Automate document processing with AI-powered machine learning
Hyperscience is an enterprise document processing automation platform that uses machine learning to extract and process data.
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Hyperscience is an enterprise-grade intelligent document processing (IDP) platform that automates the extraction, classification, and processing of data from a wide variety of document types. These include structured forms, semi-structured documents, and handwritten content. By applying machine learning models trained on large datasets, the platform reduces the reliance on manual data entry and accelerates document-heavy back-office workflows.
The platform is primarily targeted at large enterprises and public sector organizations that process high volumes of documents on a regular basis. Common use cases include insurance claims processing, mortgage applications, government form intake, and financial statement processing. Hyperscience positions itself as a solution for organizations looking to modernize legacy operations and reduce operational costs associated with manual document handling.
Key capabilities include automated document classification, data extraction with confidence scoring, human-in-the-loop review workflows for low-confidence outputs, and integrations with downstream enterprise systems such as ERP, CRM, and RPA platforms. The platform is designed to improve accuracy over time as its models are exposed to more data, following a continuous learning approach.
Hyperscience positions itself against legacy document-processing software; the comparison on its site draws on a G2 table against Kofax TotalAgility, ABBYY FineReader Server and IBM Datacap. It differentiates itself through a focus on pre-built machine learning models, workflow orchestration, and an emphasis on measurable accuracy and automation rates.
Deployment options include cloud-hosted and on-premises installations, which is relevant for regulated industries with strict data residency or compliance requirements. Pricing is volume-based and negotiated on an enterprise contract basis, with the unit cost per page falling as volume grows; the one listed price is a $50,000 12-month contract on AWS Marketplace.
Automatically labels, annotates, and structures complex documents to create trusted, high-quality training data for AI models.
Enables fine-tuning of large language models using proprietary business data for relevant, in-context results.
A Vision Language Model that processes documents with speed and precision comparable to human processing.
Extracts, validates, and routes freight documents to accelerate billing and driver pay within delivery-to-cash workflows.
Automates SNAP benefit processing using AI to help states meet H.R.1 mandates and reduce processing costs.
Automatically extracts, classifies, and structures data from both structured and unstructured documents including handwritten text.
Delivers 99.5% accuracy rates in document data extraction, outperforming challengers in technology evaluations.
Recognizes and extracts handwritten text from documents with high levels of accuracy.
Machine learning architecture that reads, understands, and processes a wide variety of data and documents at scale.
Integrates with existing technology stacks and downstream systems and processes to extend document automation workflows.
Ensures accuracy, security, compliance, and governance controls for enterprise-scale AI adoption.
Platform is FedRAMP High authorized, meeting federal security and compliance standards for government-scale deployments.
Hyperscience does not publish a per-page rate card; its one listed price is a $50,000 12-month contract on AWS Marketplace. The Hypercell document-processing platform is sold enterprise-first and quoted per deployment, sized on document volume, the modules in scope and the target environment — the platform is FedRAMP High authorized for federal workloads. Speak to sales for a quote.
Gartner's inaugural IDP Leader with the highest Completeness of Vision — and a sales-call-only procurement path.
“Hyperscience is an enterprise intelligent document processing platform founded in 2014, now FedRAMP High authorized and Gartner-recognized as a 2025 IDP Leader. The board-friendly proof is real, but pricing stays behind a sales call and the last disclosed round was December 2021.”
Gartner named Hyperscience a Leader in the inaugural 2025 Magic Quadrant for IDP, with the highest Completeness of Vision across 18 vendors, and the 2026 edition repeated the Leader placement, adding highest Ability to Execute among 15 vendors. That's the kind of analyst proof a board will recognize without a primer. Twelve years in, led by CEO Andrew Joiner, FedRAMP High authorized.
The ORCA Vision Language Model anchors the platform, and Hyperscience publishes a 99.5% extraction accuracy benchmark — a real number, not a marketing band. Hypercell for SNAP targets state-government workflows that UiPath Document Understanding and AWS Textract aren't packaging the same way.
The catch is the procurement motion. Beyond a $50,000 12-month contract listed on AWS Marketplace, pricing is contact-sales only, and the last disclosed round was a $100M Series E in December 2021 led by Global Founders Capital, Tiger, Stripes and Bessemer. Run a 90-day claims-processing pilot against your incumbent before signing an enterprise contract.
Hypercell for SNAP and FedRAMP High put Hyperscience ahead of UiPath Document Understanding and AWS Textract for regulated workflows.
Inaugural 2025 Gartner Magic Quadrant Leader and FedRAMP High authorization make this an easy board defense.
Enterprise contract motion with on-prem option means 8-12 week pilots, not same-quarter payback.
Directly advances back-office automation for document-heavy regulated industries rather than just trimming cost.
Twelve years in, led by CEO Andrew Joiner, a $100M Series E behind it, but no disclosed round since December 2021.
Regulated enterprises who process high-volume documents at scale.
Teams who need self-serve pricing and quick procurement.
Gartner's furthest-for-vision IDP Leader hides a CTO's procurement question behind a contact-sales pricing wall.
“Hyperscience earned Leader and furthest-for-vision placement in the inaugural 2025 Gartner Magic Quadrant for IDP, with ORCA's Vision Language Model and FedRAMP High clearing the credibility bar. But contact-sales-only pricing binds any three-year claims rollout to opaque renewal negotiations against ABBYY and UiPath.”
Gartner placed Hyperscience furthest for completeness of vision in its inaugural 2025 Magic Quadrant for Intelligent Document Processing — one of 18 vendors scored — and the 2026 edition kept that position while adding highest for ability to execute among 15. For a Head of Intelligent Automation locking a five-year claims-processing substrate, that ranking is a starting datapoint, not the answer.
The craft signal is ORCA, Hyperscience's Optical Reasoning and Cognition Agent — a Vision Language Model wired into the deterministic extraction pipeline rather than wrapped around it as a separate chat layer. The 99.5% extraction accuracy claim is honest for a vendor with FedRAMP High authorization and on-prem deployment for regulated workloads. Founded 2014; Global Founders Capital, Tiger, Stripes and Bessemer led the December 2021 $100M round.
However, the procurement gravity cuts the other way. Beyond a $50,000 12-month contract listed on AWS Marketplace, pricing is contact-sales only, which means a three-year SNAP or AP rollout negotiates against ABBYY Vantage and UiPath Document Understanding on opacity, not transparency.
Gartner placed Hyperscience furthest for completeness of vision in both the 2025 and 2026 IDP Magic Quadrants, and highest for execution in 2026.
FedRAMP High authorization and on-prem deployment match how insurance, financial services, and government back-offices actually procure.
Native Flow Blocks for SAP, Salesforce and Microsoft 365, plus the Python extensibility Forrester praised, reach downstream ERP, CRM and RPA systems.
Twelve-year category investment runway is strong but contact-sales pricing creates renewal-cycle leverage on the vendor side.
ORCA Vision Language Model plus 99.5% extraction accuracy and Gartner Leader status signal real craft ceiling.
Heads of Intelligent Automation who run regulated, high-volume document workflows.
SMB teams who need transparent SaaS pricing upfront.
Custom enterprise contracts from a $50K-a-year AWS Marketplace listing, with per-page rates only a quote reveals.
“Hyperscience runs sales-only pricing, with one PeerSpot user reporting around $1.50 per page in 2022 and a $50,000 12-month contract listed on AWS Marketplace. A $100M Series E and the double-digit revenue growth Hyperscience reports cover runway risk, but the procurement opacity is the real line item.”
Hyperscience's last disclosed round was a $100M Series E in December 2021, led by Global Founders Capital, Tiger, Stripes and Bessemer. No public per-page rate card. The one listed price is a $50,000 12-month contract on AWS Marketplace. One PeerSpot user reported roughly $1.50 per page in 2022; another called it cheaper than rival tools.
Hyperscience says the unit cost per page falls as volume scales, with tiers from hundreds of thousands of pages a year to over a billion, so treat that $1.50 as an anecdote to test in the quote, not a rate to budget on. ORCA starts without a training corpus, so push back on any services line priced for one. Hyperscience says customers regularly reach 99.5% accuracy, but that figure assumes documents already in distribution.
AWS Textract undercuts on raw extraction — under $0.05 per page at tier. ABBYY Vantage sits closer to $0.06 to $0.10. Hyperscience charges a premium for workflow orchestration and FedRAMP High. The catch: no published overage rate, so model the Year 3 invoice before signing.
Enterprise sales motion with AWS Marketplace Private Offer path; no self-serve checkout.
Typical enterprise terms with multi-year commitments; the AWS Marketplace listing is $50,000 for 12 months.
No public per-page rate card; the one listed price is a $50,000 12-month AWS Marketplace contract, and larger volume tiers need a sales quote.
99.5% claimed accuracy, 98% automation and an IDC-measured 615% three-year ROI make value measurable.
Per-page metering is forecastable at known volume, but premium versus Textract and Vantage.
Regulated enterprises who process high document volumes at scale.
Teams who need transparent per-page pricing without sales calls.
The Supervision queue runs on keyboard shortcuts, and ORCA starts extracting before anyone labels a page.
“ORCA extracts with zero training, and Supervision tasks fire when confidence drops below the per-step thresholds a flow sets. The catch is keyer discipline, since Field ID quality depends on every clerk boxing values the same way.”
Hyperscience's Field ID guidance is blunt: keyers can click field names in the sidebar, but should move field to field on keyboard shortcuts. Transcription follows suit. F9 overrides a validation in table cells; F2 is the formatting override. Keyboard-first, by design.
The queue fills when confidence drops below the target accuracy a flow sets per step — classification, field ID, table ID, transcription. ORCA extracts with zero training, and Spring 2026 added one-click deployment with a pre-built subflow. Document Drift Management clusters unknown layouts for a business user to approve in minutes. Clean output exits via native Flow Blocks into SAP, Salesforce or Microsoft 365.
The catch is keyer discipline. The docs want each field ID'd in one consistent spot, ideally top-most and left-most, because mixed choices degrade training data. Some Supervision features depend on your license package. Upside: past 1,000 documents in a dataset, the docs call extra Supervision negligible.
Supervision tasks fire below per-step confidence thresholds, and ORCA extracts with zero training, so the queue holds exceptions rather than a labeling backlog.
Per-version guides (V40 through V43) carry keyer-level best practices, like ID'ing text rather than logos, that read as operations guidance, not marketing.
Keyboard shortcuts cover field and table work, but consistent-ID discipline, license-gated features and a 2,000-character transcription field cap still shape the week.
Blocks and Flows, Custom Code Blocks and the Flows SDK take builders past no-code, and ORCA can now be trained in-app through Training Data Management.
Native Flow Blocks for SAP, Salesforce, Microsoft 365 and IBM FileNet, plus an API that feeds RPA such as UiPath, slot extraction into existing back-office flows.
Supervision leads who run high-volume keying queues in regulated back offices.
Small teams who need a published per-page rate before a sales call.
Hyperscience is built for the procurement officer at a state agency, not the team lead at a startup
“Named a Leader in the first-ever Gartner IDP Magic Quadrant with 99.5% accuracy claims and FedRAMP High. The catch is no public pricing page and a sales cycle measured in weeks.”
No pricing page at all tells you exactly who Hyperscience is selling to. Not you. Not your team lead. The procurement officer at a state agency or a top-five insurer who already has a budget line.
Once you get past the gate, the product itself is serious. The ORCA Vision Language Model reads handwriting and skewed scans with zero training — Hyperscience claims 98% accuracy on handwriting and 99.5% across customer workflows — with confidence scoring and human-in-the-loop review for the misses. FedRAMP High authorization is real work — most IDP vendors do not have it. Gartner named them a Leader in the first-ever IDP Magic Quadrant in September 2025, and again in September 2026.
But if you are not processing thousands of insurance claims or SNAP forms a month, this is wildly oversized. AWS Textract starts at a few cents a page on a credit card. Hyperscience's one listed price is a $50,000 12-month contract on AWS Marketplace, and anything bigger is a quote your finance lead has to sign off on.
Serious enterprise product, but with no public pricing page or trial workspace, daily polish is hard to judge before a sales call.
Hypercell templates for SNAP and freight pay help, but month-three is still a services-team project.
Enterprise backend processing — mobile is not a primary use case, scored neutral.
First ten minutes is a contact-sales form and a discovery call, not a trial workspace.
FedRAMP High, Gartner Leader positioning, and the 99.5% accuracy claim point to a platform built for serious workloads.
Enterprises who process tens of thousands of regulated documents monthly.
Small teams who need self-serve document extraction.
Founded 2014, $100M Series E, FedRAMP High — receipts are there, public pricing isn't.
“Hyperscience has shipped enterprise IDP since 2014 and raised a $100M Series E in December 2021, and FedRAMP High plus a Gartner Leader nod give it real federal-grade credibility. The catch is contact-only pricing with no public pricing page — buyers can't pre-validate ROI before sales gets pulled in.”
Forrester quote, Gartner Leader band, FedRAMP High. ABBYY-tier credentials in a market that demands them. Then there is no pricing page, and the only listed price is a $50,000 12-month contract on AWS Marketplace — first thing I check on an enterprise IDP vendor.
ORCA, the proprietary Vision Language Model, anchors the Hypercell Spring 2026 release with one-click deployment and no training on unseen documents. They claim 99.5% accuracy. Hypercell for SNAP targets state agencies under H.R.1. Hypercell for Freight Pay handles delivery-to-cash. Specific use cases.
But a Series E-stage cap table means investors want a liquidity path. Against ABBYY Vantage, UiPath Document Understanding, and AWS Textract, the moat is ORCA's no-training claim. Exit is reasonable — extracted JSON travels and on-prem is offered. Whether ORCA holds at enterprise scale is the watch.
ORCA's no-training claim is novel, but the field includes ABBYY Vantage, UiPath Document Understanding, and AWS Textract.
Extracted JSON travels to ERP and CRM, and on-prem deployment is offered, but model retraining locks effort into the platform.
Late-stage $100M round in 2021 and continued shipping cadence support a three-year bet, though investor liquidity pressure is real.
Gartner Leader and Forrester backing are real, but the 99.5% accuracy claim and contact-only pricing limit buyer-side verification.
Twelve years operating, a $100M Series E backed by Bessemer, Tiger, Stripes and Global Founders Capital, and FedRAMP High authorization match successful enterprise IDP patterns.
Regulated enterprises who process high-volume documents.
Small teams who need transparent self-serve pricing.
Common questions answered by our AI research team
Yes. The Hypercell ships native Flow Blocks for SAP, Salesforce, Microsoft 365, IBM FileNet, AWS S3, Google Cloud Storage and Azure Blob Storage. Its API-first design also feeds extracted data to RPA tools such as UiPath.
Yes. Hyperscience is SOC 2 Type II and Cyber Essentials Plus certified. The Hypercell platform is GDPR and CCPA compliant and holds FedRAMP High authorization for public sector workloads.
Yes. The containerized Hypercell runs on-premises, in a private tenant on AWS, Azure or Google Cloud, or as Hyperscience SaaS on AWS or Google Cloud. Air-gapped deployments are available through Google Distributed Cloud and HPE.
Hyperscience's proprietary models reach 98% accuracy on handwriting and cursive, even in low-quality scans, without manual configuration. Across document workflows, customers regularly achieve 99.5% accuracy and 98% automation.
No. The Hypercell is low-code and no-code, and business users manage the model lifecycle through an AI-guided co-pilot that suggests labels and detects anomalies. Custom Code Blocks are available for bespoke logic.
Who Hyperscience competes with, and how each one differs
Vantage runs on ABBYY's long-standing OCR/AI engine with a low-code Skill Studio for building document workflows across finance, insurance and government — a similarly broad enterprise scope to Hyperscience, but built around packaged OCR tooling rather than Hyperscience's human-in-the-loop model training.
Instabase positions itself as a foundation-model-native platform for turning unstructured documents into auditable structured data for the same large regulated enterprises (banking, insurance, government) Hyperscience targets, leaning more on LLM-based extraction versus Hyperscience's proprietary ML-plus-human-review pipeline.
Indico focuses specifically on unstructured document automation and decisioning for insurance claims and financial services — a narrower vertical slice of the same regulated-industry buyer Hyperscience serves more broadly across insurance, banking and government benefits.
Nanonets offers self-serve OCR/IDP workflow-building aimed at mid-market and SMB teams, competing on price and ease of setup rather than the enterprise-scale accuracy guarantees and FedRAMP High-authorized government deployments Hyperscience sells on.
Ocrolus specializes in financial-document verification (bank statements, pay stubs, tax forms) for lenders, overlapping with Hyperscience's mortgage- and lending-processing use cases but without Hyperscience's reach into insurance, government benefits and freight billing.
reciTAL applies NLP-driven extraction and classification to business documents for European enterprises, competing on cross-lingual document understanding — a narrower technical niche than Hyperscience's end-to-end human-in-the-loop automation platform.
Hyperscience helps you automate your document processes and turn unstructured content into structured actionable data. Find out more!
