Hyperscience Reviews
Extract, classify, and structure data from complex handwritten and digital documents with 99.5% machine learning accuracy for enterprise workflows.
Companies using Hyperscience
American ExpressCharles SchwabMetLifeMutual of OmahaStrykerVolkswagenHirschbach Motor LinesDISA Global SolutionsCalifornia Dept. of CorrectionsMissouri Dept. of Social ServicesUS Social Security AdministrationUnited States Veterans Affairs
Enterprise organizations handle massive volumes of unstructured content daily, ranging from handwritten claim forms and tax records to multi-page contracts. Traditional optical character recognition software frequently fails on messy layouts, poor image quality, and cursive writing, leaving operational teams stuck with costly manual data entry.
Hyperscience replaces these manual bottlenecks with a machine learning platform built to read, classify, and extract data at 99.5% accuracy. Designed specifically for high-volume operational environments in finance, insurance, healthcare, and government, it converts complex incoming files into clean, structured datasets that feed directly into business workflows and enterprise generative AI systems.
- Proprietary ML Extraction: Reads machine-printed text, poor-quality scans, and challenging handwriting across structured and unstructured documents.
- GenAI Data Preparation: Labels, annotates, and structures complex document sets to provide clean, trusted context for fine-tuning enterprise language models.
- Human-in-the-Loop Review: Automatically flags edge cases and routes low-confidence fields to human operators, continuously training underlying models with verified inputs.
- Enterprise Security: Backed by FedRAMP High authorization, SOC 2 Type II compliance, and role-based access controls to safeguard sensitive customer data.
- Workflow Extensibility: Integrates cleanly into existing core systems, ERPs, and automation platforms through flexible APIs and Python-based custom tooling.
Hyperscience Key Features
- High-Accuracy Document ProcessingReads, understands, and processes diverse documents at scale with up to 99.5% accuracy.
- FedRAMP High Compliance & SecurityMeets strict enterprise and public sector security standards with FedRAMP High authorization.
- GenAI Training & Data StructuringAutomatically labels, annotates, and structures complex documents to create high-quality data for AI models.
- Proprietary LLM Fine-TuningFine-tunes large language models using internal business data for relevant, in-context results.
- Downstream System IntegrationEasily extends and integrates into existing enterprise tech stacks and workflows.
- Unstructured & Handwriting RecognitionClassifies and extracts accurate data from unstructured documents and handwritten text.
Company
Founded2014
Based inNew York, USA
OwnershipPrivate
Total raised$288M
Latest roundSeries E · 2021
Notable investors
Tiger Global ManagementBessemer Venture PartnersStripesFirstMark CapitalBattery VenturesFelicis
