Platform overview, 108 seconds. Real runs in demo organizations with synthetic companies, people, and data. Waits are cut out, not sped up. Splunk stands in for the SIEM a security team already runs.
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This is Decision Terrain, your own agent platform. It runs on your hardware, or in your own cloud account.

Your team puts AI agents to work in chat, the way they’d ask a colleague. And your own systems call the same agents through the API.

They plug into the systems you already run. Here, a supplier analyst agent comes back with what matters: two suppliers running late, and the units at risk.

You already know AI can help. The real question is the risk. What is it doing? And can you stop it?

Decision Terrain is built so your CISO can sleep at night.

An agent just tried to write down a restricted codename. It didn’t get through.

You set the rules. One floor for your whole organization. Any agent can be stricter, but none can go below it.

And before anything goes wrong, you can see exactly what an agent could reach, and what one change would take away.

When it matters, the work waits for a person. A manager sees exactly what’s about to go out, fixes a detail, and approves that exact version.

And your security tools can step in. Splunk spots the blocked attempt, and halts that one agent automatically. It stays on hold until a person releases it, on the record.

Ask why anything happened, and you get the recorded path: who asked, what the model did, and what was allowed or denied. Where the record has a gap, it shows you the gap.

That’s why your organization can trust it. Not just to try AI, but to go all in.

That’s governed autonomy. That’s Decision Terrain.

What does the overview show?

It opens on the platform at work, then turns to the question most security teams ask first: what is the agent doing, and can you stop it?

  1. Agents at work. Your team asks agents for help in chat, your own systems call the same agents through the API, and agents read from the systems you already run. A supplier analyst agent reports two late suppliers and the units at risk.
  2. A rule blocks a restricted write. An agent tries to write down a restricted codename. The write does not go through.
  3. You set the floor. One set of rules applies to the whole organization. Any agent can be configured to be stricter, but none can go below it.
  4. You can see what an agent could reach. The blast radius view maps the systems and tools an agent can reach, grades each path by severity, and previews what removing one tool would take away.
  5. The work waits for a person. An agent drafts an email to an outside supplier. A manager sees the exact message, fixes a detail, and approves that version.
  6. Your security tools can halt an agent. A Splunk detection spots the blocked attempt and halts that one agent. It stays on hold until a named person releases it, and both steps are recorded.
  7. Every action has a recorded path. The Why view shows who asked, what the model did, and what was allowed or denied. Where the record has a gap, the view shows the gap instead of filling it in.

What the video shows, and what it does not

  • The organizations, people, suppliers, and data are synthetic. No real customer or program is shown.
  • Each run is real. Shots come from two demo organizations, and some joins between takes are edited for length.
  • The blast radius beat previews removing a tool. The preview was undone, and no setting was changed.
  • The halt beat stops one agent and releases it. It does not undo work the agent already did.
  • The runs used hosted models. A model name is blurred in one shot. This is not a disconnected or air-gapped run.
  • Splunk receives the audit events through the deployment’s forwarding route. A local Splunk instance stands in for the team’s SIEM.