You will get an Agentic AI search engine that understands natural language queries
Project details
Why Settle for "Dumb" Search?
Traditional search fails to understand user intent. Even modern vector search can only find what's semantically similar—it can't reason.
An Agentic Search Engine is different. It uses a reasoning engine (like LangGraph) to:
Understand a complex, natural-language query.
Break it down into a logical multi-step plan.
Execute that plan by intelligently querying your data (using vector search, text search, and filtering).
This means your users get relevant, accurate answers to the questions they actually have, not just a list of blue links.
Why Work With Me?
You're hiring an expert, not a hobbyist. I am a senior software engineer with 15+ years of experience in JavaScript (NestJS/TypeScript) and cloud architecture.
You get a production-ready solution. This isn't just a Python script. I provide a full-stack, scalable application with a NestJS backend, React frontend, and robust database (MongoDB + Qdrant).
You get the builder. I built the open-source CodiesVibe.com project this is based on. I know every line of code and can customize it for any use case.
Traditional search fails to understand user intent. Even modern vector search can only find what's semantically similar—it can't reason.
An Agentic Search Engine is different. It uses a reasoning engine (like LangGraph) to:
Understand a complex, natural-language query.
Break it down into a logical multi-step plan.
Execute that plan by intelligently querying your data (using vector search, text search, and filtering).
This means your users get relevant, accurate answers to the questions they actually have, not just a list of blue links.
Why Work With Me?
You're hiring an expert, not a hobbyist. I am a senior software engineer with 15+ years of experience in JavaScript (NestJS/TypeScript) and cloud architecture.
You get a production-ready solution. This isn't just a Python script. I provide a full-stack, scalable application with a NestJS backend, React frontend, and robust database (MongoDB + Qdrant).
You get the builder. I built the open-source CodiesVibe.com project this is based on. I know every line of code and can customize it for any use case.
AI Algorithms
Large Language ModelAI Applications
AI Chatbot, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Text RecognitionAI Models
GPT-4What's included
| Service Tiers |
Starter
$500
|
Standard
$1,500
|
Advanced
$4,000
|
|---|---|---|---|
| Delivery Time | 1 day | 10 days | 30 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
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AB
Andre B.
Dec 13, 2021
4 Devs with Azure Developer Associate Certification
AM
Alina M.
Mar 1, 2021
Senior C#/.NET Developer is Needed
Thank you for completing our initial task!
About Foyzul
JavaScript and C# expert having 12+ years of experience
Melbourne, Australia - 12:09 pm local time
Steps for completing your project
After purchasing the project, send requirements so Foyzul can start the project.
Delivery time starts when Foyzul receives requirements from you.
Foyzul works on your project following the steps below.
Revisions may occur after the delivery date.
Phase 1: Kick-off & Initial Setup
We'll start with a brief call to align on your goals. For Starter: I will deliver the open-source codebase, documentation, and schedule our 1-on-1 walkthrough. For Standard/Advanced: We will review your dataset and finalize the integration plan.
Phase 2: [Standard/Advanced] Data Integration
(For Standard & Advanced Tiers) I will connect your data source to the search pipeline, configure the data schema, and set up the Qdrant vector database to index your data.