You will get Production-Ready Agentic RAG System with LangGraph
Top Rated
Project details
If you're building a SaaS or an internal tool, you don't just need a prompt; you need a state machine that handles errors, a vector database that actually finds the right data, and a frontend that doesn't lag. I use LangGraph to build logic that stays on track and Supabase to keep your data locked down.
𝐖𝐡𝐚𝐭 𝐈 𝐝𝐞𝐥𝐢𝐯𝐞𝐫
• Real Agents : Logic that plans and checks its own work, not just a chat window.
• Source-Locked RAG : If the info isn't in your docs, the AI says I don't know. No guessing.
• Fast SaaS : Next.js 16 code that is clean enough to hand off to your next lead dev.
If you want a quick wrapper, I'm not your guy. If you want a system that's ready for users, let’s talk.
𝐖𝐡𝐚𝐭 𝐈 𝐝𝐞𝐥𝐢𝐯𝐞𝐫
• Real Agents : Logic that plans and checks its own work, not just a chat window.
• Source-Locked RAG : If the info isn't in your docs, the AI says I don't know. No guessing.
• Fast SaaS : Next.js 16 code that is clean enough to hand off to your next lead dev.
If you want a quick wrapper, I'm not your guy. If you want a system that's ready for users, let’s talk.
Programming Languages
JavaScript, Python, TypeScriptCoding Expertise
Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$900
|
Standard
$2,800
|
Advanced
$6,500
|
|---|---|---|---|
| Delivery Time | 5 days | 14 days | 30 days |
Number of Revisions | 1 | 2 | 3 |
Number of Pages | 1 | 3 | 8 |
Design Customization | - | ||
Content Upload | - | - | |
Responsive Design | |||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Functional Page/Module
(+ 2 Days)
+$250Frequently asked questions
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GJ
Gautam J.
Aug 24, 2026
WhatsApp Chatbot Development with LLM Integration
Akshay is great to work with. He’s got good product and technology knowledge. He isn’t just a yes man, he pushes back on bad ideas with his own thoughts which I value greatly. I would recommend Akshay highly
TM
Trivikrama M.
Oct 23, 2025
Data Parsing and Transformation - Next.js (IMMEDIATE REQUIREMENT)
Great working with Akshay. He was extremely helpful at a time we need urgent work. Look forward to hiring him again!
JK
Jatinder K.
Sep 29, 2025
Next.js and Supabase Developer Needed for CRM Backend Logic Transfer
Exceptional talent
AC
Ashish C.
Aug 18, 2025
Backend Documentation & Architecture for Two Platform Ideas
Delivered everything on time and exactly as requested. Clear documentation and well-structured architecture diagrams made it easy for our team to move forward. Highly recommended!
AD
Ashok D.
Jun 29, 2025
Full-Stack Architect with Microsoft Technology Stack Expertise
About Akshay
Applied AI Engineer | Full-Stack
100%
Job Success
Gandhinagar, India - 8:08 am local time
Over the last 4+ years, I've built and maintained SaaS applications, dashboards, automation systems, APIs, and AI-powered products. I work across the full stack, from frontend and backend to databases, third-party integrations, cloud infrastructure, and AI systems.
I help existing products add capabilities such as AI agents, RAG, semantic search, AI automation, tool calling, and intelligent workflows without treating AI as a separate demo bolted onto the product.
My stack includes Next.js, TypeScript, Node.js, Python, PostgreSQL, Supabase, Redis, REST APIs, WebSockets, RAG, AI Agents, LLM Integration, Tool Calling, MCP, Vector Search, Semantic Search, LangGraph, Docker, AWS, Vercel, and CI/CD.
I'm comfortable joining an existing codebase, working with product and engineering teams, and taking ownership of features from 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 → 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 → 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻.
I value clean engineering, straightforward communication, and building AI features that actually solve business problems.
Your product already works. Let’s make it work smarter. ⭐⭐⭐
Steps for completing your project
After purchasing the project, send requirements so Akshay can start the project.
Delivery time starts when Akshay receives requirements from you.
Akshay works on your project following the steps below.
Revisions may occur after the delivery date.
Architecture Design & Data Schema
We define the System Graph (LangGraph) and Database schema. Before a single line of AI logic is written, we ensure the data flow and Security Rules (RLS) are architecturally sound to prevent future technical debt.
Vector Infrastructure & RAG Indexing
I set up your Vector Database (Pinecone/pgvector) and develop the ingestion pipeline. We implement semantic chunking and metadata filtering to ensure the AI retrieves the most relevant context with zero hallucinations.