Why?
Voiceflow’s collaborative conversational AI platform helps enterprise product teams build and deploy generative AI applications quickly. Now with the power of Anthropic’s Claude model family in Voiceflow, enterprise teams will be able to quickly test, iterate, and launch generative AI applications for use cases such as customer support automation, customer experience copilots, internal task automation, and more.
What this means for Voiceflow customers:
- Full access to the full Claude model family. Claude is a family of state-of-the-art large language models now on canvas. Teams building and deploying agents need the control and flexibility to use the right models for specific tasks and actions. Controlling costs and performance is only possible with powerful model options.
- Joint model and build expertise. We’re combining the knowledge of Anthropic's cutting-edge AI research with Voiceflow's agent builder. This will give teams additional access to models powered by cutting edge AI research and quick access to the latest Claude models for building AI products in Voiceflow.
- Use case-specific guidance. The Claude model family is ideal for high complexity actions and tasks across core business use cases. Our teams will be working closely to create reusable templates, guides and comparisons for customer support, revenue generation, internal automation and other core use cases. This will help teams automate complex interactions and get to an impactful POC that’s ready for production.
“We’re excited to add Anthropic’s models to Voiceflow and work closely with the Anthropic team to help joint customers explore, test, and scale generative AI use cases in the enterprise. Anthropic has become a clear leader in AI with great demand from our customers, especially with the release of their latest 3.5 Sonnet model. We’re excited to work together to help customers unlock the value of AI automation in the enterprise.” - Braden Ream
Anthropic model overview
Here’s an overview of the Claude model family, specifically looking at performance and cost trade-offs.
![](https://cdn.prod.website-files.com/657639ebfb91510f45654149/66956d89bb6a169a01508e44_AD_4nXeTuLKZtfY7phcw-2SfNQsD9Mx2BL6K56dh594YzAY7uNqLp41Gj6KJ2QCdOvdo7DWqDGU8ZpT70TGqQ6ZjS80R-_GNJ69t0xTycp63_MjiDTTe2dHGrgn9ifohxdXdVCoMKEm_LVLtya9SgWP0SjjIHg4.png)
![](https://cdn.prod.website-files.com/657639ebfb91510f45654149/66956d9a3a2d4b8621729206_AD_4nXdTAZiaU1YCrKKQKXNWadzpiAFDu3TGboZ0naEaZWxhesWmVohS4Q67YHxTRcK6S_AE-nsg_qfcECzN01MyOPXwqhvfBiZxgVDBDCJRLNQdoQnxHNNYMGTBFPDeHHGiC3FjWUkfxWhkVb1cEyEGUvgs0_Lw.png)