You will get Custom RAG System: Notion/PDFs/Doc, BM25 + Semantic Search, HyDE
Rising Talent

Rising Talent

Project details
Most RAG systems return vague, generic answers because they rely on basic vector search alone. I build systems that actually work by combining BM25 keyword retrieval, semantic search, and HyDE query enhancement to surface precise, contextually-rich answers from your documents.
I've built RAG pipelines ingesting thousands of documents with multi-provider LLM support (Claude, GPT-4, Gemini), reranking, vision enrichment for images, and built-in eval pipelines to measure and improve retrieval quality, not just ship and hope for the best.
You get source code, full documentation, and a system you actually understand and own.
I've built RAG pipelines ingesting thousands of documents with multi-provider LLM support (Claude, GPT-4, Gemini), reranking, vision enrichment for images, and built-in eval pipelines to measure and improve retrieval quality, not just ship and hope for the best.
You get source code, full documentation, and a system you actually understand and own.
AI Development Type
Knowledge RepresentationAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$299
|
Standard
$799
|
Advanced
$1,499
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$50Frequently asked questions
1 review
(1)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
ML
Mike L.
Mar 31, 2026
Openclaw Consultant Needed for Secure Executive Assistant Setup
About Bren
AI Automation, Agent & OpenClaw Specialist
Lisbon, Portugal - 1:15 pm local time
My background spans neural network research (published 2013), Web3 business consulting, and technical project management for an AI blockchain infrastructure company. That mix of research rigour, business context, and hands-on technical delivery is what I bring to every project.
Current focus: AI agent deployment on VPS and cloud (DigitalOcean, AWS, Oracle), Docker configuration, Telegram/Discord integrations, custom automation pipelines, and workflow systems. I run these in production myself meaning I've already learned how to solve the most important edge cases.
Available for fixed-price projects and ongoing retainer work.
Steps for completing your project
After purchasing the project, send requirements so Bren can start the project.
Delivery time starts when Bren receives requirements from you.
Bren works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Discovery & Data Audit
Review your data sources, assess volume and structure, confirm retrieval goals and success criteria.
Step 2: Ingestion & Chunking Pipeline
Build the ingest pipeline: connect to your sources, chunk intelligently, enrich with metadata.
