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Case study: Kuerii Vision — a retail chain's cameras turned into business sensors
kuerii
Case study: Kuerii Vision — store cameras turned into business sensors

We build the technology your company can't find on the market.

Software, data, AI, vision, robotics and IoT — custom-designed and taken to production by the same team.

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Rotating windows from Kuerii projects: the Kuerii Vision command center for a store, an agent reconciling invoices against SAP, telemetry from a robot fleet and a demand-forecast model in training; around them, an operations alert, a deployment terminal and an edge server's event log.

Industries we work in

  • Retail
  • Manufacturing
  • Construction
  • Beverages
  • Energy
  • Logistics
  • Healthcare
  • Finance
  • [Client]
  • [Client]

Capabilities

One factory for all of your technology. Six disciplines in a single engineering team, from the first prototype to the system running 24/7.

Agents that operate, not just chat. Connected to your ERP, your documents and your systems, with permissions, audit logs and a person approving what's critical.

  • Invoice reconciliation against SAP and purchase orders
  • Internal assistants that answer from your data and cite the source
  • Supplier and customer service that escalates to people

In Kuerii Vision, an assistant answers in plain language about what each store's cameras are seeing.

Models that reach production and stay there. Data platforms, forecasting and MLOps: every model with metrics, monitoring and retraining.

  • Demand forecasting by SKU, store and day
  • Predictive maintenance from sensor data
  • Data platforms with a single version of the truth

Kuerii Vision joins people counts with point-of-sale data to measure each store's real conversion rate.

Your cameras, turned into business sensors. Edge models on the infrastructure you already own; only anonymous events travel to the cloud.

  • Footfall, queues and conversion in stores
  • Quality inspection on the production line
  • Industrial safety: PPE, restricted zones and forklifts

Kuerii Vision: a Mexican retail chain's cameras measure footfall, queues, out-of-stocks and shrink.

Plant and field, connected and measured. We integrate robots, PLCs and sensors with your operation, with real-time telemetry and alerts someone acts on.

  • Orchestrating fleets of mobile robots (AMR)
  • Line and asset telemetry with anomaly alerts
  • Plant digital twins to simulate changes

Kuerii Vision runs on edge servers inside each store and reports its own health and every camera's.

Critical systems, built around how you operate. When no product fits, we build the whole system: web, mobile and integrations, with a single team from start to finish.

  • Portals and apps for operations, field and customers
  • Integrations with ERP, POS, WMS and BI
  • Legacy modernization without stopping operations

Kuerii Vision includes the console, the daily executive report and the point-of-sale integration.

Secure networks end to end, from cloud to plant floor. We design, segment and monitor IT and OT networks, with security and privacy defined by design.

  • IT and OT network segmentation with least-privilege access
  • Monitoring, detection and incident response
  • Compliance: LFPDPPP, ISO 27001 and auditable logs

Kuerii Vision processes video inside the store and complies with Mexico's LFPDPPP by design.

How we work

From diagnosis to production in weeks, not years. We agree on success metrics before writing code and measure every phase against them.

  1. Diagnosis

    2–3 weeks

    We review processes, data and infrastructure and agree on the business case and metrics.

  2. Pilot

    8–12 weeks

    A real system on a bounded site, measured against the agreed success criteria.

  3. Production

    3–6 months

    Rollout to the whole operation with monitoring, alerts and an accountable team.

  4. Scale

    6–12 months

    New sites, modules and models on the same platform, improving continuously.

Production-grade engineering.

  • Edge & cloud

    We process where the data is born; only what's needed goes to the cloud.

  • MLOps

    Every model versioned, monitored and retrained on fresh data.

  • Security and privacy by design

    Encryption, least privilege and LFPDPPP from the architecture up.

  • High availability

    Redundancy, live monitoring and local operation if the network drops.

  • Integration with what you have

    ERP, POS, BI and installed hardware, without replacing your investment.

Architecture

From signal to decision.

Sensor

Cameras, PLCs, sensors and existing systems capture what happens in the operation.

Technologies

The platforms you already use, connected.

Leading clouds, ERPs, hardware and frameworks, without locking you into one vendor.

  • SAP
  • Oracle
  • Microsoft Azure
  • AWS
  • Google Cloud
  • NVIDIA
  • ROS 2
  • Hikvision
  • PostgreSQL
  • Kubernetes
  • Power BI
  • Python

We integrate with what you already have.APIs, ERP, POS, BI and the hardware that's already installed.

Tell us about your operation
“[Client testimonial — pending]”
[Name][Role] · [Company]

Numbers

Measurable results. Every project is measured against metrics agreed from the diagnosis.

Projects in production
[Figure]
Deployed models
[Figure]
Connected devices
[Figure]
Years of experience
[Figure]

Cases

Cases already in production. From idea to daily operation.

Retail · Computer vision A Mexican retail chain's cameras, turned into business sensors. Problem: the chain measured what happens at the checkout, but not what happens before it. What we built: a GPU server in each store analysing video from the existing cameras, with modules for footfall, conversion, queues, out-of-stocks and loss prevention, a conversational assistant and a morning report. How we delivered: diagnosis, pilot and store-by-store expansion. Privacy by design: only anonymous events travel to the cloud, in line with LFPDPPP.

Retail · Computer vision

A Mexican retail chain's cameras, turned into business sensors.

Problem: the chain measured what happens at the checkout, but not what happens before it.

What we built: a GPU server in each store analysing video from the existing cameras, with modules for footfall, conversion, queues, out-of-stocks and loss prevention, a conversational assistant and a morning report.

How we delivered: diagnosis, pilot and store-by-store expansion.

Privacy by design: only anonymous events travel to the cloud, in line with LFPDPPP.

Insights

What we're learning. Engineering notes from projects in production.

Coming soon

Retail vision without replacing cameras

How to get store metrics from the video you already record.

Coming soon

AI agents on top of your ERP

What to automate first and how to keep humans in control.

Coming soon

MLOps at the edge

Deploying and monitoring models across hundreds of remote sites.

Coming soon

OT network cybersecurity

Segmenting plant and IT without stopping production.

Your next critical system, built to fit.

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