Agentic Fabriq

Product & Competitive Intelligence

Gives enterprises a single control plane to permission, monitor, and audit every AI agent.

Company Overview

Builds the identity, governance, and visibility layer for AI agents. Sits in the middle of every agent's calls, managing both agent and user identity, handling token exchange, enforcing least-privilege access, and logging everything for audit and compliance. Positioned as 'Okta for Agents.'

Competitive Advantage & Moat

Product Roadmap & Public Announcements

TypeScript and Python SDKs live. Centralized agent registry with per-agent/per-user permissioning. OAuth2/JWT token management. Real-time audit logging. SSO integration, role-based access controls, instant revocation. Demo available with OpenWebUI integration. Website has pricing page and feature descriptions.

Signals & Private Analysis

'Okta for Agents' positioning signals intent to become default identity layer for agentic AI. Guardrails market projected $0.7B in 2024 to $109B by 2034. Nobody has agreed on what 'OAuth for agents' means yet, giving Agentic Fabriq a window to define the standard.

Product Roadmap Priorities

Agent Behavioral Anomaly Detection
Improving
Risk Reduction
IT-Security

ML-powered anomaly detection that monitors every AI agent action in real time, flagging and blocking suspicious or out-of-policy behavior before damage occurs.

In Plain English

It's like a security camera that watches every AI agent in your company and sounds the alarm the instant one starts doing something it shouldn't.

Analogy

It's like giving every AI agent in your company a parole officer who's read every rule book and never sleeps.

Adaptive Access Policy Learning
Improving
Operational Efficiency
Engineering

ML-assisted automatic generation and continuous refinement of least-privilege access policies for AI agents based on observed usage patterns.

In Plain English

It figures out exactly what permissions each AI agent actually needs by watching what it does, then locks everything else down automatically.

Analogy

It's like a smart thermostat for permissions—it learns exactly how much access each agent needs and automatically dials everything else down.

Integration Risk Prediction
Improving
Decision Quality
Strategy

ML-powered risk scoring that predicts the security and compliance impact of connecting a new AI agent to an enterprise tool before the integration goes live.

In Plain English

Before you plug a new AI agent into Salesforce or Slack, it tells you exactly how risky that connection is and what could go wrong.

Analogy

It's like a credit score for AI agent integrations—before you approve the connection, you already know if it's trustworthy or trouble.

Company Overview

Key Team Members

  • Paulina Xu, Co-Founder & CEO
  • Matthew Xu, Co-Founder & CTO

Paulina and Matthew met at MIT admit weekend and have been friends since. They dropped out before their second year to build Agentic Fabriq. Paulina was studying AI + Physics and doing CS/ML research at MIT Kavli Institute, MIT Haystack Observatory, and INAF Padua. Matthew dropped out of MIT at 19. They understand how autonomous agents reason, authenticate, and fail at a level that incumbents retrofitting human IAM systems fundamentally lack.

Funding History

  • 2025 | Paulina Xu and Matthew Xu co-found Agentic Fabriq.
  • 2026 | Accepted into Y Combinator W26 batch.
  • 2026 | Product live with TypeScript/Python SDKs, VentureBeat coverage.

Competitors

  • Enterprise IAM: Okta/Auth0, Microsoft Entra ID.
  • Agent Auth Startups: Composio, Arcade, Nango.
  • Enterprise Integration: Merge, WorkOS.
  • Emerging: Permit.io, Indent, various AI firewall startups.