Shaip Expands Genai Data Capabilities Amidst Growing Demand For Stable, Scalable Partners

Shaip scales GenAI data capabilities with multi-modal, gold-standard datasets to meet rising demand for reliable, enterprise-grade AI solutions.

With AI evolving rapidly, companies are rethinking how they source training data,” said Hardik Parikh, Co-Founder & CRO, Shaip. “We built Shaip to deliver trusted, scalable data solutions.”

— Hardik Parikh, Co-Founder & CRO, Shaip

LOUISVILLE, KY, UNITED STATES, June 24, 2025 /EINPresswire.com/ -- As the AI industry undergoes rapid evolution, organizations are increasingly seeking dependable, enterprise-grade partners to power their GenAI strategies with high-quality, diverse, and scalable training data. In response, Shaip is significantly expanding its data infrastructure and offerings—fortifying its position as a leading provider of secure, multi-modal AI datasets and end-to-end GenAI services.

Shaip’s platform is purpose-built for enterprise AI and offers:
- Multi-modal data coverage across text, audio, image, and video
- End-to-end GenAI services, including RLHF, prompt ranking, summarization, alignment, content comparison, and QA workflows
- A global workforce of 500,000+ trained annotators, fluent in 50+ languages and specialized across healthcare, legal, technical, and conversational domains.

Shaip also offers a readily available, gold-standard dataset across key GenAI domains:
- Healthcare: 30M+ de-identified patient notes across 30+ specialties, 280K+ hours of doctor-patient conversations, 30K+ clinical documents with entity and relationship annotations, and over 1M medical images (MRI, CT, X-rays)
- Conversational AI: 140K+ hours of speech data in 70+ languages, including wake-word detection, IVR, scripted and spontaneous speech, utterances, TTS, and multi-speaker interactions
- Computer Vision: 60K+ food and document images, and 50K+ facial recognition and anti-spoofing datasets

“With the AI landscape evolving so quickly, companies are re-evaluating how they manage and source critical training data,” said Hardik Parikh, Co-Founder and CRO of Shaip. “We’ve built Shaip to be the go-to data platform for organizations that demand transparency, compliance, and precision—at scale.”
Shaip’s AI data platform empowers teams to accelerate development timelines, enhance model accuracy, and maintain control over sourcing, quality assurance, and delivery—all with full auditability and enterprise-grade security.

Companies looking to enhance or stabilize their GenAI data pipelines can engage with Shaip through customized pilots and domain-specific solutions designed to support responsible, scalable AI development.

To learn more or request a demo, visit www.shaip.com.

About Shaip
Shaip enables responsible AI development through high-quality training data across text, audio, image, and video. From data licensing and collection to annotation and synthetic data generation, Shaip supports enterprises in building accurate and ethical AI models across healthcare, legal, financial, and tech sectors. Headquartered in Louisville, Kentucky, Shaip is trusted by Fortune 500 companies in over 60 countries.

Anubhav Saraf
Shaip
+1 866-473-5655
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EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.

Frequently Asked Questions

What types of data does Shaip provide?

Shaip provides multi-modal data coverage across text, audio, image, and video.

What services does Shaip offer for GenAI?

Shaip offers end-to-end GenAI services, including RLHF, prompt ranking, summarization, alignment, content comparison, and QA workflows.

What industries does Shaip support?

Shaip supports industries like healthcare, legal, financial, and tech with specialized datasets and services.

First published on Tue, Jun 24, 2025

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