Computer vision development services
Computer vision development: object detection and image classification, visual quality inspection, OCR and text recognition in images, video analytics, medical image analysis, and models that run on cameras, phones and edge devices, with dedicated computer vision engineers for your team or a computer vision project delivered end to end.
Computer vision systems we build
Object detection and image classification
Products, parts, vehicles, parcels and defects found, counted and sorted in photos by detectors such as Ultralytics YOLO26, RF-DETR and RT-DETR and by vision transformer classifiers, fine-tuned in PyTorch on your labelled images and scored per class on a test set agreed in advance.
Visual quality inspection
Scratches, dents, missing components and print errors caught on the production line from industrial cameras, with anomaly detection models from Anomalib where defective samples are rare, and a pass or reject signal sent to the line controller within its cycle time.
Text recognition in images
Labels, serial numbers, number plates, meter readings, handwriting and identity documents read with PaddleOCR or docTR, or with Azure Document Intelligence in Foundry Tools, Amazon Textract and Google Document AI, each field checked against a format rule and uncertain reads sent to a person.
Video stream analytics
Camera streams decoded and analysed with NVIDIA DeepStream, GStreamer and OpenCV: footfall and vehicle counts, queue lengths, safety equipment checks and zone alerts, objects followed across frames with ByteTrack or BoT-SORT, and events sent to your systems instead of hours of footage reviewed by people.
Cloud vision services
Azure Vision in Foundry Tools, Amazon Rekognition and Google Cloud Vision integrated where their ready-made labels, text detection and content moderation reach the accuracy you need, including the move off Azure Image Analysis 4.0 before its retirement in September 2028.
Segmentation and measurement
Pixel-level masks that measure size, area and shape: field boundaries and crop health in satellite imagery, wound and lesion area in clinical photos, particle size on a conveyor, with SAM 3 cutting the labelling time and a smaller segmentation model running in production.
Medical imaging models
X-ray, CT, MRI, ultrasound, dermatology and digital pathology images read from DICOM and PACS, models built with MONAI and PyTorch, results shown as overlays for a clinician to confirm, and the test evidence a software as a medical device file needs.
Vision models on devices
Models quantised and exported to TensorRT on NVIDIA Jetson, OpenVINO on Intel hardware, Core ML on iPhone and iPad and LiteRT (built on TensorFlow Lite) on Android, sized to keep up with the camera’s frame rate without sending images to the cloud.
Visual search and multimodal models
Similar-item search over product and image catalogues with CLIP or SigLIP embeddings in a vector index, and multimodal language models such as Gemini, GPT and Qwen-VL for captions, attribute extraction and checks where there is too little labelled data to train a detector.
Hire computer vision engineers
Dedicated computer vision engineers
Computer vision engineers who join your team full time, work in your tools and process, and report to your lead. You interview them; we carry the Ukrainian contract, payroll, invoicing and leave.
Computer vision development projects
A defined piece of computer vision development with a scope, a fixed plan and a named lead on our side who owns the result and reports progress in your channels.
Ongoing computer vision development
Computer vision development as a continuing service: the same people every month, a backlog you prioritise, and hours you can see in our portal and on the invoice.
The dedicated team page explains how specialists join your team, and the outsourcing page covers project delivery, take-overs and how we charge.
Who works on your computer vision development
Computer vision engineers
Detection, segmentation, OCR and model evaluation
Machine learning and MLOps engineers
Training pipelines, deployment and monitoring
Python and C++ engineers
Video pipelines and on-device inference
.NET, Java and mobile engineers
The applications that act on the model’s results
Data annotators and QA engineers
Labelled training data and test sets
From test images to the production line
A vision project starts with images from your real cameras, lighting and angles, and a test set labelled and agreed with you before any training. A pretrained model or a cloud service sets the baseline in the first weeks, so a custom model has to beat a measured number, and the measure is the one that matters on site: missed defects, false rejects or reads per hour.
In production the model is versioned with the data it was trained on, images showing faces or number plates are blurred or kept in your own cloud, and accuracy is watched for drift when a camera, a lens or the lighting changes. Hard cases collected in production go back into the training set for the next release.
Other data and AI services we provide
AI and machine learning
AI and machine learning development services: forecasting, fraud detection, recommendation systems, computer vision, NLP and speech recognition, and MLOps, with dedicated machine learning engineers or project delivery.
Generative AI development
Generative AI development services: RAG over your documents, AI agents, chatbots, LLM features, document processing, fine-tuning, evaluation and voice agents, with dedicated AI developers or project delivery.
Data engineering
Data engineering services: ETL pipelines, Spark, dbt and streaming, warehouses and lakehouses on Snowflake, Databricks, BigQuery, Redshift and Microsoft Fabric, with dedicated data engineers or project delivery.
Data analytics and Power BI
Data analytics and Power BI services: dashboards in Power BI, Tableau and Looker, product analytics, A/B testing, financial and marketing reporting, with dedicated data analysts and BI developers or project delivery.
Database development
Database development and administration services: schema design, query tuning, migrations and backups on SQL Server, PostgreSQL, MySQL, Oracle and MongoDB, with dedicated database developers and DBAs or project delivery.
Data annotation
Data annotation and labelling services for AI: image, video, text, audio and LiDAR labelling, RLHF and evaluation data, with quality control on every batch, from dedicated data annotators or project delivery.
MLOps
MLOps services and consulting: ML platforms, CI/CD for models, model registries, serving and autoscaling, GPU infrastructure, drift monitoring and LLMOps, with dedicated MLOps engineers or project delivery.
Databricks development
Databricks development and consulting: lakehouse set-up, Lakeflow pipelines, Unity Catalog, migrations, AI/BI, machine learning and cost control, with dedicated Databricks engineers or project delivery.
Snowflake development
Snowflake development and consulting: warehouse design, Snowpipe and Openflow ingestion, dbt, migrations, Cortex AI, security and cost control, with dedicated Snowflake developers or project delivery.
Kafka and event streaming
Apache Kafka development and consulting: event-driven architecture, Kafka Connect and Debezium, Flink and Kafka Streams, Confluent Cloud, MSK and Event Hubs, with dedicated Kafka engineers or project delivery.
Workflow automation
Workflow and AI automation services: n8n, Make, Zapier and Power Automate flows, AI agents in workflows, CRM, finance and document automations, with dedicated automation developers or project delivery.
Questions about computer vision development
Which industries do your computer vision engineers work in?
Manufacturing, for visual inspection and assembly checks; e-commerce and retail, for visual search, product tagging, shelf and footfall analytics; healthcare, for medical image analysis; fintech and insurance, for identity document checks and damage assessment from photos; agriculture, for crop and field monitoring from satellite and field cameras; logistics, for parcel, pallet and label recognition; and AI products where vision is the product itself.
How many labelled images do we need?
Fewer than many teams expect, because the model starts from a pretrained one: a few hundred well-labelled images per class often show whether the approach works. Rare defects, fine distinctions and many different camera set-ups need more, and anomaly detection, synthetic images and model-assisted labelling fill the gaps.
Can we ship the model in a closed-source product?
Yes, with the licences checked first. Ultralytics YOLO models are released under AGPL-3.0, so a closed-source product needs an Ultralytics Enterprise License, while detectors such as RF-DETR and RT-DETR are released under Apache 2.0. The licence of every model and library is listed before training starts, so the choice is made knowingly.
How quickly can computer vision engineers start?
When the right computer vision engineer is available, the start is gated only by your interview and the NDA and IP assignment. Otherwise we run a search, which typically produces candidate profiles within two to three weeks, and nobody starts until you have said yes.
How do we hire computer vision engineers through BigTree108?
Tell us the work, the seniority and the hours you need. We propose one or two people with their profiles, you interview them the way you would interview your own hire, and you sign one agreement with BIG TREE 108 LLC and receive one invoice a month.
Who owns the work they produce?
You do. Every specialist has a signed contract with BigTree108 that assigns all work product to the company, and our agreement with you assigns it onward. Code, designs and documents are delivered into your own repositories and tools, not kept where only we can change them.
Have images or video to make sense of?
Tell us what the camera sees, what has to be detected, read or measured, and where the model has to run. You get an answer within one business day: a plan for a proof of concept, candidate profiles, or a review of your current model.