EdgeSense for Computer Vision by Deloitte
Deloitte · Cybersecurity & IT
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
# **How does EdgeSense Work?**
- **AI models on the edge:** CCTV camera feed monitoring with observations detected in real time.
Show the rest of the publisher’s description (19 more lines)
The EdgeSense Computer Vision models detect people, assets, animals and objects and monitors how they interact with each other; capturing video snippets that meet a specific set of criteria as defined by the business.
- **Workflow:** Automated notifications for users to review observations and drive escalation or resolution.
EdgeSense save and aggregates relevant video snippets of potential process observations and notifies the allocated personnel for expert review, event confirmation and feedback.
- **Dashboards:** Real-time trend analysis, insights, benchmarking & reporting.
EdgeSense data analysis includes trend reports outlining observations and resolutions over time for each type of deviation, zone, camera, and location.
# **Benefits of EdgeSense:**
EdgeSense has many benefits compared to the traditional camera surveillance:
**Monitoring** – Significantly better monitoring of facilities and assets through the use of AI, computer vision and robust data analytics and statistics.
**Insights** – More accurate and quantifiable insights into the type, severity, and frequency of observations.
**Continuous improvement** – Automated feedback loops continuously improve the accuracy of AI and CV models.
**Saves Time** – Significantly reduces FTE time required to review video footage.
**Real Time** – Reporting, warnings and alerts can be sent in real-time and can also interact with operational equipment.
**Scalable** – EdgeSense is cloud native, which allows it to easily scale to multiple locations, environments, and processes.
# **Example use cases include:**
- **Workplace Safety:** Ensure compliance and reduce accidents.
- **Animal Health and Welfare:** Monitoring livestock and their handling.
- **Asset Condition Monitoring:** Keep track of equipment health and use.
- **Road Safety**: Monitor driver behaviour and improve traffic management.
- **Body-Worn Cameras:** Enhance intelligence extraction and accountability.
Highlights
Highlighted by the publisher on AWS Marketplace.
Our EdgeSense platform enables business users to log in, review, classify and drive actions from observations detected by CV models.
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Sources
Linked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.

