You will get a scoped build plan, estimate, and clickable prototype for your app idea
Project details
Most app projects fail before a line of code is written, because nobody pinned down what to build. This project fixes that in days, not weeks. Send me your idea in plain words and I will return a build plan a developer can actually execute: prioritized user stories with acceptance criteria, a sprint-based cost and time estimate, and, on higher tiers, a clickable prototype of the key screens plus a build-ready pack for your dev team or AI coding tools. I run an AI product studio and operate more than a dozen production AI systems; scoping is the discipline I apply to my own products before I build them. You get a document you can hand to any developer, agency, or investor, and you stop paying for discovery meetings that go nowhere.
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
AI-Generated Code, Conversational AI, Natural Language GenerationAI Tools
Azure OpenAIAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$99
|
Standard
$299
|
Advanced
$599
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 2 |
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 | - |
About Mahesh
AI App Developer | LLM Agents, RAG, Chatbots | Next.js, Node, Azure
Prosper, United States - 8:23 pm local time
What I can do for you:
- LLM apps and agents: OpenAI, Azure OpenAI, Anthropic Claude, tool calling, structured output, evaluations and guardrails
- RAG done right: chunking, embeddings, pgvector, hybrid search, citation-grounded answers that hold up in regulated industries
- Full-stack delivery: Next.js, React, TypeScript, Node.js, Python, PostgreSQL, deployed on Azure or Vercel with CI/CD, monitoring, and cost control
- Integrations: Microsoft 365 and Graph API, CRMs, internal APIs, email and document workflows
Recent work includes an AI answer-engine monitoring platform for pharma brand teams, an AI workforce analytics product used by companies and government agencies, a discovery agent that turns client conversations into scoped and estimated project plans, and forecasting agents for a major auto-finance company.
I work fast, communicate clearly, and treat your budget like my own. If you need someone who can take an AI feature from idea to production without hand-holding, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Mahesh can start the project.
Delivery time starts when Mahesh receives requirements from you.
Mahesh works on your project following the steps below.
Revisions may occur after the delivery date.
Review your brief and ask focused questions
I read everything you send and come back within one day with clarifying questions on goals, users, and constraints.
Scope the build
I turn your answers into prioritized user stories with acceptance criteria and a sprint-based effort estimate you can put in front of any developer or agency.