MLflow
Identity Audit
DirJournal Editorial Verdict
MLflow is listed on DirJournal under Machine Learning in San Francisco, California, United States.
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Editorial Verification
Full Audit Transparency Report
200 OK StatusVerified
Primary website is live, secure (HTTPS), and free of malware.
Domain AgeVerified
Real-world domain age (≥1 yr, verified via the Wayback Machine) OR pre-migration legacy ID OR ≥2 years of platform tenure. Survival across multiple search-engine update cycles is itself a trust signal.
Schema ValidationVerified
Valid Organization / ProfessionalService JSON-LD emitted on every page load — checked at render time.
Citation ClarityPending Manual Review
Verified outbound links to at least two authoritative sources (social profiles, sameAs URLs).
Operational HistoryVerified
Minimum 12-month active history in the claimed industry — derived from the business's founding year, Wayback-verified domain age, or listing tenure (any one signal passes).
Entity RegistrationPending Manual Review
Cross-referenced with official state or country business registries.
Physical FootprintData Incomplete
Verified non-virtual presence via Google Maps or official lease documentation.
Complete in DashboardActive LeadershipData Incomplete
Confirmation of key team members and executive roles.
Complete in DashboardNAP ConsistencyData Incomplete
Verified match of Name, Address, and Phone data across platforms.
Complete in DashboardProfessional LicensingPending Manual Review
Verification of required industry-specific certifications or licenses.
Sentiment AuditPending Manual Review
Manual review of third-party reputation signals (BBB, Trustpilot, etc.).
Editorial DiscretionPending Manual Review
Final human review to ensure the business provides genuine value.
This entity has not yet undergone the 12-Point Manual Editorial Audit. The 5 Verified points above are objective system checks this listing already passes; the remaining 7 are manual editorial reviews that still need a human auditor's sign-off.
About
MLflow
MLflow is an open-source platform created by Databricks for managing the complete machine learning lifecycle including experiment tracking, model registry, and deployment across any ML library.
DirJournal's Perspective
Editorial analysis
MLflow powers over 100,000 ML practitioners globally by standardizing experiment tracking across fragmented toolchains. Its model registry directly addresses the critical gap between prototype success and production deployment that derails most ML teams.
Reviewed by DirJournal Editorial Board
Frequently Asked
About MLflow
What does MLflow do?
MLflow is an open-source platform created by Databricks for managing the complete machine learning lifecycle including experiment tracking, model registry, and deployment across any ML library.
Where is MLflow based?
MLflow is based in San Francisco, California, United States.
When was MLflow founded?
MLflow was founded in 2018 and has been operating for 8 years.
Technical Grounding
JSON-LDSoftwareApplication
- Location
- San Francisco, California, United States
- Founded
- 2018
- Team Size
- 1-10 employees
Digital Footprint · Technical Entity Graph
- Website
- Schema TypeSoftwareApplication
- JSON-LDActive
- NAP Vault IDNot assigned
- Social ProfilesNone linked
- Platform TenureNew listing
View Technical Schema▸
- @type
- SoftwareApplication
- areaServed
- Worldwide
- openingHours
- Open 24/7
Knows About
ML Lifecycle ManagementExperiment TrackingModel RegistryML DeploymentOpen Source MLOps
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