Flagship product proof

CerviGuard leads the product portfolio

CerviGuard is the product path buyers should inspect first: a live workspace, current workflow screenshots, a public implementation repository, and draft regulatory material are available before qualification.

CerviGuard case history table with pseudonymous case IDs, analysis status, and TZ and lesion classifications.

Case history

Every submitted case with its analysis status and classification, from the demo workspace.

CerviGuard add-case form for uploading a de-identified cervical image with clinical notes.

Case intake

Guided intake flow for de-identified cervical-screening material and review notes.

CerviGuard workflow from structured case intake through AI-assisted and clinician review to triage and follow-up tracking.

Workflow model

From a new case through AI-assisted review to the clinician sign-off and follow-up plan.

Two directions in our healthcare AI work

Clinical analytics products

Imaging and structured-data inferential/predictive analytics for screening, triage support, and follow-up coordination.

Research and communication tools

Tools for prevention communication, qualitative questionnaire design, synthetic-data research, and aggregated insight analysis.

Offer map

Product, research, and service capabilities around CerviGuard

Flagship product

CerviGuard clinical platform

Cervical-screening workflow product with draft MDR Class I self-assessment material and clinician-reviewed AI outputs.

Live research pilot

DataGems synthetic-data workspace

Synthetic-data research workspace for schema drafting, configured generation jobs, peer-level status, and JSON/CSV exports.

Service capability

Permissioned cloud-on-edge deployment

Deployment support for healthcare AI workloads that need tenant boundaries, encryption controls, edge/on-prem execution, and traceable release records.

Service capability

Healthcare cybersecurity and resilience

Security/resilience services for healthcare organizations that can involve authorized/certified personnel, partner security products, and scoped engineering support.

Live research pilot

DataGems research track in practice

DataGems helps research and data teams shape synthetic-data workflows, test schemas, track generation jobs, and export reviewable results across distributed environments. We discuss inference configuration, job design, and output review with research and data partners.

Distributed generation workflow

DataGems can run configured generation jobs across distributed nodes in scoped research environments, with reviewable job status and exports.

Internal and external inference options

DataGems can use its internal inference path or saved external inference profiles when a scoped research workflow needs a different model.

DataGems create-a-generation-job form with schema-first workflow.

Generation job setup

Job drafting flow with schema guidance, instruction fields, and configured generation controls.

DataGems dashboard with job and record counters, shown with public-safe sample data.

Dashboard metrics

Operational overview for generated records, running jobs, failure counts, and last job timing.

Pricing, procurement, evidence, and trust context for the products above.