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Many businesses want to build powerful AI agents and LLM applications, but they struggle to connect AI systems with private data, APIs, databases, and internal tools securely. Without a reliable connection layer, AI models cannot access real-time information, automate workflows, or interact with business systems effectively.
I build custom Model Context Protocol (MCP) servers that connect your data sources, APIs, databases, and AI tools into a secure, scalable environment. Your MCP server enables AI agents to retrieve information, execute actions, and communicate with your systems through structured tools and resources.
I use advanced technologies including TypeScript, Node.js, Python, MCP SDK, FastAPI, Express.js, Pydantic, PostgreSQL, Supabase, MongoDB, Redis, LangChain, LlamaIndex, OpenAI API, Anthropic Claude API, Google Gemini API, Docker, Docker Compose, Postman, GitHub Actions, AWS, Azure, Google Cloud, and DigitalOcean.
My services include MCP architecture design, API integration, database connectivity, authentication, security validation, testing, deployment, and monitoring using tools like Langfuse, Helicone, and Sentry. I help businesses create production-ready AI agents, RAG applications, SaaS platforms, and automation systems connected to the data and tools they need.
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
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DecisionOS — The Operating System for Organizational Intelligence
DecisionOS is a modern enterprise platform designed to help teams capture, analyse, approve, and remember every important business decision.
Instead of losing context across meetings, messages, and documents, teams can bring everything into one structured workspace—discussions, evidence, alternatives, risks, votes, approvals, and outcomes.
The working principle is simple: teams create a decision, add context and supporting evidence, compare possible options, identify risks, gather feedback, and complete a formal approval process. After the decision is made, DecisionOS tracks the result, records lessons learned, and preserves the full history for future teams.
The product was designed in Flowstep AI as a complete decision lifecycle experience, with AI-powered summaries, risk analysis, decision health, dependency mapping, voting, timelines, outcome reviews, and searchable organizational memory.
Think of it as GitHub for business decisions.
don't forget to include your flowstep link!
The biggest mistake businesses make with AI come and learn.
They think they need more AI tools.
They don't.
What they really need is one AI solution that solves one expensive problem.
I've seen businesses pay for:
1. ChatGPT Plus
2. Claude
3. Gemini
4. Cursor
5. Multiple automation platforms
Yet their teams still spend hours every week on repetitive work.
Why?
Because buying AI tools isn't the same as building an AI workflow.
The businesses getting the best results aren't using the most tools.
They're asking better questions.
Instead of:
❌ "Which AI tool should we buy?"
They ask:
✅ "Which task costs us the most time every week?"
That's where AI creates real ROI.
Whether it's lead qualification, customer support, document processing, internal approvals, or reporting, solving one bottleneck often delivers more value than adding five new AI subscriptions.
That's how I approach every AI project:
Start with the business problem.
Then build the AI solution.
I'm curious...
What's one repetitive task in your business that you'd automate tomorrow if you could?
I'd love to hear how others are thinking about AI adoption.
#AI #Automation #BusinessAutomation #AIEngineering
I like your thoughts. In which domain are you building a product?
Rocky, the Watchmaker
A cinematic tribute piece inspired by Rocky, the alien engineer from Project Hail Mary. I imagined Rocky’s problem-solving mind applied to something delicate and human: a Swiss tourbillon movement, rendered in stone-textured, alien anatomy.
Fully AI-generated, 46 seconds, closing with a full diagnostic scan sequence built from custom technical-overlay prompting (no template scan effects, no stock VFX). Includes a short workflow breakdown showing how the piece was built, start to finish.
This project pushed multi-shot creature consistency, material physics on organic-vs-mechanical surfaces, and a from-scratch diagnostic HUD language, all without traditional 3D or CGI tools.
I have nothing more to say. All I can say is, "Amazing!" 😛