AI Data Services

Your Models Need Data They Can Trust.

CapeStart prepares, labels, annotates, and validates the data your AI and machine learning models depend on. Our integrated team of analysts and subject-matter experts delivers accurate, quality-checked datasets across text, image, audio, and video, at the scale your project needs.

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AI Models Need the Right Data to Work

Machine learning models learn from the data you give them. When that data is incomplete, inconsistent, or poorly labeled, accuracy suffers, and no amount of tuning fully makes up for it. Preparing and annotating large, high-quality datasets is slow, specialized work, and it is rarely the best use of your team's time.

CapeStart is the annotation partner that turns your raw data into clean, accurately labeled datasets your models can learn from. When real-world data is limited or difficult to obtain, our synthetic data services help fill critical gaps and support AI model development.

If any of this sounds familiar, this service is built for you:

You have large volumes of unstructured data that need to be prepared for AI or ML.
Your AI models need more diverse, representative data, including synthetic datasets to address gaps and rare scenarios.
Your team needs accurate annotation across text, image, audio, video, or documents.
Your internal experts do not have the time to review and label every data point manually.
You need quality checks, clear guidelines, and scalable workflows before moving into model training or evaluation.

How We Prepare Data for Your AI Models

CapeStart supports general AI data annotation, specialized medical image annotation, and synthetic data generation, with solutions tailored to your data requirements and quality standards.

Data Annotation Services

Image, text, document, video, and audio annotation across the modalities your models need, from bounding boxes and semantic segmentation to named entity recognition, transcription, and document fields.

 Build AI-Ready Datasets

Medical Image Annotation

Specialized clinical annotation by a team that includes radiologists and radiologic technologists, across CT, MRI, X-ray, mammography, ultrasound, and ophthalmic images, including OCT and Fundus images.

Annotate Clinical Images

Structured Data Workflows, Built Around Your Model Requirements

CapeStart does more than label data. We build the annotation workflow around your model objective, data type, quality requirements, and review process. From the first sample to final delivery, our teams define clear labeling rules, calibrate reviewers, run quality checks, and keep feedback built into the workflow.

How We Work
01
Data and Requirement Review
We review your sample data, model objective, annotation scope, labeling requirements, validation needs, and preferred delivery format.
02
Guideline and Workflow Setup
We define annotation rules, reviewer instructions, quality criteria, escalation paths, and project documentation so the team works from a consistent standard.
03
Sample Annotation and Calibration
We annotate a sample dataset for your review, then use your feedback to refine labeling parameters, instructions, and quality expectations before scaling.
04
Scaled Annotation and Quality Control
Our trained analysts and subject-matter experts scale the annotation workflow with multi-level quality checks for accuracy, consistency, and completeness.
05
Delivery and Sign-Off
We deliver quality-checked datasets in the required format, support review and sign-off, and adjust the workflow if additional batches, edge cases, or model feedback require refinement.
Why Capestart

Annotation Built for Model Performance

End-to-End Solutions

End-to-end data preparation, synthetic data generation, annotation, enrichment, validation, and quality control tailored to your AI and ML needs.

Precision and Quality Control

High-quality annotations supported by multi-level quality checks for accuracy, consistency, and reliability.

Built to Scale

From small pilot projects to millions of assets, with workflows designed to maintain quality as volume increases.

Industry-Specific Expertise

Domain-trained experts who annotate to the standards and context of your industry.

Data Privacy and Security

Strict security protocols help keep sensitive data protected and confidential throughout the project.

Structured Workflows for AI-Ready Data

Our annotation and validation workflows are designed to deliver quality-checked datasets in formats that fit your machine learning, AI training, and evaluation pipelines.

Workflow

In-house annotation and validation workflows built around project-specific guidelines, reviewer instructions, and escalation paths

Modalities

TextDocumentsImageAudioVideo

Quality

Multi-level review, validation, calibration, and sign-off processes

Exports

JSON, CSV, and project-specific formats ready for downstream ML workflows

Security

Controlled access, confidentiality practices, and secure handling of sensitive data

Don’t See Your Workflow?

We align annotation, review, delivery, and export formats to the way your model team works.

Questions Teams Ask Before They Start

How do you make sure annotation quality is consistent across large datasets?

We start with clear labeling guidelines, reviewer training, and sample calibration. As the project scales, multi-level quality checks help maintain consistency, accuracy, and reliability across the dataset.

Yes. CapeStart works with trained analysts and subject-matter experts for projects that require domain understanding, including healthcare, financial services, telecom, retail, legal, and medical imaging use cases.

Yes. You can share a sample dataset and your requirements. We annotate a sample at no cost, so your team can review the quality, provide feedback, and confirm the approach before scaling.

We annotate text, documents, images, audio, and video. This includes bounding boxes, polygons, segmentation, named entity recognition, document fields, transcription, speaker labels, event tags, and timestamps.

Yes. Our medical image annotation work is supported by a team that includes radiologists and radiologic technologists across CT, MRI, X-ray, mammography, ultrasound, OCT, and Fundus images.

We use controlled workflows, access management, confidentiality practices, and security protocols to help protect sensitive data throughout the project.

We deliver quality-checked datasets in the formats your models and workflows require, including JSON, CSV, and project-specific formats.

Yes. Many projects begin with a sample or pilot dataset. Once the labeling rules and quality expectations are confirmed, we scale the team and workflow to handle larger volumes while maintaining review and quality-control steps.

Ready to Train Your Models on Better Data?

Share your sample data and requirements with us. We will prepare a small sample annotation, so you can review the quality before moving forward.

Talk to Our Experts

Tell us what you’re trying to achieve, and we’ll get back to you.