Trainieren und implementieren Sie jedes Modell mit einer vollständig verwalteten MLOps-Lösung
Beschleunigen Sie KI-Pipelines und kommen Sie schnell in die Produktion. Mit JFrog ML können Sie problemlos beliebige KI- oder ML-Modelle erstellen, bereitstellen, verwalten und überwachen.
JFrog ML rationalisiert die KI-Entwicklung vom Prototyp bis zur Produktion und befreit Sie von Infrastrukturproblemen, damit Sie sich auf das Wesentliche konzentrieren können.
Modell-Registry
Bringen Sie Ihre Modelle von der Forschung in die Produktion mit einer fortschrittlichen, zentralisierten und produktionsbereiten Modellregistrierung. JFrog ML bringt alle Vorteile von JFrog Artifactory in den MLOps-Lebenszyklus.
Manage the entire model lifecycle with a single centralized registry- Gain visibility into training parameters, hyper parameter tuning and model metadata
- Manage model and traditional software artifacts in one system
- Bring DevOps and MLOps together one one source of truth
Modell-Training
Einfaches Trainieren und Feinabstimmen von KI/ML-Modellen, von linearer Regression bis hin zu erweitertem Deep Learning und LLMs, mit einem einzigen Klick.
- Trained models are saved in the model registry for a smooth transition from training to production
- Train models on GPU or CPU machines to handle any workload
- Retrain models periodically with easy-to-set-up automations
Modell-Serving
Stellen Sie KI/ML-Modelle im Produktivsystem in beliebiger Größenordnung mit einem Klick bereit.
- Serve models as API endpoints for any realtime machine learning use cases
- Execute batch inference on any dataset from various data sources
- A/B test models to compare real-world performance
Modell-Überwachung
Überwachen Sie die Modellleistung und erkennen Sie Datenanomalien in Echtzeit.
- Überwachen Sie die Modellgenauigkeit im Laufe der Zeit und passen Sie die Parameter bei Bedarf an
- Vorhersagequalität kontinuierlich verbessern und Systemzuverlässigkeit aufrechterhalten
- Überwachungs- und Warnsysteme wie PagerDuty und Slack integrieren, um den Zustand und die Performance von Modellen in Echtzeit zu verfolgen
Über 7.500 DevOps-Teams vertrauen JFrog
Bei über 80 % der Fortune 100 im Einsatz
Cars.com
FFF Enterprises
Workiva
Deloitte
Spot
Mercedes
Monster
Redbox
Yunex Traffic
"We wanted to figure out what can we really use instead of having five, or six different applications. Is there anything we can use as a single solution? And Artifactory came to the rescue. It turned out to be a one-stop shop for us. It provided everything that we need."
"By deploying JFrog, we’ve seen less vulnerabilities, which has given our developers more time to focus on developing new applications. And with the different development teams all being on the same platform, it has centralized and streamlined the process."
"Since moving to Artifactory, our team has been able to cut down our maintenance burden significantly…we’re able to move on and be a more in depth DevOps organization."
"Since moving to Artifactory, our team has been able to cut down our maintenance burden significantly…we’re able to move on and be a more in depth DevOps organization."
"Before… delivering a new AI model took weeks... Now the research team can work independently and deliver while keeping the engineering and product teams happy. We had 5 new models running in production within 4 weeks."
“Most large companies have multiple sites and it is critical for those companies to manage authentication and permission efficiently across locations. JFrog Enterprise+ will provide us with an ideal setup that will allow us to meet our rigorous requirements from the get go. It's advanced capabilities, like Access Federation, will reduce our overhead by keeping the users, permissions, and and groups in-sync between sites.”
"Instead of a 15-month cycle, today we can release virtually on request.”
“As a long-time DevOps engineer, I know how difficult it can be to keep track of the myriad of package types – legacy and new – that corporations have in their inventory. JFrog has always done a phenomenal job at keeping our team supported, efficient and operational – because if JFrog goes out, we might as well go home. Thankfully, with AWS infrastructure at our backs as well, we know we can develop and deliver with confidence anywhere our business demands today, and in the future.”
“When we had that issue with log4j, it was announced on Friday afternoon and [using JFrog] by Monday at noon we had all cities rolled out with the patch.”
Multi-Cloud: Unsere Cloud oder Ihre eigene
JFrog ML bietet native Unterstützung für AWS und GCP. Somit können Sie entweder auf unserer Plattform oder Ihrer eigenen Infrastruktur Ihren Deployment-Prozess optimieren.
Jetzt mit Termin mit einem Experten vereinbaren
