Compliance & Governance
AI Assurance Explained
Learn what AI assurance is, how evaluation sets provide evidence that AI systems are working as intended, and why they're essential for AI governance, testing, and audit readiness.
AI Workflows
Automated call review against your own policies
Describe your business and what to check in plain language. Argus Archive reviews every call against it, after the call or live with the Real-time add-on, and sends each alert to the right person in Microsoft Teams.
From your policy to the right person
Four steps in one editor, with no code at any point.
Describe your business
Add your products, your terms and the standards your reviewers apply. Every rule in the policy uses it.
- Terms read the way your firm uses them
- Written once for the whole policy
Ask your questions
Each rule is one question about the call, such as "Did the adviser read the risk warning?" The answer can be yes or no, a number, a list, or the exact quotes found.
- Write it yourself, or describe it in one sentence and AI writes it
- Check your own people, the customer or both
Choose what happens
Pick when an alert is raised from simple menus, how serious it is, and what follows: a tag, a message to a Teams channel or an event to your own systems.
- Conditions picked, never typed as code
- Follow-up that runs on its own
Test, then publish
Try the policy on past calls or on test conversations the AI drafts for you, check each answer, then publish it.
- Problems found before they reach a reviewer
- Every change saved as a version
Review that stands up to scrutiny
Each alert has an owner, and every decision on it is recorded with a reason, so you can show how it was handled.
- The exact words from the call that raised it
- Assigned to a reviewer, with a status and notes
- Escalated with a reason, such as possible regulatory exposure
- Closed with a reason, such as a false positive or a confirmed breach
- Shared with a Teams user or channel
- Every step kept in the audit log
What teams check with it
The same editor serves compliance and customer service. Common first policies:
Risk warnings
Required warnings and disclosures given before the customer agrees.
Conduct risk
Pressure selling, promised returns or risks played down.
Off-channel moves
Asking to carry on by mobile or a messaging app.
Supervisor requests
Customers who ask for a manager or say they will complain.
Service standards
Greeting, identity checks and next steps agreed on each call.
Calls for a case
Matching calls filed into an open case by their alerts.
How do I write a rule?
Describe your business and your review standards once, then add each rule as a question in plain language. Define Rule with AI writes a rule from a short description. Alert conditions are chosen from menus, so there is no code.
How do I know a policy works before it goes live?
Test it on a sample transcript, on past calls or on test conversations the AI drafts, and check each answer. Publish only when you are happy. Every change is saved as a version with a note, and AI Assurance keeps the testing on record.
Does it check calls live or after they end?
You choose for each policy. After the call is included; live checks need the Real-time add-on.
What can happen when a rule matches?
Argus Archive raises an alert at the severity you set. It can also tag the call, post the alert to a Microsoft Teams channel and file the call into an open case. Sending an event to your own systems through the API is coming soon.
How can I see why an alert was raised?
The alert shows the rule, the AI's answer and the exact words from the call, with the recording and transcript one click away.
Who can change a policy?
Only people whose role allows it. Publishing makes a new version live, and earlier versions stay on record.
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