Healthcare marketing compliance agent
Tryozi's compliance agent surfaces the right issues before anything goes live.
Every page change is checked against approved marketing rules, with flagged language and supporting evidence prepared for human review.
The impact
86%
less time preparing a page review
Healthcare marketing compliance agent
Case study facts
- Industry
- Telehealth
- Team
- Marketing
- Systems connected
- 3
- Time to live
- 2 weeks
- Engagement
- AI implementation
The impact
Results for the team
- less time preparing a page review
- 86%
- less time preparing a page review
- Changed language and potential rule conflicts arrive organized for review, reducing the time reviewers spend preparing each page check.
- more changes checked per reviewer
- 4×
- more changes checked per reviewer
- Each reviewer can check more page changes because changed claims and potential issues arrive already organized for review.
- of flagged changes retain their evidence
- 100%
- of flagged changes retain their evidence
- Every flagged change keeps the relevant source text and approved rule attached, so reviewers can inspect the evidence behind it.
Situation
Every edit restarted the review.
Reviewers had to inspect every marketing change from scratch. Small edits could introduce a problematic claim, and a queue of unstructured checks made it hard to focus on what had changed.
Challenge
Small changes could create new claims.
Reviewers needed to see which language had changed, which approved rule applied and why a passage might need attention. The agent had to prepare that evidence without taking over legal judgment or publishing authority.
What we built
A focused review queue with evidence.
We built a compliance agent that compares page changes with the client's approved rules and claim library. It pinpoints the language that triggered a concern, links the relevant rule and prepares the issue for review.
The record travels with the change, so a reviewer sees the evidence and its disposition before making the publishing decision.
- 01
Detect the change
Diff the proposed copy against the previous version.
- 02
Retrieve the rules
The agent pulls the approved guidance relevant to each claim.
- 03
Analyze the language
- RAG
Unsupported claims, omissions and possible rule conflicts are flagged.
- 04
Assemble the evidence
Each flag shows the exact passage and the rule behind it.
- 05
Route to a reviewer
- Human in the loop
The responsible person gets a focused, prioritized review queue.
- 06
Record the decision
The approved disposition stays attached to the content change.
Evals and guardrails
Catch missed issues. Keep approval human.
Detection evals
Measure missed issues and incorrect flags against reviewer-checked examples. Repeat tests after changes to prompts, models or rules.
Evidence evals
Check that approved rules support each finding. Verify cited passages and rule versions so reviewers can trace the reason for every flag.
Guardrails
Check required output fields and approved rule references. Send failed checks and uncertainty to a reviewer; block publishing access.
Results
Reviewers can focus on what changed.
Changed language and potential rule conflicts arrive organized for review, reducing the time reviewers spend preparing each page check. Each reviewer can check more page changes because changed claims and potential issues arrive already organized for review.
Every flagged change keeps the relevant source text and approved rule attached, so reviewers can inspect the evidence behind it.
- less time preparing a page review
- 86%less time preparing a page review
- more changes checked per reviewer
- 4×more changes checked per reviewer
- of flagged changes retain their evidence
- 100%of flagged changes retain their evidence
From Tryozi
“We had tried other partners and nobody could unblock it. Revensi came in, understood the problem quickly, and turned a bottleneck into something that just runs. Total game changer.”
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