Verta Gains Significant Momentum with the Addition of New Enterprise-Focused Capabilities to its MLOps Platform

New capabilities to Verta's MLOps platform address ML engineering and deployment challenges, improving ML model production by 30x

PALO ALTO, Calif., Aug. 9, 2022 /PRNewswire/ -- Verta, a leading provider of Artificial Intelligence (AI) model management and operations solutions, today announced continued momentum with enhanced enterprise-focused capabilities added to its MLOps platform. The new updates include additions to Verta's native integration ecosystem and subsequent capabilities around enterprise security, privacy and access controls, model risk management, and the pursuit of responsible AI. These updates can improve ML model production time by 30x, a feat that furthers Verta's commitment to solving challenges organizations face with running intelligent products in production in efficient and safer ways at scale.

"The focus of ModelOps is steadily evolving from model experimentation to operational AI where business value is ultimately realized," said Manasi Vartak, CEO and Founder of Verta. "The consequences and technology ecosystem of AI operating in a production setting are far different from when and where the models are built.   We continue to innovate and deliver on our roadmap to provide organizations with a platform to maintain operational excellence and perform to their service-level agreements (SLA), system reliability and high availability requirements, model performance expectations, and governance policies and procedures."

Automating the delivery, monitoring, governance and scalability of AI has become increasingly important to business success. Verta's model monitoring capabilities help data science teams ensure their models remain accurate and that their intelligent products keep providing value to customers. By monitoring model performance, data drift and service levels across deployment environments, Verta ensures model-based applications continue to perform at their best.

"With Verta, we were able to quickly deploy a model registry that seamlessly integrated with our identity systems and access control requirements, providing the trusted model supply chain Scribd needs to succeed," said R. Tyler Croy, Director of Platform Engineering at Scribd. "Not only does this positively impact the customer experience by improving the time needed to get models into production, but it also helps attract and retain top talent by removing obstacles between them and their projects shipping to users."

Verta was recently recognized as a Cool Vendor in the 2022 Gartner® Cool Vendors™ in AI Core Technologies— Scaling AI in the Enterprise report.¹  The report states, "Automating delivery, monitoring, governance and scaling up of AI models is becoming a priority for end-user clients."

The Gartner report also provides recommendations for data and analytics leaders tasked with AI implementation, including that they should:

• Accelerate the time to value from AI initiatives by exploring and leveraging new solutions offered by startup vendors based on your use cases and industry needs.
• Explore the breadth of solutions that address your priorities such as faster model development, ModelOps, data quality, AI explainability and security.
• Compose AI projects by choosing solutions that allow you to measure ROI, be agile, reduce risk and ensure higher model performance.

Verta strives to seamlessly integrate with the tools and products enterprises already use in their IT infrastructure and ML workflows. Along with an extensible platform and open APIs, Verta has built several native integrations for secure and faster onboarding and roll-out in enterprises. New additions to the Verta native integration ecosystem include:

• Active Directory & OAuth2 support: Verta now supports seamless integration with LDAP-based systems like Active Directory. Additionally, for 3rd party Identity Providers like Okta used at enterprises, Verta supports OAuth2-based workflows with OpenID and SAML. This enables Single Sign On (SSO) and automates user management and provisioning with the enterprise identity provider of choice. Verta's authentication integration eliminates the need for a shadow IT infrastructure and reduces the burden on IT when provisioning and deprovisioning users, as everything can happen from a centralized system. In addition to being critical for security and compliance reasons, SSO makes it easier for users to access Verta applications and avoid managing multiple passwords.
• Python Package Index (PyPI) Integration: The PyPI Index is the most commonly used central repository for Python packages and dependencies. As an enterprise-grade model management and deployment platform, Verta provides seamless support for both public and private PyPI repositories for models packaged and served in Verta.  This enables teams to securely share python packages and dependencies within the organization with fine-grained access control and guarantee uptime and availability.
• Datadog Integration: ML models are typically embedded in products and business applications and tightly integrated with other production APIs and services. Verta is bridging this gap with a new integration with Datadog — enabling users to get deep visibility into the operational health of their ML models with just a few simple steps. The integration allows you to send operational and endpoint metrics from Verta to Datadog, enabling SREs and IT teams to get a unified view of operational health and achieve faster troubleshooting.
• Apache Kafka Integration: Verta provides simplified and scalable model deployment and inference serving for batch, real-time and streaming ML applications. With the latest Apache Kafka integration, users can take any model and deploy it in a scalable infrastructure. With Verta as the serving platform, the models can autonomously use their inputs to push predictions into Kafka streaming cluster –– one of the most popular data stream systems used in ML.
• Vulnerability Scanning: Verta is invested to improve the security of AI models with vulnerability detection. It has standardized vulnerability scanning at multiple points of the ML lifecycle to help models get to production faster and stay secure when they're deployed. As part of Verta's implementation process, customer admins can configure the image scanning software their company prefers and Verta runs vulnerability scans automatically to surface issues.

Building and managing AI is a collaborative process involving stakeholders across multiple teams and functions. As the number of people increases, management of security, compliance and collaboration not only becomes essential but also becomes more complex. Verta provides a comprehensive set of roles and permissions to meet the needs of complex security policies while simultaneously enhancing collaboration and productivity for teams and individuals. The platform's user management interface provides administrators with detailed platform audit logs, allowing them to easily establish integrations and apply IT policies and controls in a completely self-served manner.

^[1] Gartner, "Cool Vendors in AI Core Technologies — Scaling AI in the Enterprise," Farhan Choudhary, Alexander Linden, Chirag Dekate, Soyeb Barot, Sumit Agarwal, Afraz Jaffri], 27 May 2022

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About Verta
Verta provides AI/ML model management and operations software that helps enterprise data science teams to manage inherently complex model-based products. Verta's production-ready systems help data science and IT operations teams to focus on their strengths and rapidly bring AI/ML advances to market. Based in Palo Alto, Verta is backed by Intel Capital and General Catalyst. For more information, go to www.verta.ai or follow @VertaAI.

SOURCE Verta Inc.