You will get AI Prototype / MVP in 2 Weeks
Project details
Got an AI product idea but no time to build it yourself? I'll take your concept from zero to a working, deployed AI product in exactly 14 days — model layer, backend API, and a clean frontend interface, all running live on AWS. No vague prototypes, no handoffs between specialists, no scope creep. One engineer owns the entire build end-to-end. You walk away with full source code, a live deployment, and something you can demo to investors, customers, or your team on Day 14. Tell me the idea — I'll handle everything else.
What's included $1,500
These options are included with the project scope.
$1,500
- Delivery Time 15 days
- Number of Revisions 1
Frequently asked questions
About Sagar
AI and Software Product Engineer | Python | Go | Rust | AWS
Navi Mumbai, India - 2:27 am local time
What I build:
→ AI + SaaS Products — full-stack applications with LLM capabilities baked in from day one, not bolted on later. Built for real users, real scale, real businesses
→ LLM Applications & AI Agents — RAG pipelines, document intelligence, agentic workflows, custom chatbots — production-grade, not proof-of-concept
→ Custom ML Models & LLM Fine-tuning — when off-the-shelf models aren't enough, I build and fine-tune for your domain, your data, your edge cases
→ Fast backends in Python (FastAPI, LangChain) or Rust when throughput and latency actually matter
→ Clean frontends in React or Svelte — interfaces that make AI feel intuitive, not clunky
→ Cloud infrastructure on AWS — containerized, scalable, production-hardened
→ Enterprise Architecture — system design for complex organizations, multi-service integration, data migration at scale, performance optimization
→ Prototypes & MVPs — for founders who need to validate fast or walk into a board room with something real
Industries I've shipped in:
US Healthcare — HIPAA-aware architectures, clinical data pipelines, AI-assisted workflows
Airlines — operational systems, real-time data processing, reliability-critical infrastructure
Payments — high-throughput transaction systems, fraud detection, compliance-aware design
IT Infrastructure — enterprise tooling, data migrations, infrastructure modernization, observability
These aren't side projects. These are production systems handling real data, real users, real consequences.
Who I work best with:
Startups and SaaS teams who need someone to own the technical vision end-to-end — architecture to deployment — without needing a 6-month timeline and a committee. Growth-stage companies integrating AI into existing products. Enterprises building AI divisions, migrating data at scale, or modernizing legacy infrastructure where getting the architecture right from day one is non-negotiable.
If you need one person who has seen the full picture — from fine-tuning a domain-specific model to deploying the SaaS that runs on top of it — that's the work I do.
My background:
IIT Delhi (Master's, AI & Quantum Communication) + 10+ years across the full stack. I've worked as a pure enterprise architect, built and recruited entire AI engineering teams for clients, fine-tuned LLMs on domain-specific data, run complex data migrations, and shipped SaaS products from zero to production.
I think in products and systems, not just code. That means I'll tell you when a simpler solution is better, when you don't need a custom model, and when the real bottleneck isn't technical at all. I've sat on both sides of the table — as an engineer and as a product builder — and that changes how I approach every engagement.
Stack:
Python · Rust · Go · FastAPI · LangChain · LlamaIndex · React · Svelte · AWS · PostgreSQL · Elasticsearch · PyTorch · Docker · Kubernetes · Vector DBs · OpenAI / Anthropic APIs
How I work:
→ Clear scoping upfront — you'll know exactly what's being built before a line of code is written
→ Direct communication, no jargon, no vanishing mid-project
→ I flag problems and tradeoffs early, not after the deadline
→ Comfortable working async across US timezones
Ready to build? Send me a message describing what you're working on — even a rough idea — and I'll tell you honestly how I'd approach it and whether I'm the right fit.
Steps for completing your project
After purchasing the project, send requirements so Sagar can start the project.
Delivery time starts when Sagar receives requirements from you.
Sagar works on your project following the steps below.
Revisions may occur after the delivery date.
Share your idea
Describe what you want to build in plain English, the problem, the user, and any examples you like. We'll have a 30-minute kickoff call to align on the one core AI feature the MVP will demonstrate and agree on what "done" looks like.
I build, you review
I handle architecture, AI integration, backend, frontend, and deployment. You get regular progress updates and a working product on Day 14. One round of revisions is included before final handover with full documentation and source code.