Computer vision integration, from the camera to the decision
The model is rarely the hard part of a computer vision project any more. The hard part is everything around it: cameras that produce different images at night, inference that must run on the device because the uplink cannot carry video, a result that has to land in a workflow where a person or a system acts on it, and a way to know when accuracy drifts after the lighting changes. We do the integration, which is where most vision projects actually stall.
Who this is for
- - An operations, manufacturing or logistics business with cameras already installed and no system acting on what they see.
- - A product team that needs a vision feature inside its app: document capture, measurement, inspection, identification.
- - A team deciding between a general vision API and a custom model, and needing a rule rather than a sales pitch.
- - A deployment where video cannot leave the site and inference must run on the edge.
What you get
- - A decision, with evidence, on general vision API versus custom model for your images, before any training.
- - The pipeline from camera or upload to result: capture, preprocessing, inference, post processing, delivery into your workflow.
- - Edge or cloud inference chosen on bandwidth, latency and cost, not habit.
- - An accuracy threshold agreed in advance, measured on your images, with the drift monitoring to know when it slips.
- - Models, pipeline and evaluation data in your accounts.
What it costs
There is no honest fixed price before discovery, and anyone who gives you one is guessing. What we can say in writing after two weeks: the build cost, the running cost per month at your expected volume, and what moves each. The build is driven by how many systems the work must touch and how strict the accuracy, latency and compliance bars are. The running cost is model calls plus infrastructure, and it can differ by ten times depending on the choices made in week one. How we price AI work.
How long it takes
Discovery, two weeks: we map the problem, the systems involved and the success criteria, and put the numbers in writing. Pilot, four to six weeks: one capability, live, on a slice of real traffic, measured against those criteria. Then production hardening and scale out. Each stage is a separate agreement with no minimum commitment, so you can stop after discovery with a plan you own. How we work.
What you own afterwards
Everything. The code, the prompts, the evaluation set, the infrastructure configuration and the documentation, in your accounts, under your name. We do not hold anything hostage and we do not license our own platform to you. The evaluation set matters most: it is the thing that lets your team, or any other team, change the system later without breaking it. The deliverables clause.
Questions buyers ask
What do computer vision integration services include?
Everything between the camera and the decision: capture and preprocessing, choosing and running the model, post processing, delivering the result into the workflow that acts on it, and monitoring accuracy so drift is caught. The model itself is usually the smallest part of the work.
Should we use a vision API or train a custom model?
General vision models are remarkable at describing images and weaker at measuring them. If the task is description or classification of ordinary scenes, start with an API. If it is measurement, defect detection, or anything with a tight accuracy threshold on your specific images, a custom model usually earns its cost. We test both on your images before recommending.
Should inference run on the camera or in the cloud?
On the device when the uplink cannot carry video, when latency must be near instant, or when video may not leave the site. In the cloud when models change often, when the fleet is small, or when the result is not time critical. Most real deployments split: a small model on the edge decides what to send, the cloud handles what needs it.
How long does a computer vision integration take?
Discovery takes two weeks and includes a test on a sample of your images, which answers the API versus custom question. A pilot runs four to six weeks on one camera or one document type with a measured accuracy threshold. Production and fleet rollout follow. Each stage is a separate agreement.
Before you decide
If you want the technical background first, read how computer vision works and integrates. Then, from our engineers:
Send us a sample of your images
Two weeks of discovery puts the cost, the timeline and the plan in writing before you commit to anything. Or start with the free audit.