Image & Video Annotation
Create consistent visual training data for detection, segmentation, classification, tracking and event understanding—across individual images and long video sequences.
DetectionSegmentationTracking
Managed AI data services
Reliable data for
real-world AI.
Point AI provides managed annotation and validation across image, video, 3D, text and audio. Our dedicated neurodiverse teams deliver consistent work to your requirements, with deep expertise in complex computer vision projects.
Dedicated trained teamsQuality aligned to your criteriaBuilt around your workflow
Source data
Annotated output
Objectsboxes + classes
Reviewsecond pass
Open questions1 raised
A flexible data partner for AI teams
- AI startups
- Research teams
- Enterprise programs
- Technology partners
Services
Data annotation and validation services.
From creating new ground-truth datasets to reviewing model-generated labels, we provide the people, management and quality controls required to deliver dependable AI data.
3D & Sensor Annotation
Structure LiDAR, point-cloud and multi-sensor data for systems that need to perceive objects, movement and space.
3D cuboidsPoint cloudsLiDAR
Text & Language Data
Produce and review language data for classification, entity extraction, intent, relevance and model-response evaluation.
ClassificationEntitiesEvaluation
Audio & Speech Data
Prepare human-reviewed audio data through segmentation, timestamping, classification and transcription validation.
SegmentationTimestampsSpeech review
Data Validation & QA
Review human- or model-generated labels, correct errors and validate outputs against project-specific acceptance criteria.
Data reviewPre-label correctionQuality control
Managed AI Data Teams
Add a trained, dedicated team without adding internal management overhead. We coordinate onboarding, delivery, QA and feedback as requirements evolve.
Team trainingProject managementFlexible scale
In practice
One frame. Six ways to structure it.
The right annotation type depends on what your model has to learn. Select a type to see how the same source data is labelled — and what it is delivered as.
Axis-aligned rectangles. The fastest way to localise well-defined objects.
COCOYOLOPascal VOC
Computer vision expertise
Specialized support for the visual data that is hardest to get right.
Dense scenes, subtle class boundaries, long video sequences, 3D environments and changing conditions demand more than basic labeling. Point AI teams are calibrated to project-specific rules, raise ambiguous cases early and maintain consistency across batches.
Bounding boxes & polygonsSemantic & instance segmentationObject tracking & events
Classification & attributes3D cuboids & point cloudsPre-annotation correction
Industries
Domain-aware data services for real-world AI.
Different applications demand different annotation decisions. We adapt team training, guidelines and quality review to the context in which your model will operate.
Defense & Security
Structured visual and sensor data for systems operating across dynamic scenes, varied conditions and complex object classes.
Medical & Life Sciences
Protocol-led annotation and validation for specialized imagery and research data where consistent interpretation is essential.
Autonomous Systems & Robotics
Image, video, 3D and sensor data that helps perception systems recognize objects, understand scenes and operate in the physical world.
Aerial & Geospatial Intelligence
Annotation for drone, satellite and multi-sensor imagery across changing terrain, scale, viewpoints and sensor conditions.
Industrial & Smart Infrastructure
Structured datasets for inspection, monitoring, asset recognition, safety and automation in operational environments.
AI & Emerging Technology
Flexible support for computer vision, language AI, generative AI and multimodal programs moving from experimentation into production.
Why Point AI
Built for data that needs judgment—not just volume.
Point AI combines dedicated people, hands-on project management and structured quality controls to make complex data programs easier to run.
Partnership
Managed, not merely outsourced
A clear project owner coordinates the team, production workflow, quality review and communication with your stakeholders.
Our team
Dedicated neurodiverse teams
Team members receive professional training, supportive management and the opportunity to build lasting expertise in demanding AI data work.
Complexity
Ready for evolving requirements
Detailed guidelines, changing taxonomies and difficult edge cases are handled through calibration, documentation and clear escalation.
Quality
Quality defined for your project
Acceptance criteria, representative samples and structured review establish what good looks like before production scales.
Flexibility
Designed around your workflow
We align with your tools, formats, guidelines and delivery rhythm, keeping the data operation connected to your model-development process.
Communication
Ambiguity surfaced early
Questions and edge cases are raised quickly so decisions can be documented and applied consistently across the dataset.
How we work
From first sample to dependable production.
A focused calibration phase establishes the right interpretation before the team and dataset scale.
STEP 01
Align on data and success criteria
We clarify the use case, inputs, output format, acceptance criteria, priorities and practical constraints.
STEP 02
Calibrate on representative data
A focused pilot tests the guidelines, exposes edge cases and establishes a repeatable review approach.
STEP 03
Move into managed production
The trained team delivers in agreed batches, with quality review, feedback and requirement updates built into the workflow.
Who we are
Data infrastructure for AI, powered by neurodiverse talent.
Point AI was founded in 2019 as a social-employment venture: a data company built around exceptional professionals on the autism spectrum, delivering work that stands on its own technical merit.
Our teams are employed and trained in-house rather than sourced per task. People stay — and that is precisely why the work stays consistent. Annotators who remain on a project build familiarity with your data, your guidelines and your edge cases over months, instead of restarting the learning curve with every batch.
We work as an extension of your R&D team: adopting your workflows and tools, keeping communication direct, and raising questions early as requirements change.
Work with Point AI →Diversity is not just right—
it’s smart business.
2019Founded as a social-employment venture
30+Neurodiverse professionals on our teams
50MAnnotations delivered
EmbeddedWorking as an extension of your R&D team
Frequently asked questions
What AI teams need to know before starting.
Every program is different. These are the practical questions we resolve early so your team can move forward with clarity.
We support image, video, 3D and sensor, text and language, and audio data. Engagements can include new annotation, review of existing labels, correction of model-generated pre-labels and ongoing quality operations.
Yes. We can align the team with your preferred tools, formats, guidelines and delivery process, or help define a practical workflow when one is not yet established.
We start by understanding the model use case, data, required outputs, quality criteria and timeline. A representative pilot then helps refine the instructions and confirm the right production approach.
Quality is tied to project-specific acceptance criteria—not a generic promise. We use calibration, documented decisions, structured review and feedback to keep interpretation consistent as requirements evolve.
Yes. We can support a focused dataset or a recurring data program. The team structure, review process and delivery rhythm are matched to the scope and maturity of the project.
Start a conversation
Start with the data challenge.
Tell us what you’re building, what data you have and where the current process is getting stuck. We’ll help define a practical pilot, quality approach and delivery plan.
- Clarify scope and acceptance criteria
- Calibrate on representative data
- Build a delivery model around your workflow
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