Agent assurance for enterprise AI

Agent autonomy. Justified.

CredencePlus helps engineering, infrastructure, and AI teams verify agent behavior and justify autonomy with evidence.

Test the boundaries. Defend the decision.

Evaluate your AI agent workflow See the evidence

For the teams accountable for what agents do.

Behavior under evaluationIllustrative scenario

Evidence supportsAutonomous

The observed actions stay within the workflow’s intended scope.

An example of evaluation, not a live workflow or enforcement control.

Observed behavior.
Accountable autonomy.

Read-only logs & traces

Inside your environment

Evidence you own

The decision, made defensible

How much autonomy
does the evidence support?

Evaluate agent behavior, not just its answers.Grant autonomy based on evidence.

Workflow assessmentIllustrative example

Infrastructure operations

Alert triage agent

Human in the loop

✓Source evidence collectedVerified

✓Alert context evaluatedVerified

!Ambiguous escalation decisionReview

Why this verdict

The agent handles routine triage, but ambiguous alerts need an analyst’s judgment before escalation.

Traceable actions. Defensible decisions.

Example scenarios show the assessment format. Actual verdicts depend on your workflow and evaluation evidence.

Follow the evidence

Every action.
A trace you can inspect.

Connect an agent’s inputs, actions, and outputs to their sources. See exactly where the evidence stops.

WorkflowIncident triage agent

Observed duration1.08s

EvaluationHuman review required

span_03

Summarize

Missing evidence

Two supported facts. One missing source.

The service and incident status trace to observed inputs. The suggested escalation owner has no supporting source.

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SourceObserved eventevt_1042

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ActionAgent summaryspan_03

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DecisionHuman reviewSource gap identified

Synthetic trace for illustration. Explore an action, then inspect its input, output, or evidence.

Boundaries, behavior, and evidence

Find the failure.
Defend the decision.

Test the deployed workflow against expert ground truth. See exactly where behavior meets expectations — and where it breaks.

Define the intended scope.

Start with one AI agent workflow and the actions it is intended to take. Use read-only logs and traces to evaluate it as deployed.

As deployed. No endpoint installation.

Challenge the behavior.

Test missing evidence, adversarial inputs, tool failures, and agent handoffs. Score what the agent actually did, step by step.

Real behavior against expert ground truth.

03✓

Justify the autonomy.

Get an autonomy verdict with the evidence behind it. Identify the failed action or handoff and explain the decision to reviewers.

A verdict you can substantiate.

A model update changes the evidence. Re-test.

Re-test after every model, prompt, or tool change to catch regressions. Track tokens, time, and human intervention on every run.

Let’s evaluate yours

Built for your environment

Your environment.
Your evidence.

For engineering, infrastructure, and AI teams that have to substantiate an autonomy decision — and keep the underlying data under their control.

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Your data stays with you
Runs inside your environment. Nothing leaves.
✓
No endpoint or server installs
Works from read-only logs and traces.
✓
One evidence trail. Multiple obligations.
Findings map to NIST AI RMF, the EU AI Act, or sector model-risk expectations to support authorization, audit, and AI use-case reporting.

Your enterprise environment

⇄ AI agent workflows

Read-only logs & traces↓

CredencePlusEvaluate · Trace · Re-test

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▤ Signed evidence package

Research at the foundation

Security expertise.
Evaluation discipline.

CredencePlus grew out of CTIBench, a cybersecurity benchmark recognized as a NeurIPS 2024 Spotlight. The same focus on expert ground truth now informs evidence-based evaluation of agentic workflows.

From multi-agent threat-intel pipelines and phishing analysis to control-evidence reporting, the question stays the same: can you substantiate what the agent did?

Start with one AI agent workflow

One AI agent workflow.
A defensible decision.

Bring an AI agent workflow. Within days of read-only access, know what autonomy it can support, what justifies it, and where it breaks.

Tell us about your agent and what you want to understand.