Developers · A Glimpse of What's Next

Your teams.
Awareness-grade context.

The Agentic Awareness Layer is more than a security substrate. It's the platform your teams will build the next generation of enterprise AI experiences on.

AI Defendo ships today · Developer surface comes next
The Problem

AI is fragmented. Your data platforms weren't built for it.

Your SOC has its SIEM. Your SREs have observability. Your compliance team has audit tooling. None of them can answer questions about your AI agents' behavior, memory, delegation, or intent.

Building custom copilots on top of these tools means writing brittle glue for data that was never designed to reason about autonomous action.

Four Domains

The same awareness. Four different lenses.

One substrate. Four kinds of copilots your teams could build — each answering the questions their domain actually asks.

01 · SOC
Incident Response

Investigation copilots that reason across agents.

"Show me every agent action that touched the customer-PII datastore in the last 48 hours."

Analysts stop stitching evidence across tools. The copilot pulls signed verdicts, session trajectories, and delegation graphs — and produces a forensic narrative auditors can actually read.

Outcome — Faster incident scoping. Regulator-defensible narratives. No new pipelines to build.
02 · Platform
Agent Behavior

Reliability copilots that see agent drift.

"Anything unusual with the ticket-triage agent in the last week?"

SRE and platform teams get baselines per agent, per session, per principal. Drift surfaces before it becomes an incident — with root-cause hypotheses attached.

Outcome — Agent SLOs stop being lagging indicators. Drift becomes an observability signal.
03 · GRC
Regulatory

Compliance copilots with audit-grade evidence.

"Prove no AI agent processed EU-resident PII outside the approved data path this quarter."

Cryptographically signed evidence that auditors can independently verify. Not screenshots. Not report generation. Actual chain-of-custody for every AI decision.

Outcome — GRC becomes continuous, not quarterly. Evidence is machine-generated.
04 · ML
Quality

Evaluation copilots that grade production behavior.

"How is the finance copilot performing against our helpfulness and accuracy criteria this week?"

Every agent turn scored against your criteria — live, not offline. Regressions surface with the sessions that produced them, still linkable to source prompts and tool calls.

Outcome — Eval graduates from a benchmark to a runtime signal.
The Thesis

The next generation of enterprise AI experiences won't be built on custom data plumbing.

They'll be built on awareness-grade platforms that already understand agent behavior. The Agentic Awareness Layer is that platform.

AI Defendo is the first product proving it. Your teams are the next builders.

Building Together

We're building the platform in the open.

Enterprise AI teams reshaping their SOC, platform, GRC, and ML functions are welcome to shape what we build. If your teams will be building on an awareness substrate — we want to hear from you before we ship the surface.

Priority conversations: enterprise AI teams in regulated industries and platform engineering organizations preparing to run agents at scale.

Build the awareness layer with us.

AI Defendo ships today. The developer surface comes next. If your teams will build on it, we want your input first.