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Hey Contra!
Excited to finally be here and connect with builders, founders, and innovators from around the world.
I'm Osman, an AI Engineer specializing in AI Agents, LLM Applications, Automation Systems, and Full-Stack Development. Over the past 3+ years, I've helped businesses transform ideas into intelligent products using OpenAI, Gemini, LangChain, LangGraph, FastAPI, Django, and modern cloud technologies.
Some of the solutions I've built include:
• AI Agents and Multi-Agent Systems
• RAG Applications with Private Knowledge Bases
• AI-Powered SaaS Products
• Automation Workflows with n8n, Zapier, and Make
• Voice AI Agents with Twilio and ElevenLabs
• Custom Chatbots and Internal AI Tools
• Data Automation and Web Scraping Systems
I enjoy solving complex problems and building products that create real business value—not just demos.
Looking forward to connecting with founders, startups, agencies, and teams working on exciting AI projects.
If you're building something ambitious with AI, let's talk.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Always dreamed of being a freelance designer & dev. Pretty amazing to be finally living those dreams! Thanks @Contra HQ @Ben Huffman
AI Assistant Using Your Business Knowledge Base — RAG on Your Documents
THE PROBLEM
Q&A bots break down when knowledge lives in documents: a 100-page manual has no "questions" to match, it can't fit into a prompt, and generic chatbots hallucinate instead of admitting what they don't know.
THE SOLUTION
A RAG (Retrieval-Augmented Generation) knowledge base: documents are split into meaningful chunks, embedded into a vector index, and the assistant answers from the right sections — by meaning, not keywords.
Any format as-is: PDF, DOCX, TXT, Markdown — 100+ pages is fine
Answers grounded in YOUR documents — it says "I don't have that information" rather than inventing
Source references — every answer shows which document and section it came from
Runs on your infrastructure — documents never leave your control
One command to re-index after updating documents — documented, no programmer needed
LIVE DEMO
Ask it about my products, pricing, deployment and support — it answers from 6 real documents with sources:
https://kb-assistant-demo.dvc-ai.workers.dev
The 'I don't have that information' line is the part most RAG builds skip, and it's the one that matters. How do you set the cutoff? On mine, a fixed similarity threshold broke once I filtered results by user role. Scores shifted and it refused questions it could answer.
A closer look inside my Clause Check template.
Clause Check is a SaaS AI concept I designed to make reviewing and understanding contracts a little easier.
Here’s a look at more of the landing page, from the UI components and interactions to the small details that bring the design together.
