Computer Vision for
Real-Time Decisions.

Move beyond “model demos.” We engineer production Computer Vision and Edge AI inference stacks that detect, track, read, and verify—running in low-latency environments with privacy-first deployment, observability, and measurable accuracy.

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Real-Time Perception

On-Device Inference

Privacy by Design

Vision Systems Trusted in Production Environments

42%
Defect Escape Reduction

Visual inspection that catches drift and edge cases.

18ms
Edge Inference Latency

Optimized runtimes for real-time decisions.

100%
Privacy-First Deploys

Keep frames on-device; export only signals.

$0.
Vendor Lock-In

Own the pipeline, models, and deployment artifacts.

Beyond the Vision Demo.
Production, Not Prototypes.

Most CV systems break in the real world due to lighting drift, camera variance, and deployment fragility. We build robust pipelines with edge optimization, verification, and telemetry—so it works on Day 2.

The CV Failure Pattern

What most “build teams” ship:

  • No Drift Strategy

    Models degrade with lighting, camera swaps, and seasonal changes.

  • Fragile Edge Runtime

    Inference fails under latency, memory, or thermal constraints.

  • Zero Observability

    No confidence telemetry, no audit trail, no retraining signals.

The Coretus Vision Standard

Production-grade perception:

  • Robust Data + Drift Controls

    Dataset design, augmentation, QA, and drift monitoring signals.

  • Edge-Optimized Inference Stack

    Quantization, batching, runtime tuning, and hardware-aware deployment.

  • Telemetry + Human Review Loops

    Confidence logging, audit trails, and retraining triggers with HITL gates.

Less Noise. More Verified Signals.

Strategic Capabilities.

Moving from Frames to Decisions at the Edge.

Detection + Tracking

Object detection, multi-object tracking, counting, and event triggers for real-time operations.

  • Low-Light Robustness
  • Multi-Camera Calibration

OCR + Visual Reading

Industrial OCR, meter reading, labels, forms, and ID capture with confidence gating.

  • Confidence Thresholds
  • Human Review Queue

Quality Inspection

Defect detection, anomaly spotting, and visual QA tuned for production variance.

  • Drift Monitoring
  • Golden Sample Tests

Edge Deployment

On-device inference for low latency and privacy—optimized for your hardware constraints.

  • Quantization + Pruning
  • Runtime Tuning

Data Engine

Annotation pipelines, dataset QA, active learning loops, and continuous improvement signals.

  • Hard-Negative Mining
  • Active Learning

Secure Telemetry

Audit trails, metrics, and alerting for model confidence and operational reliability.

  • Event Logs
  • Confidence Drift Alerts
/// Vision-Edge Stack

Hardened Pipeline for
Edge Perception.

Data + Label QA

Training Integrity

Dataset versioning, annotation QA, and hard-negative mining so the model learns real-world variance.

Label QA + Consensus
Augmentation Strategy
Active Learning Loop
DatasetsTaxonomyQA

Edge Runtime

Low Latency

Quantization, acceleration, batching, and hardware-aware tuning for stable on-device inference.

INT8 / FP16 Optimization
Runtime Tuning
Thermal + Memory Constraints
TensorRTOpenVINOTFLite

Verification Gates

Signal Quality

Confidence thresholds, region rules, and HITL escalation before decisions become actions.

Confidence Thresholding
Rule-Based Filters
HITL Escalation
PoliciesRegionsReview

Observability

Drift + Ops

Confidence telemetry, event logs, alerting, and retraining triggers so your system improves over time.

Confidence Drift Alerts
Edge Health Metrics
Audit Trails
MetricsLogsAlerts
/// Vision Accelerator

Ship Vision.
Skip the Fragility.

We deploy the Coretus Vision Kernel™—a pre-hardened foundation for data QA, edge runtime optimization, verification gates, and observability.

Your teams focus on use-case accuracy and operational impact, not rebuilding pipelines.

6-10 Wk

Time-to-Deploy Saved

$180k+

Annual Compute Savings

Built for audit trails, confidence gating, and edge runtime stability.
Runtime Hardened

Your Environment Reality

Lighting • Motion • Cameras • Constraints

Coretus Vision Kernel v3.1

Data QA

  • • Taxonomy
  • • QA

Edge Runtime

  • • INT8
  • • Accel

Verify Gates

  • • Rules
  • • HITL

Telemetry

  • • Drift
  • • Alerts
/// Pre-Configured Vision Pods

Deploy Production-Ready Vision Squads.

Integrated delivery units specialized in CV pipelines, edge optimization, and drift observability—so you ship reliably, not repeatedly rework.

Vision Architect

Designs end-to-end perception systems: cameras, preprocessing, models, verification, and signal outputs.

DetectionTrackingVerification

Data & QA Lead

Builds annotation QA, taxonomy, dataset versioning, and active learning loops to handle drift.

TaxonomyLabel QAActive Learning
0.7%
False Positive Target
Production Validation Included

Squads arrive with deployment patterns, monitoring hooks, and a drift plan—built-in from day one.

Edge Optimization Engineer

Quantization, runtime tuning, and hardware-aware deployment for stable, low-latency inference.

INT8TensorRTThermal

Vision Ops Lead

Observability, confidence telemetry, drift detection, and retraining triggers with operational dashboards.

TelemetryDriftAlerts
/// Architectural Integrity

The Vision Blueprint.

Vision systems are a pipeline: capture, preprocess, infer, verify, and observe drift—built to survive real environments.

01. Capture Layer

Cameras, frames, time sync, and stable ingest for consistent inference.

Tech Stack:
RTSP • GStreamer • Time Sync

02. Preprocess

Normalization, ROI extraction, distortion correction, and calibration.

Tech Stack:
OpenCV • ROIs • Calibration

03. Edge Inference

Optimized on-device runtimes for low-latency decisions and privacy.

Tech Stack:
INT8 • TensorRT • OpenVINO
Low Latency

04. Signals + Telemetry

Events, confidence, logs, drift signals, and retraining triggers.

Tech Stack:
Metrics • Alerts • Audit Logs
Secure Signals
On-Device
Privacy-First
/// Delivery Framework

The Road to Reliable Vision.

A phased model that prevents brittle deployments: data, edge runtime, verification, then scale.

Phase 01

Environment + Data Audit

Define camera reality, edge constraints, label taxonomy, and success metrics for production.

Output: Vision Feasibility Blueprint
Phase 02

Model + Dataset Build

Train, validate, augment, and QA datasets with drift signals and hard-negative mining.

Output: Robust Model Baseline
Phase 03

Edge Optimization + Verification

Quantize, tune runtime, add confidence gating and HITL escalation paths for reliability.

Output: Production-Ready Edge Stack
Phase 04

Deploy, Observe, Improve

Ship with telemetry, drift monitoring, alerts, and a retraining loop connected to ops.

Output: Measurable Perception at Scale
/// Performance Validation

Proven Vision Outcomes.

Vision Case Archives
41%
Waste Reduced

Visual Inspection for
Manufacturing QA

Manual QA missed subtle defects during lighting variance and shift changes.

Deployed an edge-optimized inspection pipeline with confidence gating and drift telemetry.

"We stopped arguing over defect calls—confidence + review gates made it operationally trustworthy."

QA
Quality Lead
Industrial Plant
3.6x
Throughput Gain

Edge Vision for
Logistics & Yard Ops

Gate processing slowed due to manual checks and inconsistent barcode reads.

Shipped OCR + tracking on-device with stable latency and telemetry-backed improvements.

"Edge inference made it fast and private—only signals leave the site, not raw video."

LO
Ops Manager
Logistics Hub
/// Delivery Models

Vision Partnership Models.

Choose the engagement aligned with deployment speed, edge constraints, and operational ownership.

Fast Deployment

Managed Vision Squads

Embedded team specialized in CV pipeline engineering, edge runtime optimization, and monitoring.

Velocity & Reliability
SQUAD SPECS
Strategic Advisory

Fractional AI CTO

Define your vision roadmap, edge hardware strategy, data loops, and production validation plan.

Strategy & Architecture
EXPLORE ADVISORY
Build-Operate-Transfer

Build-Operate-Transfer

We incubate your CV/Edge platform, run it in production, then transfer ownership to your teams.

Platform Ownership
VIEW BOT MODEL
Scale Delivery

Vision ODC

Your dedicated CV + Edge AI delivery center for continuous improvements and multi-site deployments.

Operational Scale
EXPLORE ODC
/// Trust & Controls

Governed
Vision Decisions.

Vision systems must balance speed with error control. We embed verification and auditability so decisions are trustworthy in production.

Confidence + Verification Gates

Thresholds, region rules, and constraints before actions trigger.

Privacy-First Outputs

Keep frames local; export signals, metadata, and alerts only.

Audit Trails + Drift Monitoring

Event logs, confidence drift, retraining triggers, and versioned deployments.

Audit Logs

Traceable Runs

Privacy

Signals Only

HITL

Review Gates

Telemetry

Drift Alerts

/// Vision Briefing

See the Edge Vision Stack.

A 100-second breakdown of data QA, runtime optimization, confidence gating, and drift monitoring.

Coretus Computer Vision & Edge AI Briefing
Vision Lead
Principal Engineer
Vision Systems Lead
01:40 • EDGE MODE

Perception

Detection + tracking tuned for reality.

Edge Runtime

Stable low-latency inference on-device.

Telemetry

Confidence + drift signals + retraining triggers.

/// Vision FAQs

Frequently Asked
Vision Specs.

Service Identity
Computer Vision & Edge AI

Handling Lighting + Camera Drift?

Yes. We design dataset QA, augmentation, confidence telemetry, and drift triggers for ongoing reliability.

Edge Hardware Constraints?

We optimize for your device: quantization, runtime tuning, and thermal/memory-aware deployment.

Privacy & On-Site Deployment?

Frames can stay on-device. We export signals/metadata only with secure telemetry and audit trails.

OCR Confidence + Review Gates?

We use confidence thresholds and HITL review queues for low-risk operational decisions.

Observability & Drift Alerts?

Telemetry, dashboards, and drift alerts are built in—so you can detect regressions before they hurt ops.

Vision Feasibility?

We can deliver a 48-hour feasibility audit for your highest-impact inspection, OCR, or tracking workflow.

Request Vision Briefing

Own Your Visual Intelligence.

Stop running fragile pilots. Deploy VPC-hardened vision systems fine-tuned for edge latency, thermal stability, and 100% IP sovereignty. We bridge the gap between camera hardware and boardroom decisions.

Hardware-Aware Optimization

EU AI Act & Privacy Ready

100% Model Weight Ownership

Request Vision BriefingRequest Vision Briefing