Winter 2025 Release
Earning
Leadership
Through Relentless Innovation
At Hyperscience, leadership isn’t a given, it’s a responsibility. Being recognized as a [Leader] by top analysts validates our vision, but it’s our relentless drive to innovate that keeps us there. The Winter 2025 Release | R42 builds on that innovation momentum, introducing capabilities designed to redefine what it means to deliver AI that truly works and delivers measurable, immediate business value.
New Capabilities Enhance ORCA, Hyperscience Vision Language Model (VLM)
ORCA (Optical Reasoning and Cognition Agent), delivers day-one, zero-shot document processing with no training required - just plug it in and start extracting. The Winter 2025 Release introduces significant enhancements that reinforce its position as one of the most powerful VLMs on the market.
Supervision Location Focus: Guides users to the estimated field location, boosting transparency and trust in ORCA’s output.
Chat with Documents: An LLM block alternative that provides a GenAI experience to query, summarize, and validate information with contextual document citations. This enables users to deploy the feature in restricted or air-gapped environments without needing to call external APIs, enhancing security and deployment flexibility.
Composite Blocks: Simplify VLM workflows and speed implementation, while enabling ORCA reprocessing.
Expanded Capabilities in Redaction, Masking and Synthetic Data Generation
Hypercell automates the identification and anonymization of Personally Identifiable Information (PII) through redaction or masking with synthetic data. This capability allows businesses to protect sensitive data from potential exposure and use data for analytics and AI model training without compromising security or regulatory obligations.
Full-Page Transcription: AI transcribes all document content, including printed and handwritten text.
Intelligent PII Detection: Automatically identifies standard and complex sensitive data.
Human-in-the-Loop Supervision: Reviewers can verify all detected PII to ensure complete accuracy.
Secure Anonymization: Sensitive data is masked with synthetic data or redacted while preserving document structure.
Smarter Model Lifecycle Management
The Hypercell Model Lifecycle Management (MLM) enhancements enable implementation teams to train smarter models much faster by improving the transparency of training data and providing clearer feedback during validation. These enhancements significantly reduce the manual effort required by knowledge workers and ensure system scalability for high-volume environments.
Faster Data Tracing: Easily search by original document name in the Training Data Manager (TDM), significantly reducing time spent looking for documents that require updates.
Reduced Manual Effort in Flexible Extraction: Minimize manual keyer work by limiting Flexible Extraction tasks to only the relevant unregistered pages and fields that require human attention.
High-Volume Scalability: Dramatically improve the speed of release creation, which is critical for large customers managing many layouts.
Maximize ROI and Reduce TCO
272%
ROI over five years for 1M pages/year
$1.6M
Cost savings provided by Hyperscience vs. building on a hyperscaler platform
97+%
Accuracy achieved in model testing across four key datasets, beating out six hyperscalers & OCR providers
50%
Improvement in response latency achieved by running specialized smaller models compared to monolithic LLMs
95%
Organizations who are not getting a demonstrable return from generative AI projects.
Leader
in the 2025 Gartner® Magic Quadrant™ for IDP Solutions
(Winter 2025)
Release Summary
The Hyperscience Winter 2025 Release | R42 advances our strategy of orchestrating intelligent document process automation with unprecedented understanding, speed, and modularity. Understanding is powered by innovations in our core AI models to improve accuracy, user experience and transparency. Speed comes from platform enhancement that boost performance, optimize training cycles, and reduce manual tasks. Modularity delivers flexible infrastructure and integration options, including multi-cloud connectivity.
Read the full Release Notes
The key features of the Winter Release are grouped below according to these three central themes:
ORCA Supervision Page Location Focus
ORCA is the first VLM in the IDP market to provide Field Location Guidance, pointing a user to the estimated location of a field on a page during supervision tasks. This delivers increased transparency, accelerates supervision tasks, and provides a better user experience.
ORCA General Prompting Block
This update enables ORCA to power tasks beyond just extraction and use the VLM for specific queries like you would with ChatGPT, without defining a specific layout or using a third-party API.
Redaction & Masking
Unlock document data for AI and analytics by safely and automatically anonymizing sensitive PII for required compliance and auditability. This enables the secure use of documents for purposes like training internal machine learning models with synthetic data and providing a fast, legally compliant method for secure information sharing (e.g., FOIA compliance).
Full Support for Routing Blocks in the Flow Canvas
Improves the ability for business users to visualize and understand complex automation flows, making it clearer how documents are processed with routing logic to better reflect core business processes.
ORCA Supervision Page Location Focus
ORCA is the first VLM in the IDP market to provide Field Location Guidance, pointing a user to the estimated location of a field on a page during supervision tasks. This delivers increased transparency, accelerates supervision tasks, and provides a better user experience.
ORCA General Prompting Block
This update enables ORCA to power tasks beyond just extraction and use the VLM for specific queries like you would with ChatGPT, without defining a specific layout or using a third-party API.
Redaction & Masking
Unlock document data for AI and analytics by safely and automatically anonymizing sensitive PII for required compliance and auditability. This enables the secure use of documents for purposes like training internal machine learning models with synthetic data and providing a fast, legally compliant method for secure information sharing (e.g., FOIA compliance).
Full Support for Routing Blocks in the Flow Canvas
Improves the ability for business users to visualize and understand complex automation flows, making it clearer how documents are processed with routing logic to better reflect core business processes.
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