LumeSage / Company introduction
Company introduction · LumeSage
LumeSage is the medical and life sciences AI data services brand of Beijing Langhui Technology Co., Ltd. We organize task definition, source and permission verification, expert production, quality review and version evaluation around shared delivery criteria for research, business and procurement teams. Data availability, expert staffing and processing environments are verified and agreed per project.
LumeSage / Our mission
Our mission
Verifiable specialist data, expert production and ongoing evaluation for medical and life sciences AI teams.
Turn specialist knowledge into trustworthy AI capabilities, with a sound basis for developing and continuously improving medical and life sciences AI.
Put the mission into every delivery
- Traceable sources and permitted uses
- Check provenance, lawful processing basis, training use, retention and redistribution. De-identification does not replace authorization.
- Reviewable expert judgments
- Specify expert fit, review, sample denominators, disagreement resolution, rework and acceptance records.
- Comparable model versions
- Freeze tasks and rubrics; agree access, contamination checks, retest conditions and role disclosure.
Review delivery standards →Three services across the development cycle
Procure each service separately or connect them in stages, with agreed inputs, deliverables and acceptance criteria.
01 / Specialist data
Data matched to your task
Verify sources, strata, counting rules and permissions for imaging, clinical text and multimodal tasks before agreeing a data card and pilot.
Data card · File manifest · Quality and permission notes
Specialist data →02 / Expert production
Turn expertise into training material
Scope annotation, review, preference judgments or evaluation design. Specialist fit, qualifications, effort and review methods are agreed per project.
Task rubric · Review records · Versioned outputs
Expert production →03 / Ongoing evaluation
Understand changes and failure types
Medical Gate uses agreed private tasks and scoring rules. Define retest scope, cadence and independence arrangements in the project agreement.
Scoring rubric · Failure analysis · Version comparison
Ongoing evaluation →Start with a pilot; expand in four steps
01 · Scope
Agree the use case, data conditions, outputs and acceptance method.
02 · Verify and pilot
Check permissions and expert fit; agree a paid pilot and exit criteria.
03 · Produce and accept
Work to frozen specifications, with quality, rework and file verification records.
04 · Retest and iterate
Retest as agreed. Translate failure categories into new task specifications.
What makes a deliverable verifiable
Agree the content, access level and timing of these materials before delivery.
- Task and counting
- Define modality, inclusion rules, deduplication keys and units. Cases, studies, series, slices and annotations are distinct.
- Source and permissions
- Check provenance, lawful processing basis, training use, retention and redistribution. De-identification does not replace authorization.
- Samples and distributions
- Review samples, fields, strata and missingness. Sample approval is not batch acceptance.
- Expertise and quality
- Specify expert fit, review, sample denominators, disagreement resolution, rework and acceptance records.
- Files and versions
- Agree paths, checksums, versions, format checks and image–text pairing. Settle against accepted, deduplicated units.
- Evaluation separation
- Freeze tasks and rubrics; agree access, contamination checks, retest conditions and role disclosure.
How evaluation informs the next production cycle
Use failure categories and new task specifications as feedback. Do not automatically return private holdout questions or answers to training. Where one provider performs production and evaluation, disclose roles and agree personnel, access and test-set separation, including independence limitations. Evaluation supports development decisions; it does not replace clinical validation or regulatory approval.
Bring a task; start with verifiable outputs
Share the objective, modality, data readiness, acceptance needs and timing. Do not submit patient information or raw medical data through public forms.
About LumeSage
LumeSage is the medical and life sciences AI data services brand of Beijing Langhui Technology Co., Ltd. We organize task definition, source and permission verification, expert production, quality review and version evaluation around shared delivery criteria for research, business and procurement teams. Data availability, expert staffing and processing environments are verified and agreed per project.
About LumeSage · Expert production · Specialist data
+86 15010400907 · date@lumesage.com