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| IBM+EVS |
Equitus Video Sentinel (EVS) is available natively for IBM Power users specifically needing to unlock advanced AI-driven video intelligence services without crippling operational efficiency or hardware costs. While IBM Power 10/11 architecture provides standard enterprise processing power, memory bandwidth, and security.
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Enterprise IBM Power users can utilize Equitus EVS to solve their video analytics challenges:
1. Native Multi-Modal AI Without GPU Dependency
Problem: Standard AI video analytics rely heavily on expensive, power-hungry, and supply-constrained GPU clusters.
Power Users Need EVS: Equitus EVS leverages the ONNX runtime framework to compile and execute complex multi-modal AI models—including YOLO (object detection), SAM (segmentation), and RelateAnything (relationship modeling)—directly on IBM Power11’s integrated Matrix Math Accelerators (MMA). This allows Power users to run deep vision models natively on enterprise CPUs without relying on dedicated GPUs.
Problem: Standard AI video analytics rely heavily on expensive, power-hungry, and supply-constrained GPU clusters.
Power Users Need EVS: Equitus EVS leverages the ONNX runtime framework to compile and execute complex multi-modal AI models—including YOLO (object detection), SAM (segmentation), and RelateAnything (relationship modeling)—directly on IBM Power11’s integrated Matrix Math Accelerators (MMA). This allows Power users to run deep vision models natively on enterprise CPUs without relying on dedicated GPUs.
2. From Simple Detection to Contextual Intelligence
Problem: Basic video management systems (VMS) only provide simple motion detection or basic object taggers, resulting in thousands of false positives and alert fatigue for operators.
Power Users Need EVS: EVS supplies the semantic and contextual layer missing from raw camera feeds. By fusing relational graphs (RelateAnything), EVS interprets dynamic scenes—such as recognizing a bag left unattended near a restricted doorway by a specific individual—transforming raw video data into actionable, high-precision intelligence.
Problem: Basic video management systems (VMS) only provide simple motion detection or basic object taggers, resulting in thousands of false positives and alert fatigue for operators.
Power Users Need EVS: EVS supplies the semantic and contextual layer missing from raw camera feeds. By fusing relational graphs (RelateAnything), EVS interprets dynamic scenes—such as recognizing a bag left unattended near a restricted doorway by a specific individual—transforming raw video data into actionable, high-precision intelligence.
3. High-Speed Unstructured Video Search & Forensics
Problem: Enterprises generate terabytes of unindexed, unstructured video daily. Manually searching hours of video across hundreds of camera streams during a security event is labor-intensive and slow.
Power Users Need EVS: EVS turns video streams into indexed, searchable metadata in real time. Power users can perform forensic queries (e.g., searching by specific attributes, colors, or relational behaviors) in seconds across vast video repositories, drastically reducing incident response times.
Problem: Enterprises generate terabytes of unindexed, unstructured video daily. Manually searching hours of video across hundreds of camera streams during a security event is labor-intensive and slow.
Power Users Need EVS: EVS turns video streams into indexed, searchable metadata in real time. Power users can perform forensic queries (e.g., searching by specific attributes, colors, or relational behaviors) in seconds across vast video repositories, drastically reducing incident response times.
4. Maximizing Existing Hardware & Lowering TCO
The Problem: Scaling enterprise video analytics typically requires purchasing separate, specialized vision servers or cloud compute licenses.
Power Users Need EVS: EVS integrates directly into existing IBM Power11 infrastructure and enterprise Video Management Systems (VMS). By maximizing memory bandwidth and multi-threaded parallel execution on Power11 CPUs, EVS delivers significantly lower Total Cost of Ownership (TCO) and lower energy consumption compared to traditional GPU-bound deployments.
The Problem: Scaling enterprise video analytics typically requires purchasing separate, specialized vision servers or cloud compute licenses.
Power Users Need EVS: EVS integrates directly into existing IBM Power11 infrastructure and enterprise Video Management Systems (VMS). By maximizing memory bandwidth and multi-threaded parallel execution on Power11 CPUs, EVS delivers significantly lower Total Cost of Ownership (TCO) and lower energy consumption compared to traditional GPU-bound deployments.
5. Built-in Regulatory Compliance & Data Sovereignty
Problem: Federal, Justice, and Healthcare organizations face strict compliance mandates (CJIS, HIPAA, NERC CIP) that prohibit sending sensitive video feeds to public cloud services.
Power Users Need EVS: Equitus EVS is architected for strict on-premises data sovereignty. Running EVS on IBM Power11 ensures that all video processing, inference, and evidence indexing remain fully isolated within the enterprise network, eliminating cloud exfiltration risks and preserving strict chain-of-custody compliance.
Problem: Federal, Justice, and Healthcare organizations face strict compliance mandates (CJIS, HIPAA, NERC CIP) that prohibit sending sensitive video feeds to public cloud services.
Power Users Need EVS: Equitus EVS is architected for strict on-premises data sovereignty. Running EVS on IBM Power11 ensures that all video processing, inference, and evidence indexing remain fully isolated within the enterprise network, eliminating cloud exfiltration risks and preserving strict chain-of-custody compliance.
1. Enterprise Video Analytics Needs (The User Core)
Enterprise organizations require real-time threat detection and rapid forensic capabilities without risking data exposure or incurring unsustainable GPU infrastructure costs.
Industry Use Cases: Zero-Trust Environments
Federal / Defense: Automated perimeter surveillance, threat awareness, real-time tracking across multi-camera feeds, and tactical video intelligence.
Justice System: Automated evidence indexing, inmate behavior monitoring, courtroom video analysis, and chain-of-custody metadata tracking.
Healthcare: Patient safety tracking, fall detection, perimeter/access control, and HIPAA-compliant restricted zone monitoring.
2. Equitus Video Sentinel (EVS) Platform & Software Synergy
Equitus EVS provides the software intelligence layer, fusing multi-modal vision and graph-based models into enterprise workflows:
Multi-Modal AI Pipeline (ONNX Framework): EVS normalizes multi-modal deep learning models via ONNX runtime for cross-platform efficiency.
Integrated Analytics Stack:
YOLO (You Only Look Once): Real-time object detection and classification (people, vehicles, equipment, weapons).
SAM (Segment Anything Model): Pixel-precise instance segmentation to isolate subjects, objects, or scene anomalies regardless of lighting or angle.
RelateAnything: Open-vocabulary spatial and semantic relation modeling (predicts relationship triplets like
Person → Carrying → ItemorIndividual → Approaching → Restricted Door).
Forensic Metadata & Search: Converts unstructured video into indexed, searchable metadata (attributes like color, direction, hair, license plates, and temporal behavior).
3. IBM Power11 Infrastructure Capabilities
IBM Power11 provides the compute, memory bandwidth, and security foundation required to process concurrent high-density video streams without relying on expensive, supply-constrained GPU clusters:
Inference Efficiency: Power11 processors feature integrated Matrix Math Accelerators (MMA), enabling efficient deep learning inference directly on enterprise server CPUs.
Massive Parallel Throughput: High memory bandwidth and multi-threading enable parallel frame decoding and model processing across hundreds of live RTSP camera feeds.
Enterprise Security & Isolation: On-premises architecture eliminates cloud latency and data-exfiltration risks, providing hardware-level isolation for sensitive environments.
4. Intersection Dynamics: How the Fit Works
5. Economic & Strategic Value Driver: The Three Filter Lens
A. Scope (Scale & Architectural Reach)
Ingestion Scale: Handles thousands of live streams across multi-site enterprise networks.
VMS Integration: Integrates into existing Video Management Systems (VMS) without requiring camera replacement, preserving existing legacy infrastructure investment.
B. Goals (Economic & Operational Impact)
Compelling Economic Value (Lower TCO): Running multi-modal AI on IBM Power11 eliminates GPU licensing/hardware costs, significantly lowering total cost of ownership (TCO) and energy consumption.
Actionable Intelligence: Reduces hundreds of hours of manual monitoring to automated, under-60-second alert cycles.
C. Compliance (Legal & Governance Alignment)
Regulatory Readiness: Built specifically for strict compliance environments, supporting CJIS (Justice), HIPAA (Healthcare), and NERC CIP / CFATS (Federal/Critical Infrastructure).
Data Sovereignty: Fully local/on-premises deployment options ensure video feeds never cross third-party cloud boundaries, satisfying strict federal and legal chain-of-custody mandates.
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