Requests and model calls
Connect prompts, model and version, response identifiers, and policy decisions into one execution trail.
AI Action Evidence
Make AI actions reviewable after they happen
A final AI response rarely explains enough for operations or audit. Rantropy is developing a separate product that records the path from a request through model calls, tool execution, approval, and external action as evidence that can be checked later.
In development as a separate product
It will not launch as a bundled randomness API feature. We start by reviewing the customer's operating environment and regulatory needs.
Evidence scope
Record the execution path, not only the answer
The evidence model connects who requested what, which model and tools ran, and what happened next.
Tool calls and external actions
Record tool activity that affects real systems, such as search, data changes, and message delivery.
Approvals and exceptions
Include human approvals, rejections, retries, and overrides so responsibility boundaries remain visible.
Deployment direction
Separate SaaS and procurement requirements
Data movement, retention, and independent verification differ by customer, so the delivery model should not be fixed to one environment.
SaaS integration
Add an evidence collection layer to existing AI applications and agents.
Customer-environment deployment
Review requirements and delivery feasibility for customer AWS accounts or restricted networks.
Independent verification
Prepare tools that can inspect exported evidence without access to the originating service.
AI evidence starts with the real workflow
Tell us which models and tools you use, where approvals happen, and what an auditor must be able to verify. We will help define the events that matter.