Gleam
Provider of a browser-based data-entry assistant for clinical research sites that reads source data in the browser, maps and fills EDC case report form fields, and maintains traceability back to source. The product is designed for deployment without custom integrations, uses AI/ML to learn CRF structure and improve over time, and is built to keep a qualified human in control of final data submission.
Industries
Nr. of Employees
small (1-50)
Products
Browser-based data-entry assistant
A browser extension that learns CRF pages, fetches source data, maps values to EDC fields, stages entries for human review, and links each value back to its source for verification and audit.
Gleam
An intuitive browser-based data-entry assistant for clinical research sites that learns the EDC, fetches eSource, fills CRFs, and traces back every step for quality control.
Browser-based data-entry assistant
A browser extension that learns CRF pages, fetches source data, maps values to EDC fields, stages entries for human review, and links each value back to its source for verification and audit.
Gleam
An intuitive browser-based data-entry assistant for clinical research sites that learns the EDC, fetches eSource, fills CRFs, and traces back every step for quality control.
Services
30-minute tailored demo and Q&A, including a walkthrough video and discussion of compliance and costs to evaluate how the assistant fits site workflows.
30-minute tailored demo and Q&A, including a walkthrough video and discussion of compliance and costs to evaluate how the assistant fits site workflows.
Expertise Areas
- Clinical trial data entry automation
- EDC and eSource interoperability for site workflows
- Human-in-the-loop AI for clinical data
- Audit trail and electronic records compliance (21 CFR Part 11, ICH GCP guidance)
Key Technologies
- AI-assisted data extraction
- Browser-extension automation
- Machine learning for form understanding
- Document parsing for PDF/paper sources (planned)
News & Updates
Discussion of limitations of manual transcription and criteria a tool must meet to replace manual data entry at research sites; argues for human-reviewed automated assistance that reads any source and fills any EDC.
Explains regulatory perspective: tools that are fit for purpose and keep a qualified human accountable are consistent with 21 CFR Part 11 and ICH GCP; describes validation and audit expectations.
Design principles describing the product team's emphasis on usability and workflow-focused details to make clinical data-entry work less burdensome.
Article on the importance of verifiable, reviewable suggestions and maintaining user control to build trust in automated data-entry assistance.
Discussion of limitations of manual transcription and criteria a tool must meet to replace manual data entry at research sites; argues for human-reviewed automated assistance that reads any source and fills any EDC.
Explains regulatory perspective: tools that are fit for purpose and keep a qualified human accountable are consistent with 21 CFR Part 11 and ICH GCP; describes validation and audit expectations.
Design principles describing the product team's emphasis on usability and workflow-focused details to make clinical data-entry work less burdensome.
Article on the importance of verifiable, reviewable suggestions and maintaining user control to build trust in automated data-entry assistance.