You will get a production-ready AI MVP in 2 weeks: web app, API, and LLM features
Project details
I build AI products end to end: the web app, the API, the database, the infrastructure, and the LLM layer that makes it useful. Over the past six years I have shipped 50+ products, including an AI event-marketing platform that generated 30K+ leads and a three-sided marketplace that reached 15K monthly active users.
The approach is deliberately fast and visible. A clickable proof of concept in about 3 days, so you can see whether the idea holds before spending real money. A full MVP inside 2 weeks. Weekly demos, access to the repository from day one, and the complete source code at the end.
Typical work: RAG and semantic search over your own data, AI agents with tool calling, chat and copilot interfaces, document and data pipelines, plus the ordinary product plumbing around them (auth, payments, admin tools, CI/CD). Stack: TypeScript, Next.js and React, Node.js, Python, PostgreSQL, vector databases, and OpenAI, Anthropic or Google models, deployed to Vercel, Cloudflare, AWS or GCP.
The approach is deliberately fast and visible. A clickable proof of concept in about 3 days, so you can see whether the idea holds before spending real money. A full MVP inside 2 weeks. Weekly demos, access to the repository from day one, and the complete source code at the end.
Typical work: RAG and semantic search over your own data, AI agents with tool calling, chat and copilot interfaces, document and data pipelines, plus the ordinary product plumbing around them (auth, payments, admin tools, CI/CD). Stack: TypeScript, Next.js and React, Node.js, Python, PostgreSQL, vector databases, and OpenAI, Anthropic or Google models, deployed to Vercel, Cloudflare, AWS or GCP.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Models
OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$5,000
|
Advanced
$9,000
|
|---|---|---|---|
| Delivery Time | 3 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | |||
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | ||
Source Code |
Frequently asked questions
About Andrey
AI & Full-Stack Developer
Plovdiv, Bulgaria - 10:34 pm local time
With 6+ years of experience and 50+ deployed applications, Andrey helps businesses transform ideas into production-ready products. His approach is fast and iterative: 3 days to a proof of concept, 2 weeks to an MVP. He works across the full stack — from frontend interfaces to backend APIs, databases, infrastructure, and DevOps.
Andrey also consults engineering teams on adopting AI-native development workflows — integrating AI coding tools into daily work, restructuring CI/CD pipelines for AI-assisted code generation, setting up PR review processes for AI-written code, and adding security and quality guardrails.
Steps for completing your project
After purchasing the project, send requirements so Andrey can start the project.
Delivery time starts when Andrey receives requirements from you.
Andrey works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff and scope
A call to agree what the MVP has to prove, and to cut everything that does not serve it. You get a written scope, architecture sketch and delivery plan the same day.
Proof of concept
Within about three days the core AI feature works end to end and is deployed, so you can click it and judge whether the idea holds before the full build.