Computer vision
Computer Vision Development Services
DartSol builds computer vision systems that read documents, detect objects, inspect products and analyze video, tested on your own images and designed with a person in the loop.
What computer vision can do for your business
OCR and document extraction
Read invoices, forms, IDs and scanned documents, and pull out the fields you need for staff to review.
Visual inspection
Flag scratches, dents, missing parts or incorrect labels on products and assets.
Object detection and counting
Detect and count items, vehicles or stock in photos and camera feeds.
Image classification and tagging
Sort and tag large image libraries, such as product catalogs or property photos, automatically.
Video analytics
Spot events in video, such as entry into a restricted area, and alert the right person.
Visual search and matching
Find similar images or match photos to records in your catalog or database.
How we build computer vision systems
Define the decision
We start with what the system should decide or extract, and what a mistake costs, so we measure the right thing.
Collect and label data
We gather representative images from your real conditions (lighting, angles, devices) and label them consistently.
Choose the approach
A ready-made vision API, a fine-tuned model or classic image processing: whichever is accurate enough at the lowest cost and complexity.
Evaluate honestly
We report precision and recall on images the model hasn't seen, including the hard cases, before anything goes live.
Deploy in the cloud or on device
Run in your cloud, on a server near the cameras, or on edge devices where connectivity or latency matters.
Keep people in the loop
Low-confidence results go to a person for review, and their corrections improve the model over time.
Privacy and responsible use
- We avoid collecting faces or other biometric data unless it's genuinely necessary for the use case
- Biometric data, such as face geometry, is regulated in several US states, including Illinois and Texas, so we flag consent and retention requirements early
- Images are stored with access controls and retention limits agreed with you
- We test across lighting, devices and conditions so performance holds up beyond the demo
- Decisions with significant consequences stay with people
How a project runs
- 1
Feasibility check
Test the idea on a sample of your images to see what accuracy is realistic.
- 2
Data and labeling
Build a labeled dataset that reflects your real conditions.
- 3
Build and evaluate
Train or configure the model and measure it against agreed targets.
- 4
Deploy and monitor
Integrate with your systems, add human review, and track accuracy over time.
Frequently asked questions
What is computer vision?
Computer vision is the field of AI that lets software interpret images and video: reading text, recognizing and counting objects, spotting defects or classifying what's in a picture. Businesses use it to automate visual checks and data entry that people currently do by eye.
How many images do we need?
It depends on the task. Some problems work well with an existing vision API and a few dozen test images; custom models usually need hundreds to thousands of labeled examples. The feasibility check tells you what your use case needs before you invest in a full build.
Can it work with our existing cameras or scanners?
Often, yes. Image quality, resolution, lighting and camera position matter, so we check sample images from your current equipment first and recommend changes only if they're needed.
Can it run without an internet connection?
Yes, models can run on local servers or edge devices near the cameras. This helps where connectivity is limited, latency matters, or images shouldn't leave the site.
How accurate will it be?
Accuracy depends on your images and how hard the task is. We measure it on images the model hasn't seen, agree target metrics with you, and route uncertain results to a person. No vision system is perfect, so we design for mistakes rather than assuming there won't be any.
Do you build face recognition?
Only where it's lawful, clearly necessary and properly consented. Many use cases, such as counting people or detecting safety equipment, don't need to identify anyone, and we'll recommend the least intrusive approach. This is general information, not legal advice.
Discuss Your Project
What happens next
- 1We review your request.
- 2We reply by email with any questions, or suggest a short call.
- 3If it's a good fit, you get a written quote for the agreed scope.
Prefer another way? Email info@dartsol.com or pick a time on Calendly (opens in a new tab).
DartSol LLC is registered in Austin, Texas, and works remotely with businesses across the United States, as well as in Canada and Australia.