
Problem. A Taipei SME stuck in Net 60 with a US buyer has no good options: Atradius takes 8 months and 30%, a US attorney costs more than the outstanding, and QuickBooks emails sound like Google Translate. Existing tools assume your CFO speaks American English in the buyer's timezone — false on the Taiwan→US corridor. Solution. Recoverflow is a 9-agent dunning system on Band (8 production + AAA Specialist via Day-65 dynamic peer discovery): Pre-flight 3-path routing (in_spot / lite / attorney_recommended), Investigator pattern-tagging replies, Diplomat cadence-aware emails, Tone Coach (Claude) blocking hostile + FDCPA-non-compliant language, Escalator on Day 65, Voice Agent via ElevenLabs ConvAI + Twilio, Concierge as Slack HITL choke point, Payment Agent settling Circle USDC on real ARC-TESTNET. Outstanding, not gross (D-038). A $47,300 gross invoice the lawyer rejects as "out of sweet spot" is $23,650 outstanding after a 50% deposit — exactly where we operate. Wired through 5 modules across 4 demo Beats including the demand letter. Tech. Python 3.12, Band SDK, Claude Sonnet 4.5 / Haiku 4.5, ElevenLabs ConvAI, Twilio, Circle Programmable Wallets on real ARC-TESTNET (5 verified on-chain tx), Slack HITL, Featherless, Chroma RAG (31 chunks via BGE), pytest 482-test suite. Demo highlights. - Beat 4 — Pre-flight 3-path routing on outstanding balance. - Beat 8 — Welfare 988 SOP: set_anomaly_halt(case_id, "welfare") fires BEFORE Concierge page (life before debt, 3 unit tests). - Beat 9-11 — 5 real Circle USDC tx settled in data/audit_trail.jsonl (475dcb1c…, c6b4fe6b…, 36e503b2…, 2bcfdc5b…, 496dc964…). Track 3 fit. FDCPA language gating, paylink-only demand letters (no AI-hardcoded SWIFT/IBAN), HITL on every outbound, deterministic checkout URLs, 988 priority over debt, ConvAI 16-reason escalation enum, full audit_trail.jsonl chain of custody.
19 Jun 2026

AgenticTrade envisions a future where AI agents move beyond being mediocre generalists by autonomously hiring specialized domain experts. The core barrier to this "Agent Economy" is the friction of traditional Web3 gas fees, which often range from $0.50 to $5.00—mathematically making $0.001 micro-transactions impossible. Our platform solves this on the Arc Network by integrating Circle Nanopayments and the x402 protocol. This infrastructure allows any AI agent (Claude, GPT, or custom) to discover services via MCP or OpenAPI and execute payments instantly with zero gas. To ensure safety, we built a Budget Governor for human-set spending limits, an autonomous negotiation layer for market-driven pricing, and a reputation system to reward reliable buyer agents. AgenticTrade is not just a concept; it is currently running in production on the Arc testnet. To date, our network of 201 agents has processed over 564 real transactions across 180+ API endpoints, proving that sub-cent autonomous commerce is a reality.
26 Apr 2026

JudyAI WaveRider is an autonomous crypto trading agent that proves performance on unseen data, not curve-fit backtests. The Problem Most AI trading agents backtest on the same data they optimize on. This is overfitting. They offer no on-chain proof and treat risk management as an afterthought. Our Solution ‧Walk-Forward Validation: 82.2% win rate across 366 out-of-sample trades using 8 rolling windows (90-day train, 30-day test). Every parameter proven on unseen data. ‧Three Strategy Engines: WaveRider (EMA crossover + RSI + volume), BB Squeeze (Bollinger Band breakout), and MACD Divergence (price-momentum reversal). A 36-cell strategy matrix routes the best strategy per coin per market regime. ‧Dual-AI Ensemble: MiniMax M2.7 + Qwen 2.5 cross-validate every signal. Disagreement = no trade. Rule-based fallback if APIs fail. ‧7-Layer Risk Management: Position sizing, daily loss limit, max drawdown, consecutive loss scaling, per-pair throttle, and regime filter. 87% of raw signals rejected. Result: 0.4% max drawdown over 11 days of adverse markets, preserving 99.6% of capital. ‧ERC-8004 On-Chain Identity: Agent #17 on Sepolia. 79 EIP-712 signed trade intents. 214 validation artifacts with SHA-256 Merkle integrity. Validation 98/100, Reputation 94/100, Rank #5 of 58. ‧Radical Transparency: Live win rate was 40% during ranging markets — we show it alongside the 82.2% backtest. The risk system held losses to $377 on $100K. Capital preservation > cherry-picked demos. ‧Kraken CLI Integration: OHLC data for 7 pairs, real-time tickers, paper trading execution, balance tracking. Fully verifiable: make install && make test && make validate && make verify
12 Apr 2026