Verta launches GenAI Workbench to simplify generative AI app development

Verta, a company that specializes in AI model management and operations, has announced the launch of its GenAI Workbench, a platform that aims to help developers create and refine custom generative AI (GenAI) applications.

GenAI is a branch of AI that uses large language models (LLMs) to generate text, images, audio, or code from natural language prompts.

The GenAI Workbench combines automated machine learning and human feedback to enable rapid experimentation and improvement of LLM solutions. It supports a variety of open-source and proprietary LLMs, such as Llama 2, Mistral, Falcon, GPT, and PaLM, and provides “Starter Kits” with baseline prompts for common use cases. Users can also switch between different LLMs and prompts without affecting their GenAI applications.

The platform also features a GenAI Leaderboard, which ranks LLM and prompt configurations based on quality, cost, and latency, allowing users to choose the best solution for their needs. Additionally, the platform allows non-technical domain experts to influence the results of the GenAI applications during and after development.

Verta’s CEO Manasi Vartak said, “We built the Verta GenAI Workbench to help teams go from GenAI hype to GenAI productivity as quickly as possible.” Verta, which was named in Gartner’s “2022 Cool Vendors in AI Core Technologies” report, aims to revolutionize AI technology by automating the delivery, monitoring, governance, and scaling of AI models.

The Verta GenAI Workbench is available on AWS, Azure, and GCP, as well as on-premise deployments. Users can sign up for free at Verta’s website.

Verta is a Model Management and Operations platform for managing, serving, and governing artificial intelligence and machine learning models.

Verta’s production-ready systems help data science and IT operations teams focus on their strengths and rapidly bring AI/ML advances to market. Based in Menlo Park, Verta is backed by Intel Capital and General Catalyst.

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