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Retail Knowledge Graph
In this project, we built a semantic knowledge graph tailored to the retail industry. The pipeline involved developing AI agents to transform heterogeneous data into standardized formats. Ontologies were created to represent domain knowledge accurately. Using Gemini models and LangChain, user queries were converted into Cypher queries to retrieve insights from a Neo4j database. We utilized an MCP server for orchestration and LangSmith for secure login and audit trails. This system enhances complex data exploration for non-technical users.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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Everyone's on Day 7 of Config Makeathon. I'm on Day 0 😅
Asked Figma's AI agent to generate a character for my project. I think it understood the brief a little too well.
I think it captured my current mood perfectly 😐🤖
More soon.
lol there's still time!
KILLBEROS
Risk-First (Educational · Fully simulated)
Measure the danger before the gain.
Most small investors don't lose for lack of ideas they lose for lack of risk discipline: they over-trade, double a losing position, and over-size out of fear or greed. KILLBEROS gives anyone the risk discipline of an investment fund, on a modest $1,000 budget ($500 in play, €500 kept untouchable). 100% educational, fully simulated no real money, no broker, no orders ever placed.
• Risk Planner — real position sizing on any instrument: size, risk, reward-to-risk, computed live.
• The 7 Gates — every trade must pass 7 risk checks; break one (e.g. a reward:risk below 2:1) and it's BLOCKED. The danger is measured first.
• Market Regime — live market "weather" (real Fear & Greed + real crypto prices) decides which strategies are even allowed to play.
• AI Advisor + a mistake "pokédex" — so the same error never repeats.
• Journal — log real trades, see your true edge: win rate, expectancy, drawdown (real backend, not a mockup).
Innovative Workflow)
KILLBEROS was designed and built in Figma Make, then reviewed live and iterated, version after version (V2 -> V43), by an AI agent "Cowork Brain" working through Figma's MCP.
But the real innovation is HOWdecisions were made: every significant choice (doctrine, a risk gate, a strategy, the UI) was debated by a standing panel of 11 AI "voices" that the agent embodies in one head — 5 trader profiles (macro, chartist, a risk/Aladdin voice with veto power, a short-term "gambler", and a long-term allocator) + 5 engineer profiles (backend, UX, API, security, data).
Risk speaks first, the angles are confronted, a decision is made, and the dissenting view is written down. (Junior) signs off on anything irreversible. It's a small AI team with a real method not a single prompt. Build-in-public: every version and decision is journaled.
And After :
KILLBEROS is the educational tip of the iceberg. Behind it, a far more powerful engine the full GambleRisk is in the works: the same risk-first doctrine, but it paper-trades itself for weeks to PROVE its edge, market regime by market regime, before anything else. Still risk-first, still discipline-before-gain. This is just the beginning.
Team : Junior Odika (+ Cowork Brain, AI collaborator).
URL :
Hey Junior, don't forget to share your project on Instagram, X, or LinkedIn with #ConfigMakeathon and @figma to complete your submission! 😊
Check the guidelines and get that in before the deadline!
Created AI generated product photography for a luxury footwear brand. Focused on premium lighting, realistic textures, and high converting visuals designed for e commerce and marketing campaigns.
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