University-Wide Compliance Powered by Pulse
Pulse turns unmeasured accessibility practices into one university-wide strategy, covering every video and every use case. Continuous video library monitoring identifies your accessibility gaps. Use that data to prioritize remediation and get more coverage from every budget dollar.
Compliance Policies Need Better Information
Volume
Millions of minutes of video exist across your library, all requiring captions and audio description. Manually reviewing every file isn't possible at that scale.
Incomplete Data
Caption accuracy varies widely across your library. Audio description coverage is entirely unknown. That uncertainty creates compliance risk.
Cost
Budgets rarely cover remediating everything. Without knowing what videos are at the most risk, that spend can't be prioritized.
Pulse Provides the Data Needed for Smarter Compliance Policies
Complete Scoring. Complete Insight. Complete Control.
Pulse provides every video's compliance status in one place so you know exactly where your accessibility budget is going.
- Every file gets its own caption accuracy score and audio description analysis, showing exactly which videos adhere to your policy.
- Review real data on your video compliance today. Use it to build policies that fit your institution's needs.
- Determine the remediation workflows that are right for you, based on your risk tolerance and budget.
- A complete record of your video library tracks exactly where every budget dollar goes.
Other Approaches
AI captions everywhere, faculty clean them up
You turn on auto-captions across every platform and ask instructors to review and fix their own.
- You can't tell which captions are accurate and which ones aren't
- You can't say whether you've reached compliance, only that you have a policy
A bundled plan with unlimited AI
Other platforms offer subscriptions that include unlimited AI captions and audio description, plus a fixed bank of human review hours.
- “Unlimited” applies to the inexpensive part. Human review, where the quality actually comes from, is capped
- You still have no insight into your library, so you can't tell where those limited hours should go
How Pulse Works
Pulse connects to your platforms and scores every video. You decide how each score gets remediated. New content is scored the moment it’s uploaded. Your insights stay current.
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Connect
Link your video platform.
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Scan
Each video is evaluated for caption and audio description needs.
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Score
Each video receives an AI sufficiency score for captions and AD.
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Remediate
You designate which videos receive which service level by leveraging its score.
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Monitor
Continuous scoring on all new content – access real-time details in your Pulse dashboard.
You Set the Rules
The process is consistent. What changes is up to you, from the review level to the exact conditions that trigger it. Adjust either one whenever your budget or priorities do.
Choose Your Review Level
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Launch
No Human Review
Leverage the best automatic speech recognition to get closed captions and audio description back quickly and economically.
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Refine
Targeted Human Review
Targeted human review of auto-generated outputs to ensure major accuracy issues are addressed.
- Recommended
Accommodate
Complete Human Review
Full human review of auto-generated outputs. Compliance is guaranteed.
How You Control It
Configurable Routing Rules
You decide what happens at each score threshold, and you can layer in your own context like who published the video, how many views it has, or which department it came from.
Flexible Delivery
Finished files come back through your existing integrations, through the API, or as direct downloads.
Accommodation Bypass
Student accommodation requests skip the scan entirely and go straight to full human review.
Budget Targeting
Spend gets directed toward the files that need it most, so a fixed budget produces more real coverage than spreading it evenly.
“[Pulse] isn’t just a caption quality tool, it’s a budget strategy. It ensures we invest human review where it’s actually needed, while giving faculty confidence that every video they upload meets a dependable accuracy baseline.”
Brian Smith
IT Manager, UFIT Video & Collaboration Services, University of Florida
Every Video's Status in One Place
Caption accuracy across your library
- Track how caption accuracy is distributed across every file you hold.
- The dashed line marks the accuracy threshold you set.
- Files below it are routed to the review level you choose.
| Caption accuracy | Duration (Minutes) |
|---|---|
| 0–5% | 0 |
| 5–10% | 0 |
| 10–15% | 0 |
| 15–20% | 0 |
| 20–25% | 0 |
| 25–30% | 0 |
| 30–35% | 0 |
| 35–40% | 0 |
| 40–45% | 0 |
| 45–50% | 12 |
| 50–55% | 20 |
| 55–60% | 16 |
| 60–65% | 28 |
| 65–70% | 40 |
| 70–75% | 78 |
| 75–80% | 210 |
| 80–85% | 32 |
| 85–90% | 430 |
| 90–95% | 620 |
| 95–100% | 62 |