Shaip is now part of the Ubiquity ecosystem: Same team - now backed by expanded resources to support customers at scale.
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License, de-identify, and annotate healthcare data across text, audio, imaging, and multimodal datasets—built for privacy, quality, and scale.
Over 80% of healthcare data is unstructured—spread across clinical notes, EHRs, medical dictations, imaging, and diagnostic reports. This data is powerful, but difficult to access, expensive to prepare, and highly regulated.
AI teams face critical challenges:
Without the right data foundation, even the most advanced algorithms fail to deliver impact.
Shaip solves this problem by putting data first.
Shaip is a trusted healthcare data partner helping organizations build, train, and deploy AI models using ethically sourced, compliant, real-world healthcare data.
Unlike vendors focused only on annotation, Shaip supports the entire healthcare AI data lifecycle:
This unified approach reduces risk, shortens timelines, and ensures your models are trained on data that reflects real clinical complexity.
AI-enabled systems are not going to completely replace human medical experts. But this technology will enhance their capabilities and effectiveness by automating the most repetitive activities prone to errors. At Shaip, we believe data can positively impact the health of a global population. It’s evident in our cognitive data collection, de-identification, and annotation services. We help organizations to unlock new and critical information found deep within unstructured data i.e. physician notes, discharge summaries, and pathology reports.
Then we give it structure, and purpose through natural language processing (NLP) that delivers domain-specific insights on symptoms, diseases, allergies, and medications. Now the healthcare community, through Shaip AI data, has the right insights to make better decisions that result in better patient outcomes.
High-quality, compliant data across text, audio, imaging, and multimodal AI.
Access high-quality, real-world healthcare data—off-the-shelf or custom collected—to match your exact AI requirements.
Capabilities include:
Remove PHI/PII so data can be used safely for AI training and analytics.
Key features:
Turn raw healthcare data into model-ready training datasets with expert labeling and QA.
Annotation workflows include:
Data that powers Medical AI to life
Shaip provided high-quality data for AI models in healthcare to improve patient care. Delivered 30,000+ de-identified clinical documents adhering to Safe Harbor Guidelines. These clinical documents were annotated with 9 clinical entities.
De-identify and annotate clinical documents from domain experts.
De-Identified & annotated 30,000+ documents per client guideline.
Gold Standard clinical data to develop the client’s NLP and Healthcare.
Scale data de-identification across different regulatory jurisdictions, including GDPR, HIPAA, and as per Safe Harbor.
The market value of artificial intelligence in healthcare hit a new high in 2020 at $6.7bn. Experts in the field and tech veterans also reveal that the industry would be valued at around $8.6bn by the year 2025.
Data procurement has always been an organizational priority. More so when the concerned data sets are used to train autonomous, self-learning setups.
Our medical data catalog datasets are not only massive but have gold-standard quality data. Rest assured that the data you utilize is secure, de-identified.
Empowering teams to build world-leading AI products.
Healthcare AI uses artificial intelligence to improve medical services like diagnosis, treatment, and patient management by analyzing healthcare data.
AI improves diagnosis accuracy, reduces costs, automates tasks, and provides personalized treatments, leading to better patient care and outcomes.
AI is used in medical imaging, disease diagnosis, drug discovery, remote patient monitoring, virtual health assistants, and hospital management.
AI offers personalized treatment plans, early disease detection, and real-time remote monitoring, enabling timely interventions and better outcomes.
Shaip de-identifies sensitive data, removing personal information to comply with regulations like HIPAA and GDPR, ensuring secure and ethical data use.
NLP extracts insights from unstructured medical data like physician notes, identifying symptoms, diseases, and treatments for better decision-making.
Yes, we can customize datasets based on demographics like age, gender, or ethnicity, and geographic regions to match your project’s specific needs.
Delivery timelines depend on the complexity and volume of the data requested. We work efficiently to deliver high-quality data within the agreed time frame.
We offer sample datasets or pilot projects so you can evaluate the quality and relevance of the data before committing to a larger purchase.
Pricing depends on factors like data type, volume, customization, and delivery timeline. Contact us for a detailed quote tailored to your project.
