Make every
data point count.
Smarter data workflows. Better AI.
From raw images and video to reliable AI-ready datasets, we combine advanced models, custom processing, intelligent automation and human expertise to make data production more efficient, accurate and accessible.
Built on neurodiverse talent. Driven by AI innovation.
Point AI was founded to create skilled technology careers for neurodivergent people. Today that team is the core of an AI data company working on some of the hardest data in the field.
Meet our teamFrom complex data to reliable results.
Models do the work they are good at. People decide where judgment matters. Every project is managed end to end, with the result you can check.
AI-powered data creation
Transform unstructured data into useful, structured outputs through model-assisted workflows.
How data is generated 02Intelligent automation
Combine specialised models and custom processing to reduce repetitive work.
Model orchestration 03Human-guided quality
Focus expert attention on complex cases, uncertain outputs and meaningful quality decisions.
Quality assurance 04Data management
Organise and manage datasets through coordinated operations and Point AI Studio.
Point AI StudioNot every data point needs the same workflow.
We combine processing methods, models and review strategies per project, rather than applying one fixed process.
- Raw dataImages, video, 3D or sensor data
- PrepareTask analysis, processing, model choice
- GenerateCandidate labels at scale
- EvaluateChecks, confidence, reference samples
- RouteAccept, where validatedHuman review, where uncertain or high-risk
- DeliverValidated data in Point AI Studio
Automated acceptance is used only where it has been validated for that project. Model agreement is not ground truth. See the full workflow →
One frame. Six ways to structure it.
The right output depends on what your model has to learn. Select a type to see how the same image is structured, and what it is delivered as.
COCO · YOLO · Pascal VOCDOTA · angle attributeCOCO polygons · GeoJSONPNG masks · Cityscapes · COCOPolylines · GeoJSON · OpenLABELMOT 1.1 · MOT17Practical AI, built around your business.
The same models and processing we use for training data can also run as working systems: counting, inspecting and summarising what your cameras, images and video already capture.
Your data. Organized. Accessible. Actionable.
Point AI Studio connects the data-management experience with our broader AI data operations, helping teams work with their data more effectively.
- OrganiseDatasets, projects and versions in one place, with subsets selected by class, metadata or quality.
- ReviewView images, video, 3D and DICOM with their labels in the browser; comment, approve or reject.
- DeliverFollow each batch through review and export in standard formats or through the API.
| Batch | Status | Delivery |
|---|---|---|
| batch_07 | Delivered | COCO JSON |
| batch_08 | Second-pass review | — |
| batch_09 | 3 raised for review | — |
Domain-aware data for real-world AI.
Different applications demand different annotation decisions. We adapt guidelines, workflows and quality review to the context your model will operate in.
Have a challenging data problem?
Tell us what you’re building, what data you have and what you’re trying to achieve. We’ll help identify a practical approach to processing, validation and delivery.
- Clarify the task, the data and the acceptance criteria
- Test an approach on representative samples
- Agree what is automated, what is reviewed and how it is delivered