Taigris

The audit trail for your AI toolbox

AI audit trail. Proof on the trail. Customer-owned environment. One record of AI use an operator can read and a reviewer can export.

What Taigris is

Assistants now sit inside email, chat, finance, HR, CRM, IT ops, and the frontier clients people open when those tools are not enough. Each vendor keeps a history, if it keeps one at all. None of those histories is a firm-wide trail.

Taigris is that trail. It observes AI use in context, attributes who and which system acted, binds the event to policy, and leaves a trail you can hand over.

  • One audit log across the toolbox, not a log per vendor.
  • Policy on the row, record detail, hash chain, exportable trail.
  • Hermetic, customer-owned environment: your trail stays yours.
  • A live trail: the record in motion, not a quarterly dump.

How the trail is made

The control loop is the product.

  • Observe: AI use in context, failures and successes included.
  • Detect: untracked or policy-relevant use when it appears.
  • Trace: who, which system, what was asked or decided.
  • Scope: the environment and policies you define.
  • Prove: an audit trail operators and reviewers can read.

Surfaces operators live in

The interface is the trail. The audit log lists every AI touch: source, user, system, policy, hash. Open a row for record detail. Policy sits next to the work. The live trail keeps the active record lit while the trail updates.

What a record contains

Each entry is an attributable event in a chain, not a prompt dump.

  • Source and AI system: the tool, not only a model name.
  • User and time.
  • Policy that applied, including shadow-AI policy.
  • Action and downstream outcome.
  • Response ID, and parent ID when the work continues a thread.
  • Hash and previous hash, so the trail can be verified.

Customer-owned, hermetic

Customer-owned environment. Hermetic boundary. Observation, attribution, and proof stay inside scope you control. Taigris does not take ownership of your trail.

Who it is for

Regulated teams putting AI into high-stakes work: law firms, professional services, and enterprises that already answer to clients, partners, or internal audit.

How a deployment starts

A demo walks the trail on a toolbox that looks like yours. Design-partner work then scopes observation to the environment you own, the tools in play, and the policies that belong on the row.

Questions

Related

Bring the proof with the power.

For regulated teams putting AI into high-stakes workflows. Book a demo and we’ll show the trail on your toolbox.