Hyperscience Hypercell extracts and classifies data from forms, handwriting and unstructured documents, routing to human QA or supervision only fields falling below a customer-defined accuracy SLA.
SOC 2 Type II (annual independent audit, attestation; auditor not named); FedRAMP High authorization for SaaS via Palantir FedSTART; TX-RAMP Level 2; Cyber Essentials Plus (independent technical audit, assessor not named)
ISO 27001 statement refers to AWS/GCP data centres (hosting provider's certificate, not vendor's own). HIPAA is a law, not a certification. Not registry-verified
Additional data conditions
Subprocessors and underlying models
Sub-processors: AWS, Google Cloud Platform, Palantir (cloud infrastructure: documents, transcriptions), Atlassian (support), Okta (identity); models: "proprietary AI and LLMs" plus integration with enterprise LLMs; Claude/Amazon Bedrock and Gemini 1.5 Flash / 2.5 Pro mentioned
The provider’s own sources say different things here. audit retention from https://help.hyperscience.ai/deployment/docs/audit-log-v391-and-later; that page says 'retention period cannot exceed 180 days' yet admins with advanced permission may set longer — internal inconsistency
Signals: "Industry Leading Enterprise AI Platform"; customers incl. American Express, Charles Schwab, MetLife, Volkswagen, US Social Security Administration; federal, state and local agencies
"You define a specific Accuracy SLA as a required input"; "The system only surfaces the specific fields or single characters where the model falls below your SLA"; QA and Supervision task types
Transparency blog: 'Human validation is integrated at key points, especially when model confidence is low'. Accuracy claim provider-stated evidence only: 'Customers regularly achieve 99.5% accuracy and 98% automation'
Audit logging
Audit Log records "actions taken in Hyperscience" incl. settings changes, model training, flow deployments, "Submit a response for a Supervision task"; each entry marks machine or human operator with old/new values
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