We build computer vision into products people actually use. We've shipped apps that read license plates, ID cards and utility meters straight from a phone camera, and others that capture and analyse skin to give people advice made for them. We also build the whole product around the vision part: the capture experience, the pipeline, the review and the storage.
Computer vision is the field of AI where software perceives and analyses images and video, turning pixels into structured information you can act on. It's one part of our wider AI development services, and a different job from generative AI. Here's the line between them.
Reads and interprets what's already in front of the camera: it detects and locates objects, classifies what's in a frame, segments an image into regions, tracks things across a video, and reads text off real-world surfaces with OCR. It turns pixels into structured information you can act on.
Creates new content instead, such as text, images or code. The two often live in the same product, and we build both. It makes something new, which is the content-generation side.
OCR and camera scanning
Read text, IDs and codes straight from a live camera: license plates, ID cards, passports, VINs, and gas, water and energy meters. We built the Anyline mobile apps for police forces and utilities around exactly that, wiring in a specialist OCR engine so field staff scan instead of type. That's OCR software development we took all the way to launch.
Document AI and intelligent extraction
Turn scanned or photographed documents into structured, checked data: OCR the page, classify it, pull the fields, score each one for confidence, and flag where documents disagree. We've built this as a working prototype and review flow. It runs OCR and an LLM classifier over document images, with per-field confidence scoring and automatic conflict detection, and a person can check and correct the output before it's accepted.
Camera-based health and skin analysis
Capture high-resolution images through a phone and a clip-on lens, analyse them on the spot, and give the user advice made for them. We built No7 Pro Derm Scan for Walgreens Boots: an iOS app paired with a smart lens that runs image-based skin analysis, identifies skin conditions, matches products, and lets people compare their scans over time.
Video analytics and event platforms
Ingest, store, filter and report on a stream of camera events in real time, and control recording by rules such as location. We've built the platform side of a fleet video system: real-time video analysis events flowing in from in-cab cameras, with the recording, filtering and reporting built around them.
Image recognition, detection and classification
Object detection development, image classification and image segmentation services for product and workflow features: recognising and locating what's in an image so the rest of your product can act on it. When a project calls for it, we build the capture, the pipeline and the workflow around a suitable vision model. It's part of our wider AI development services.
Image processing pipelines
On-device colour and image pipelines: white balance, curve adjustments, HDR, portrait handling. AI image processing services for products where the job is transforming the image itself, not reading content out of it.
From a single scanning feature to a full camera product, our custom computer vision solutions cover the whole path: scoping the visual signal, then capture, pipeline, review and launch. We build so the vision feature ends up as part of a product that holds up in real conditions.
Get in touchMobile apps that grab plates, IDs, passports, VINs or meter readings from the camera, so there’s no manual data entry and none of the errors that come with it.
Apps that pair a phone with a lens or device to capture images, analyse them, and hand the result back to the user with a clear recommendation.
Tools that photograph or upload documents, extract the fields, and put a person in the loop to check and correct the output before it’s accepted. Confidence highlighting flags the uncertain bits, and manual entry is there as a fallback so staff are never blocked.
Platforms that take a live feed of camera events, store and filter them, line them up against location and time, and turn them into reports.
Features that recognise or classify what a user points a camera at, so your product can score, sort or route it automatically.
Measuring and dimensioning objects from images using reference points in the frame. This is emerging work, and accuracy depends on the conditions, so we scope it honestly with you up front instead of promising a fixed number.
01
Scope the signal and the accuracy you need
02
Choose the approach and cost it
03
Build the capture, the pipeline and the review
04
Evaluate, harden and launch
Scope the signal and the accuracy you need
We start by pinning down what has to be detected or read, and to what precision. A job that can tolerate a couple of millimetres and one that needs pinpoint accuracy are two different builds, so that precision target shapes everything that follows.
Choose the approach and cost it
We pick the approach that fits the accuracy target, whether that’s an existing vision or OCR engine or something more bespoke. We estimate the model and storage costs up front, and we work out a sensible storage strategy for large volumes of images or video, so nothing surprises you later.
Build the capture, the pipeline and the review
We build the capture experience on the device, the extraction step that runs OCR or a vision model, and the layer that structures and validates the output: classification, per-field confidence scoring, and conflict detection. Where a person needs to check the result, we build a review flow, source image on one side, extracted data on the other, with confidence highlighting, correction and a manual fallback.
Evaluate, harden and launch
We evaluate the output and store results against the right record, with time and location, so they can be compared later. Then we harden the product for its setting, including regulated-industry requirements where they apply, before it goes live.
Vision features fail in ways ordinary software doesn't. A model can be confidently wrong on an unusual image, and the images themselves are often sensitive: faces, documents, IDs, medical data. We plan for both.
We're upfront about accuracy. We set the expectation with you at the start, test against real benchmarks, and design the product to cope when the model is unsure instead of assuming it never will be. Where the output feeds a decision, we build a human review step so a person can check and correct it before it's accepted. Sensitive images are handled under ISO 27001 practices and GDPR, with privacy built into the architecture and a storage strategy that fits the data instead of being bolted on later.
AWS
AWS Bedrock (Claude)
Anyline OCR
Cloudflare R2
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COO & CTO @ Equality AI
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Krisztina Orosz
Chief Experience Officer, Anyline GmbH
From the first day, Wolfpack was extremely committed, reliable and delivered solutions in outstanding quality. I also enjoyed that the Wolfpack team made lots of very useful suggestions and deeply cared about our company. Working with Wolfpack feels like working with your own team.
Axel Heinz
CEO and Founder of Makerist
They nicely replicated our brand elements into the design without much input from us. They had good ownership and delivery of the agreed tasks. Their help was essential in allowing us to focus on core back-end functionality with our in-house team. Wolfpack Digital was willing to adapt to our needs and learned the specific technologies we wanted to use on the project.
Tibor Barna
CTO at GoodBox
The highly functional app has drawn enough users to make up 20% of the customer base across platforms. Wolfpack Digital is a communicative and reliable team that’s easily capable of integrating with the in-house development team. We communicated well. They responded to us rapidly, demonstrating their understanding of our business and any errors we might face.
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CTO at FirstAgenda
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Raymond Valentine
CEO at FlexiDrive
Working with Wolfpack Digital has been a blast. Gina and her team are very product-oriented and made sure they understood our needs before diving into building the app. This upfront effort paid off by meeting the deadline weeks ahead of schedule.
Flaviu Simihaian
CEO and Co-founder of Amplicare
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Chen Lev
CEO at Storyball
Wonderful culture with the company and people. Incredibly professional, competent, and knowledgeable.
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Founder @ Pearls
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CTO @ BrainCapture
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Product Owner @ Novum Bank
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CEO @ Amara Therapeutics
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