We started deploying AI agents into production workflows earlier this year and almost immediately ran into the same uncomfortable realisation that I suspect a lot of teams are quietly sitting with right now, we had no clean answer to the question of what our agents were actually allowed to do, on whose behalf, and whether we could prove it after the fact. Our existing identity infrastructure was built entirely around human users. Agents were an afterthought at best, a blind spot at worst.
Agentic Fabriq drops into your existing stack via SDK and API without requiring you to redesign your infrastructure, and that integration story is genuinely the first thing that won us over. We didn't want to rip out what was working for human identity just to handle agents. It works with any agent framework or custom build, LangChain, CrewAI, AutoGen, OpenAI Agents, and more which meant we could instrument our existing agents without rewriting them around a new platform's conventions.
The core model is clean teams add a TypeScript or Python SDK, register their agents and tool connections, and set per-role policies so agents act only with the permissions of the user who invoked them. That user-scoped delegation model is exactly the right mental framework for the problem. An agent acting on behalf of a specific user should be constrained to that user's permissions not elevated, not ambient, not inherited from whoever deployed it. Fabriq enforces that boundary on every call, which is the kind of least-privilege thinking that human identity tooling figured out a decade ago but the agent world is only now catching up to.
Agents never store sensitive secrets, Fabriq handles all tokens, credentials, and delegated access securely, integrating with existing identity providers. That detail alone removed a category of security concern we had been managing manually and inconsistently across different agent deployments.
The audit log capability is where it pays back most visibly from a compliance standpoint. Every action every agent takes is logged, searchable, signed, and centralised. Before Fabriq, reconstructing what an agent had done during a specific workflow required piecing together logs from four different systems. Now there is one place to look, and the trail is complete and tamper-evident. For anyone in a regulated environment or preparing for a security audit, that shift from "we think the agent did this" to "here is a signed record of exactly what it did" is not a marginal improvement, it changes the compliance conversation entirely.
Admins get SSO integration, role-based access controls, and instant revocation which means the operational model for managing agents starts to look like the operational model for managing human users, which is what you want when you're trying to govern both within the same security programme.
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Being honest about the downsides matters here because Agentic Fabriq is a very early company currently booking demos and running private pilots rather than broad self-serve availability and the experience reflects that stage.
The platform is thin in places that will matter more as deployments scale. Policy configuration is functional but the tooling for managing complex, multi-team agent environments with layered permissions and conditional access rules is not yet where it needs to be for larger organisations. What works cleanly for a focused pilot with a handful of agents gets harder to reason about at scale.
Observability depth is the other gap. The audit logs do their job — they capture what happened — but the analytics layer on top of those logs is still basic. Understanding patterns across agent behaviour, spotting anomalies in how agents are using their permissions, or building compliance reports that go beyond raw log exports all require more manual work than they should. This is where a more mature product would be pulling its weight and Fabriq isn't there yet.
Documentation is improving but still has gaps, particularly around less common framework integrations and edge cases in the permissioning model. When something behaves unexpectedly the path to resolution relies heavily on direct access to the founding team — which is responsive and genuinely helpful right now, but isn't a support model that scales as the customer base grows.
Pricing transparency is also limited at this stage. Without published tiers it's hard to plan budget confidently or benchmark value against alternatives, which adds friction for procurement conversations internally.
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