📡 Social
End-to-end AI content operation: system signals → AI drafts (posts, replies, video scripts with shot lists) → quality-filtered human approval → scheduled publish, with engagement tracked back into the loop.
AI systems that Research, Decide, & Act. 24/7
Four AI systems share one discipline: signal → track → resolve → learn. Each grades its own calls against live market data — and earns (or loses) trust from its measured record, not from vibes.
Reads macro catalysts, calls sector impact and specific tickers, then scores every signal against what the market actually did. Public dashboard, full methodology.
Multi-agent analyst that routes work to whichever strategy is measurably hottest — and automatically benches its own underperformers.
Sifts millions of DEX trades for organic flow anomalies; copycat tokens and wash trading are filtered before a human ever looks.
Grades whether AI macro reasoning beats crowd-priced odds — every evaluation recorded and settled at real market resolution.
A three-stage Claude reasoning pipeline scans macro catalysts, predicts sector impact, and surfaces ranked trade ideas — then scores every outcome against live market data and feeds it back into the prompt, so accuracy compounds over time. Every call, win or lose, lands on a public scoreboard with the methodology disclosed. Runs 24/7 on a private server and pushes alerts straight to Discord — the research a desk pays an analyst for, on autopilot.
View Tool →Market alerts feed an AI content engine that drafts platform-specific posts; a keyword-discovery bot crafts brand-voice replies. The system tracks engagement and reallocates toward what performs — learning your voice and audience as it runs. You approve, it ships. Research becomes distribution, no marketing team required.
View Tool →
Web3Fuel started with a simple premise: most teams still pay people to do work an AI system could run end to end — the research, the drafting, the monitoring, the follow-up — if someone actually built it for them. So I built it: a News Scanner, a Social Engine, and a reply assistant that do exactly that. The sharper question they led to: what does it actually take to ship production AI systems a team would trust enough to put in front of real money?
The answer is leverage, not replacement. Claude reasoning pipelines do the heavy lift, and a feedback loop scores every prediction and feeds it into the next run — so the systems sharpen themselves instead of going stale. It all runs on private infrastructure I control: the News Scanner surfacing trade ideas with every outcome scored on a public scoreboard, the Social Engine turning those signals into platform-specific drafts, the reply assistant crafting brand-voice responses. A human approves at every step; the system does the rest. Research, marketing, and operations become one continuous pipeline.
The plumbing handles the predictable so the operator can spend time on the part that actually requires judgment. Once that works, creativity becomes the ceiling — the only question left is what to build next.
Whether you need AI-powered trading systems, marketing automation, analyst workflow tools, or just want to connect, reach out to discuss how we can collaborate.