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Product / AI Actors
Govern every AI actor: human, app, or agent.
An AI actor is anything that uses AI through Tallin: a person, an application, or an autonomous agent. Route that AI through Tallin and each one becomes a named identity you can scope to specific models, hold to a budget, bind to a policy, trace in an audit trail, and disable on demand. That turns agents into governed infrastructure instead of invisible spend.
What every actor gets
Six controls on every human, app, and agent.
- Identity & ownership
- Every actor, whether a person, an application, or an agent, is a first-class identity with a name, an owner, a business purpose, and an environment. No anonymous AI.
- Per-actor budget
- A monthly budget with alerts before the threshold and an automatic cutoff after it, so a looping agent stops before the invoice does the talking.
- Model & provider access
- An approved provider and model-tier scope per actor. Requests outside it are blocked at the gateway, or logged in shadow mode while you tune.
- Kill switch
- Disable an actor's Tallin-mediated model access in one click. The next request, on any of its keys, is rejected.
- Shadow mode
- Run a new agent in shadow first: Tallin records what it would have blocked, so you turn on enforcement with evidence, not guesswork.
- Audit & review
- Every request, cost, and policy decision is on the record per actor, and the AI Agent Review report turns it into a committee-ready artifact.
One agent, governed
Set it once. Enforced on every routed request.
Owner, scope, budget, and policy are defined when the agent is created, enforced in the live request path, and rolled up into one committee-ready line in the AI Agent Review.
Actor record
Representative example
- Owner
- Priya Nair · VP Support
- Approved models
- Claude Sonnet 4.5 · GPT-5 mini
- Monthly budget
- $2,000 · automatic cutoff at 100%
- Policy
- Customer PII prohibited by policy (content enforcement on the roadmap) · rate-limited
- Kill switch
- Armed
- Capture
- Metadata-only (configurable to full-content)
Honest coverage
Control what routes through Tallin. Prove what doesn't.
Tallin governs the AI traffic routed through it: model access, spend, and policy. It is explicit about what it does not control.
Product / Actor controls · Runtime control
The controls every actor needs, before agents arrive at scale.
Gartner projects 150,000+ AI agents per Fortune 500 by 2028, yet only 13% of teams feel adequately governed. Agents spend and act unattended, so each one needs an owner and a leash you set in advance.
What changes for you
No actor spends or acts without an owner and a limit.
- Owner + scope
- Every AI actor, whether a human, an app, or an agent, carries a named owner, an approved model scope, and a budget, so every dollar and action traces back to someone.
- Cutoff + kill switch
- An automatic budget cutoff and a kill switch turn runaway agent spend from an after-the-fact surprise into a control you set in advance and trigger in one click.
- Owner-routed alerts
- Alerts route to the right owner when an actor approaches its budget, requests an unapproved model, or trips a policy, giving admins a queue they can actually work.
Control queue
A live list of the controls on each actor.
Tallin keeps every control next to the actor it governs: budget cutoffs, approved model scope, required owners, kill switches, and the agents still running in shadow mode before enforcement.
- Budget cutoff
- Agent workloads · Enforced
- Approved model scope
- Per-actor gateway keys · Enforced
- Owner required
- Unowned actors · Active
- Shadow mode
- New agent rollout · Simulating
Control, on the record
Governance you can watch fire.
Every alert, cutoff, and block on gateway-routed traffic lands as an append-only entry, attributed to the actor that triggered it.
Explore
The pieces that make it work.
The in-path control point. Hosted for the strongest control, or in your own VPC for data residency.
Every AI dollar attributed to the actor that spent it.
Observed, inferred, enforced, or not covered, on every provider and actor.
Put an owner, a budget, and an off switch on every AI actor.
Create your first agent, give it a scope and a budget, and watch the controls hold in the live request path before you expand.