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TransPerfect Automate is a purpose-built AI platform for Trial Master File (TMF) operations. It classifies documents, extracts metadata, and runs completeness and quality checks directly inside your eTMF, operating in a validated, locked-state configuration designed for regulated life sciences environments. The result is faster document handling, consistent metadata, and inspection-ready documentation, without disruption to established TMF workflows.
Performance across TMF document types, drawn from production deployments
Document types classified automatically (CDISC reference model)
TransPerfect Automate is powerful AI solution that eliminates the manual process of classifying documents to the TMF Index — reducing misfilings and driving eTMF automation across TMF management.
Automated, controlled document workflows that move records through classification, review, and filing without manual handoffs
Automatic metadata extraction and coding - 35+ fields per document, including site, country, investigator, study, dates, and protocol number
Document type identification and metadata configuration matched to each document type
Pre-trained on the CDISC reference model - 1,079 document types at the sub-artifact level covering ~100% of typical TMF structures out of the box, with no training required
Language-independant processing across 40+ languages
Confidence threshold that let's high-confidence document skip manual indexing completely, while lower-confidence documents route to human review
Classification & Metadata Extraction
Pre-trained on 1,079 document types using the CDISC reference model, Automate classifies at the sub-artifact level and extracts 35+ metadata fields per document — with no training required. Processing is language-independent across 40+ languages and covers approximately 100% of typical TMF structures out of the box.
Confidence scoring & quality control
Every document receives a confidence score with a rationale for its classification. Configurable thresholds let high-confidence documents auto-progress while lower-confidence or ambiguous documents (such as correspondence) route to human review. A Quality Score is generated per document type based on AI versus human validation.
Validated, locked-state AI
The model version, prompts, thresholds, and mappings are fixed and version-controlled, with a configuration fingerprint recorded in the audit trail for every processed document. There is no self-learning in production — all updates flow through formal change control and revalidation, supporting 21 CFR Part 11, EU Annex 11, and GAMP 5 validation principles.
Human-in-the-loop governance
Oversight is configurable to your risk tolerance. Reviewer corrections trigger a feedback loop that reprocesses and revalidates against document content and rules, and the full audit trail distinguishes metadata populated by Automate from metadata entered by a person. Users can review, override, and validate AI outputs at any step.
A document arrives in the TMF via inbox, upload, integration, or email
Automate detects new documents and initiates processing
Classification, metadata extraction, and confidence and quality scoring
Results map automatically to the configured TMF fields
The document auto-progresses, goes to QC review, or enters a review queue based on your thresholds
Automate is deployed inside a HITRUST-certified hosting environment and operates under a validated system lifecycle. Many newer AI tools are not yet operating in validated, regulated environments — a baseline expectation for most life sciences organizations.
Automate is purpose-built for TMF workflows: the CDISC reference model, eTMF taxonomy, metadata relationships, and regulatory and quality document types. This domain focus consistently outperforms generic document AI on TMF content.
Automate has been running in production for close to two years on real TMF workflows, with operational performance data, real-world edge-case handling, and proven scalability into thousands of documents per hour.
