AI agents are taking real actions with real consequences.Nobody is keeping score.
The AI industry is in the middle of a structural transition. Agents are moving from sandboxes to production systems that handle customer data, execute business logic, and make consequential decisions. The models are ready. The infrastructure to prove what they did is not.
Observability tools tell you a system is healthy. Memory layers make agents persistent. Runtimes make agents capable. But none of them answer the question that matters when something goes wrong, costs spike, or an auditor calls: what happened, what did it cost, and can you prove it?
Interstrata exists to answer that question. We are building the accountability layer for the agentic era.
Accountability is infrastructure, not an afterthought.
The teams that successfully run agents in production treat accountability the same way they treat authentication — as something that exists before the first action is taken, not something bolted on after an incident. The accountability layer is as fundamental as the model itself.
Evidence should be verifiable, not anecdotal.
When an agent makes a consequential decision, there should be a tamper-evident record linking that decision to the evidence it was based on, the confidence level of the extraction, the cost it incurred, and whether a human approved it. "I think someone said" is not a provenance chain.
Custody is a choice, not a default.
Who can decrypt your agent's memory should be an explicit decision with understood tradeoffs — not a line buried in a terms of service. We build three custody profiles because the right answer depends on your threat model, not ours.
Outputs should be sendable without rewriting.
An incident binder that needs to be rewritten before sharing with leadership is a draft, not a product. An accountability report that requires manual assembly is a process, not infrastructure. The first output should be good enough to forward.
Governance follows accountability, not the other way around.
We don't lead with compliance frameworks or regulatory checklists. We lead with operational value: what did your agents do, and was it worth it? The governance narrative develops naturally once teams have evidence, receipts, and case studies. Accountability creates the foundation that makes governance possible.
Not a memory API.
Mem0 and Zep solve agent recall. We sit across them as the system-of-record.
Not an agent runtime.
Letta and LangGraph build and run agents. We work with whatever runtime you choose.
Not an observability dashboard.
75+ companies show you metrics. We show you decisions, costs, and evidence.
Not a GRC platform.
ServiceNow and IBM own enterprise compliance. We build operational accountability that governance follows.
The agentic era needs an evidence trail. We're building it.
If you're running agents in production and can't answer what they did last Tuesday — we should talk.