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NodeLoom

NodeLoom is a runtime control plane that discovers, instruments, and monitors AI agents across cloud services, code repositories, and custom frameworks, providing a continuously updated inventory with risk scores.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Organizations are rapidly deploying AI agents across cloud services, code repositories, and custom frameworks without visibility, governance, or auditability, leading to unmanaged risk, silent behavioral drift, and compliance challenges.

Solution

NodeLoom provides a runtime control plane that discovers, instruments, and monitors AI agents throughout an enterprise’s infrastructure. It automatically scans cloud providers, Anthropic Managed Agents, GitHub repositories, MCP gateways, and eBPF probes to build a continuously updated inventory with risk scores. Lightweight SDKs for Python, TypeScript, Java, and Go add structured tracing, token‑usage tracking, and non‑blocking telemetry to agents built with LangChain, CrewAI, Anthropic, or custom code. The platform detects behavioral drift, enforces configurable guardrails, and runs incident‑response playbooks that can quarantine or roll back agents. Cryptographic audit trails and one‑click compliance reports (SOC 2, HIPAA, GDPR, ISO 42001, NIST AI RMF) give auditors verifiable evidence of control and data handling.

Target Audience

Primary customers are enterprise AI engineering teams, DevOps and security operations groups, and compliance officers in regulated industries such as finance, healthcare, insurance, and legal services.

Features

  • Automated multi‑channel agent discovery across AWS Bedrock, Azure AI, GCP Vertex, Anthropic Managed Agents, GitHub CI/CD, MCP gateways, and kernel‑level eBPF probes with hourly risk scoring
  • Language‑agnostic observability SDKs (Python, TypeScript, Java, Go) providing traces, spans, token cost tracking, and batched, retry‑safe telemetry
  • Built‑in handlers for LangChain, CrewAI, and Anthropic agents plus support for any custom framework
  • Real‑time execution monitoring, behavioral anomaly detection, and configurable drift alerts
  • Guardrail engine with keyword/regex filters, semantic embeddings, and LLM‑as‑judge evaluation
  • Incident response playbooks that auto‑quarantine, notify, and rollback non‑compliant agents
  • Compliance dashboard and automated report generation for major standards, plus cryptographic hash‑chain audit logs
  • Export of audit data to SIEM platforms (Splunk, Datadog, Elasticsearch) and webhook integrations
This profile is AI-generated and may contain inaccuracies.