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AxonFlow

AxonFlow is a self‑hosted runtime control layer that intercepts every AI model or tool invocation to enforce real‑time policy decisions, approval workflows, and immutable audit records.

Amsterdam, NetherlandsFounded 2025450+ followers
Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Security and compliance teams often receive only basic audit logs that show what AI actions occurred, without context on why a request was allowed, blocked, paused, or required approval, making it difficult to meet regulations such as the EU AI Act, HIPAA, GDPR, RBI, or SEBI.

Solution

AxonFlow provides a self‑hosted runtime control layer that intercepts every model or tool invocation and enforces policy decisions in real time. SDKs for Python, TypeScript, Go, and Java let developers embed request‑level gating, approval workflows, and immutable decision records directly into their applications. The platform records not only the outcome of each action but also the exact policy version, rule matches, and any human overrides, creating a queryable audit trail that explains why a decision was made. Built‑in policy engine evaluates requests in sub‑10 ms, supporting deny‑by‑default controls, RBAC/ABAC, and custom dynamic rules, while also offering pre‑configured checks for PII, SQL injection, prompt injection, and media safety. Integration with the Model Context Protocol (MCP) secures data access to internal systems, and the system exports evidence to SIEMs and compliance reporting tools, enabling organizations to demonstrate governance and oversight without sacrificing performance.

Target Audience

Primary customers are platform engineering, security, and compliance teams in enterprises that deploy AI‑augmented workflows and need real‑time governance, auditability, and regulatory evidence.

Features

  • SDKs for Python, TypeScript, Go, and Java enabling seamless embedding of policy checks and approval gates
  • In‑memory policy engine with sub‑10 ms P95 evaluation and deny‑by‑default execution controls
  • Pre‑built safety policies (23+ PII types, SQL injection patterns, prompt injection, NSFW/violence/biometric/media) plus custom dynamic rule support
  • Step‑gate workflow governance with per‑step allow, block, or human‑in‑the‑loop decisions and retry‑aware idempotency keys
  • Model Context Protocol connectors for secure, policy‑enforced access to databases, SaaS APIs, and custom internal services
  • Immutable decision records that capture policy version, matched rules, risk level, and override options, searchable via API
  • Integrated observability: 80+ Prometheus metrics, Grafana dashboards, and SIEM export (Splunk, Datadog) for compliance reporting
  • Multi‑model routing across OpenAI, Anthropic, AWS Bedrock, and local LLMs
This profile is AI-generated and may contain inaccuracies.