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Description

Evalgent serves as a platform dedicated to the testing and evaluation of AI voice agents. The common reasons for failures in production are not due to inadequate technology but stem from the fact that demonstrations typically utilize pristine audio and compliant users, which is not reflective of actual user interactions. By identifying potential failures before they can impact production, Evalgent reduces the time needed for iterations and accelerates the path to revenue for voice agents. THE PROCESS 1. Define: establish authentic scenarios and criteria for success. 2. Run: execute tests that mimic realistic human behavior. 3. Measure: identify successful elements, failures, and operational boundaries. 4. Act: obtain clear, actionable insights for necessary adjustments or deployments. KEY FEATURES 1. Scenarios: create and define test cases based on agent directives. 2. Caller Profiles: emulate real user behaviors, including variations in accents, speech speed, and interruption styles. 3. Metrics: utilize custom LLM-related and telemetry scoring to evaluate every interaction. 4. Evaluations: conduct structured testing campaigns that yield pass/fail outcomes along with improvement suggestions. 5. Reviews: incorporate human oversight for corrections, complete with a comprehensive audit trail. This multifaceted approach ensures that voice agents are thoroughly vetted and ready for the complexities of real-world interactions.

Description

Timbal serves as a comprehensive AI ecosystem tailored for enterprises, functioning as a production AI platform that empowers teams to create, implement, and manage agents, workflows, user interfaces, and knowledge repositories based on their preferred models. Teams have the flexibility to articulate behaviors through code or utilize Studio, allowing them to operate on any chosen model and provider while delivering solutions across chat, email, voice, and product UI all from a unified runtime. By integrating the entire production stack, Timbal offers a typed Python framework, a visual builder in Studio, a runtime that efficiently manages agents and workflows, as well as governance and evaluation tools for a smooth enterprise deployment, along with seamless connections to existing systems. The agents within Timbal enable autonomous AI capabilities for practical applications, featuring reasoning, tools, and memory, whereas workflows construct reliable AI pipelines that can chain tasks, make logical decisions, retry unsuccessful actions, stream results, and ensure consistent outcomes. Additionally, the interfaces facilitate the deployment of tailored AI experiences across various platforms, from conversational chat to interactive dashboards and voice applications, while the knowledge bases help link and contextualize company information. This holistic approach allows organizations to innovate and adapt to their specific needs while leveraging advanced AI technologies.