Autonomous agents for trading signals, prediction market arb, weather arbitrage, content automation, and deep research. Local-first. Human-in-the-loop. No cloud. Compound intelligence, compounding daily.
No spam. Build updates and early access when we launch.
A 5-stage pipeline that runs every night, gets measurably smarter every cycle, and surfaces alpha you'd never find manually.
Market data, news feeds, X, HN, Reddit, weather APIs, prediction markets — all streaming in real-time.
17+ specialized agents research, score, classify, and debate findings using parallel reasoning pipelines.
Trading signals with VIX-conditional sizing, prediction market arb, weather arbitrage — all human-approved before action.
Hypothesis engine generates experiments. Eval agent benchmarks results. The system automatically incorporates what worked.
Research reports, content threads, newsletters, morning briefings — all queued for review and one-click publish.
Every decision optimizes for founder control, data sovereignty, and compounding intelligence — not cloud vendor margins.
Everything runs on your hardware. Your data never leaves your machine. No cloud dependency, no vendor lock-in. Zero API bills. You own every byte.
Agents propose, you approve. Nothing gets deployed, traded, or published without your explicit sign-off. Full governance, always. Circuit breakers on everything.
Built-in evaluation, hypothesis generation, and automated quality gates. The system gets measurably smarter every overnight run — the compound knowledge moat grows daily.
Every capability listed here is running in production on local hardware right now.
Research, content generation, evaluation, hypothesis generation, deal flow, prediction market scanning, weather arb, and morning briefing — all running every night on local models with parallel agent orchestration. The system resets, improves, and re-runs every 24 hours.
Momentum, mean reversion, and trend following strategies against live crypto data. VIX-conditional position sizing automatically tightens or relaxes risk bounds based on volatility regime.
Scans Polymarket, Kalshi, and Manifold for mispriced events. Cross-references news feeds and model consensus to identify exploitable discrepancies before the market corrects.
Identifies weather-sensitive prediction markets and commodity positions where model forecast divergence creates pricing inefficiencies. Runs NWP model ensemble comparisons.
Parallel agent debate framework where multiple models research the same question independently, then a coordinator synthesizes disagreements. Catches blind spots single-model analysis misses.
Built-in evaluation agent benchmarks every output across five quality dimensions. Hypothesis engine generates improvement experiments. Winning experiments get baked into the pipeline automatically.
Trend-aware content generation with quality gates. Research-to-thread formatting, newsletter compilation, and long-form article drafting. Human review before any publish.
9 Model Context Protocol tools exposing the system to any MCP-compatible client. Memory management, research triggers, signal queries, pipeline control — all accessible from Claude, Cursor, or custom UIs.
Scans Hacker News, Reddit, X, and market signals. Scores, classifies, and routes opportunities to a prioritized queue. Surfaces deal flow, competitor moves, and market shifts overnight.
Every layer is designed to make the next layer more powerful. The knowledge moat grows with every overnight cycle.
Real metrics, real failures, real progress. Every overnight run is logged. Every hypothesis is tracked. The system's self-improvement is visible.
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