AnChain.AI company primary sources — 2026-08-10

Company-split rationale in this pass

• The current AnChain.AI note was promoted from projects/ into companies/ because the practical dependency is not a neutral protocol surface.
• The live control surface sits with the named operator that authors risk scores, sanctions and fraud interpretation, graph-tracing workflow, Auto Report packaging, and MCP/API delivery for agentic AML and payment-screening workflows.

Primary-source snapshots

1) Main site / company framing

• URL: https://www.anchain.ai/
• Key excerpt:
  • The homepage calls AnChain.AI an AI-Powered Crypto Tracing & AML Platform spanning real-time crypto payment screening, agentic AML, and blockchain forensics.
  • It says the company is trusted by regulators, law firms, and payments teams, and frames itself as protecting the global financial system with AI-native fraud and compliance tooling.
  • It also describes an Intelligence AML API & MCP, AML Compliance Reporting, and Crypto Payment Screening, which makes the company boundary more useful than a product-only note.

2) Data / API / MCP page

• URL: https://www.anchain.ai/data
• Key excerpt:
  • The data page says AnChain.AI delivers low-latency REST APIs for machine-learning risk scores, graph-based entity clustering, sanctions screening, and transaction monitoring.
  • It claims roughly 100 ms latency on most endpoints, support for 41+ blockchains, 1B+ blockchain labels, and 99.99% uptime.
  • It explicitly says outputs are structured for LLMs, agentic AI, tool-calling, and MCP integration, and ties the platform to AML/KYC/KYB, sanctions, fraud detection, transaction monitoring, and compliant stablecoin / RWA / DeFi workflow.

3) OpenClaw integration / agent-workflow evidence

• URL: https://www.anchain.ai/blog/openclaw
• Key excerpt:
  • The OpenClaw tutorial presents AnChain.AI Data MCP as an always-on AML compliance officer layer for an AI agent.
  • It describes wallet-risk checks, pre-transaction screening, sanctions reasoning, and audit-trail generation through an agent using AnChain.AI’s MCP.
  • That is strong evidence that AnChain.AI is packaging operational compliance judgment for software and payment workflows, not only a human analyst dashboard.

4) Earlier source packet still worth preserving

• URL set: ../whitepapers/anchain-ai-primary-sources-2026-05-03.md
• Key excerpt:
  • The earlier capture preserves AnChain.AI’s CISO, x402, and case-study material around Auto Trace, Auto Report, machine-payment trust-layer framing, and programmable investigation workflow.
  • Those materials reinforce that the named operator packages screening, tracing, reporting, and compliance automation into one company-run shell.

Working conclusion

AnChain.AI clears the bar for a company/entity split because the useful question is not only what tracing API or MCP exists? but which named operator authors the risk labels, sanctions interpretation, pre-transfer decisions, trace workflow, report packaging, and AI-agent integration that downstream teams may start treating as compliance truth? That makes the company boundary analytically stronger than the old project note.