04

Vision and edge

Inventory and asset vision

Count, locate, classify, and flag inventory or equipment states from fixed or mobile imagery.

Primary buyer: Warehouse, retail, and industrial operations teams
01Primary buyerWarehouse, retail, and industrial operations teams
02Target outcomeMore frequent asset visibility and faster exception discovery
03Useful starting pointAsset classes, camera or capture path, location geometry, update frequency, exception definition, and truth samples.
01

The real constraint

Camera position, lighting, occlusion, privacy, hardware, and field maintenance can matter more than model choice.

02

How we approach it

We define zones, events, error costs, edge/cloud boundaries, review, and installation ownership before scaling cameras.

03

How we prove it

Representative footage is segmented by difficult conditions and evaluated against the operator decision it supports.

Production system

Vision and edge

Images and video converted into measurable events, quality evidence, and operational decisions.

  • 01Camera and scene specification
  • 02Detection, segmentation, and tracking
  • 03Zone, event, and temporal logic
  • 04Edge inference and secure transport
  • 05Operator review, alerts, and drift checks

Typical fit

More frequent asset visibility and faster exception discovery

IndustriesRetail / e-commerceLogisticsManufacturing
TechnologyComputer visionEdge inference

FAQ

Questions before a pilot

01Do we need perfect data before starting?

No. Discovery establishes whether representative data exists, what quality gaps matter, and the cheapest evidence needed before a production promise.

02Can Tandemora own the complete implementation?

Yes. Scope can include product interface, models, data, cloud, integrations, observability, deployment, and handover, with specialists added when the system requires them.

03How is pricing determined?

Uncertain work begins with a bounded paid discovery or pilot. Production is priced after evidence clarifies data, integration, quality, operations, and ownership.

Service focus

Computer Vision Inventory Management Solutions

Count and monitor inventory, pallets, and equipment states from fixed or mobile imagery with truth samples and explicit exception rules.

Built for
Warehouse, retail, and industrial operations teams
Designed to achieve
More frequent asset visibility and faster exception discovery

Related delivery scope

  • inventory counting with computer vision
  • vision-based inventory monitoring
  • warehouse asset tracking
  • AI pallet counting

Need a different system?

Not quite your solution?

Explore nearby systems or bring the outcome, workflow, and constraints that do not fit a predefined category. Tandemora can scope a custom solution around the real operating problem.

Your version will have different constraints.

Bring the workflow, current system, available evidence, and the assumption you trust least. We will identify the smallest useful next step.

Discuss this system