Powered Search & Discovery
Keyword search only works when users know the exact right words. Semantic search (powered by embeddings — a way of turning words into numbers that capture meaning) finds what users are looking for even if they phrase it differently. It dramatically improves engagement for data-heavy products. We also build <Link href='/analytics-dashboard-development/' className='text-accent hover:underline'>analytics dashboards</Link> so you can see exactly how users interact with your AI search.
BUILD IT FAST
Ready to build your AI product?
Tell us your use case and we'll scope your AI MVP — LLM stack, data architecture, timeline, and fixed price — within 48 hours of your discovery call.
TALK TO A FOUNDER
Not sure where to start?
Book a 20-minute call. We'll map out your scope, tech stack, and go-to-market plan — for free.
Our 6-week AI MVP process
Here is exactly what happens, week by week. No vague "agile methodology" talk — just concrete steps. This same process works whether you are a solo founder or a growth-stage company adding AI to an existing B2B SaaS product.
- 01
AI Discovery & Architecture (Week 1)
We sit down (virtually or in person) and map your AI use case in detail. What must the AI do? What data does it need? Which model fits your budget and speed requirements? We deliver a plain-English technical plan and a fixed-price quote by the end of week one — no surprises later.
- 02
Data Pipeline & Prompt Engineering (Weeks 2–3)
We prepare your data — parsing PDFs, syncing databases, or pulling from your existing APIs (remember: API = the waiter between your data and our system). We generate embeddings (the numerical fingerprints of your content), load them into a vector database, and write the first version of the AI instructions. We set a quality baseline before any product screen is built.
- 03
Core AI Feature Build (Weeks 3–4)
We connect the AI engine to your product. Streaming responses go live (text appears in real time). The AI can trigger actions in your app via function calling. Conversation memory is set up so the AI remembers what a user said earlier in the session. By the end of week 4, the core AI feature works and your team can test it internally.
- 04
Product UI & End-to-End Testing (Week 5)
We wrap the AI engine in a clean user interface — a chat window, a smart search bar, a <Link href='/analytics-dashboard-development/' className='text-accent hover:underline'>reporting dashboard</Link>, or an embedded widget in your existing app. We also run 'adversarial' tests: we deliberately try to confuse the AI with tricky or unexpected questions, so we know it holds up under real-world use.
- 05
Evaluation, Launch & Handover (Week 6)
We put it live. We set up monitoring so you can see when the AI gives a bad answer or slows down. We hand over everything: the AI model settings, the prompt library (your AI's instruction manual), the database structure, the deployment pipeline, and a plain-English runbook your team can follow to update things later.
How AI MVP development options compare — 2026
You have 4 realistic options for building your AI product. Here is how they stack up. If you are evaluating no-code tools alongside a specialist agency, this table will help you decide.
| Option | Cost | Timeline | Support |
|---|---|---|---|
| Traditional agency | £80,000–£200,000 | 6–12 months | Extra cost |
| Freelancer | £20,000–£60,000 | 3–9 months | You manage it |
| No-code AI tools | £0–£500/month | Weeks | Very limited |
| Greta | From £15,000 | 6 weeks | Included |
BUILD IT FAST
Get a fixed-price AI MVP quote
We scope AI MVPs in 48 hours. Tell us what you want to build and we'll come back with a full technical plan, LLM stack recommendation, and a fixed price.
TALK TO A FOUNDER
Not sure where to start?
Book a 20-minute call. We'll map out your scope, tech stack, and go-to-market plan — for free.
Who builds an AI MVP with Greta?
Most of our AI clients fall into 3 groups. First: early-stage startup founders who have raised pre-seed or seed money and need to show investors a working AI product — not a slide deck. Second: product teams at growth-stage companies who want to add AI features to an existing SaaS product without rebuilding the whole thing. Third: non-technical founders who have a clear problem to solve but no engineering team yet.
All 3 groups share one thing: they need a real, working AI product in front of users quickly. Not a prototype that breaks in demos. Not a proof-of-concept that lives on a laptop. A production-ready product with proper error handling, cost controls on the AI calls, and monitoring so you know when something goes wrong.
If you also need an API product alongside your AI feature — for example, to let other developers or apps connect to your AI — we build that too as part of the same engagement. Many AI products need both a user-facing interface and a developer-facing API. We scope and price both together.
Frequently asked questions about AI MVP development
How long does it take to build an AI MVP?+
Greta delivers AI MVPs in 6 weeks. Week 1 covers discovery and the technical plan. Weeks 2 and 3 focus on getting your data ready and writing the AI instructions. Weeks 4 and 5 build the product screens and run tests. Week 6 is launch and handover. If your project needs custom model training or a very large data set, we will tell you that up front at the discovery call — no surprises.
Which LLM providers do you work with?+
We work with all the main ones: OpenAI (GPT-4o), Anthropic (Claude 3.5 Sonnet), Google (Gemini 1.5 Pro), and open-source models you can run yourself. We pick the best fit for your budget, speed needs, and use case — not the one that is most fashionable right now.
What is a RAG pipeline and do I need one?+
RAG stands for Retrieval-Augmented Generation. In plain English: it lets the AI read your own documents before it answers a question. Without RAG, the AI only knows what it learned during its training — which does not include your company's data. If your product needs to answer questions about your own PDFs, support tickets, internal guides, or product catalogue, you need a RAG pipeline. Most serious AI products do.
How much does an AI MVP cost?+
Our AI MVP projects start from £15,000. A typical 6-week build — LLM connected, RAG pipeline working, and a clean user interface live — runs between £15,000 and £35,000. Projects that need custom model training or ingesting very large data sets are scoped and priced separately. We give you a fixed price after a free discovery call. No open-ended time-and-materials billing.
Can you add AI features to my existing product?+
Yes — and this is actually very common. We add AI layers on top of products you already have. Think: an AI assistant that reads your knowledge base, a smart search bar that finds results even when users mis-spell things, or automated summaries of long reports. We connect these features via your existing API and work within whatever tech stack you already use.
Sources & further reading
External references cited on this page.
Stanford AI Index Report 2024
Annual report tracking AI research, deployment, and economic impact — Stanford HAI.
McKinsey: The state of AI in 2024
McKinsey Global Survey on enterprise AI adoption rates, use cases, and ROI benchmarks.
OpenAI API Documentation
Official reference for GPT-4o, fine-tuning, embeddings, function calling, and assistants API.
Anthropic: Claude API Documentation
Official documentation for Claude 3.5 Sonnet, tool use, and prompt engineering best practices.
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Your AI MVP, live in 6 weeks
Stop waiting for the right time to build. Whether you need an LLM connected to your app, a full pipeline that reads your own documents, or an AI feature added to something you already have — we scope it, build it, and launch it. Fixed price, fixed 6-week timeline, no surprises. Book a free discovery call and get a real price within 48 hours.
Free 30-minute discovery call. Real pricing within 48 hours.