You will get Build Hybrid Search with BM25 + Vector Search for Accurate AI Retrieval
Project details
I will design and implement a production-ready hybrid search system that combines BM25 (sparse keyword search) with dense vector embeddings, fused using Reciprocal Rank Fusion (RRF) for significantly better relevance and recall.
This solution is ideal for:
- Search engines
- LLM-powered applications
- RAG (Retrieval-Augmented Generation) pipelines
-Large document indexing and retrieval
What I’ll Deliver
- End-to-end data ingestion and preprocessing pipeline
- Sparse indexing using BM25 (e.g., Solr, Elasticsearch, OpenSearch)
- Dense vector indexing using modern embedding models (OpenAI / Hugging Face)
- Hybrid retrieval layer with BM25 + vector search
- Score fusion using RRF (or weighted normalization if preferred)
- LLM-ready retriever optimized for RAG use cases
- Clear documentation and handoff for easy maintenance
This solution is ideal for:
- Search engines
- LLM-powered applications
- RAG (Retrieval-Augmented Generation) pipelines
-Large document indexing and retrieval
What I’ll Deliver
- End-to-end data ingestion and preprocessing pipeline
- Sparse indexing using BM25 (e.g., Solr, Elasticsearch, OpenSearch)
- Dense vector indexing using modern embedding models (OpenAI / Hugging Face)
- Hybrid retrieval layer with BM25 + vector search
- Score fusion using RRF (or weighted normalization if preferred)
- LLM-ready retriever optimized for RAG use cases
- Clear documentation and handoff for easy maintenance
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Natural Language Generation, Natural Language Understanding, Text RecognitionAI Models
BERT, ChatGPT, LLaMAWhat's included $15,000
These options are included with the project scope.
$15,000
- Delivery Time 60 days
- Number of Revisions 3
- AI Model Integration
- Batch Normalization
- Database Integration
- Detailed Code Comments
- MLOps
- Model Deployment
- Model Documentation
- Model Monitoring
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- NLP Tokenization
- Prompt Engineering
- Setup File
- Source Code
Optional add-ons
You can add these on the next page.
Fast 30 Days Delivery
+$5,000
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KC
Ken C.
Feb 1, 2026
Technical Consultation: Large-Scale Text Retrieval System Architecture Review (1-2 Hours, Paid)
About Sohail
Principal Software Engineer | Search, Recommendation & AI/ML Platforms
Toronto, Canada - 8:46 pm local time
Steps for completing your project
After purchasing the project, send requirements so Sohail can start the project.
Delivery time starts when Sohail receives requirements from you.
Sohail works on your project following the steps below.
Revisions may occur after the delivery date.
Steps I’ll Take to Get the Project Done
Requirements & Use Case Review Data Ingestion & Preprocessing Sparse Index Setup (BM25) Dense Vector Indexing Hybrid Search & Score Fusion LLM & RAG Integration (If Required) Testing & Relevance Tuning Documentation & Handoff