Confidently release agent improvements faster with automated testing

Every new version of an AI agent carries the promise of an improvement. But before releasing an update, you need to feel confident that the promise will actualize into a better customer experience. This requires having strong answers to two questions: Does the improvement cover every intent, every scenario, and every guardrail? And what data do you have available to tell you that the improvement will perform better than what customers are already experiencing?

Configuring agent testing scenarios to answer these questions takes time and can miss scenarios no human thought to include. Most teams only find out if a change helped by testing it on real customers. As the number of agents and use cases grows, the optimizing process can either slow the pace of improvement or risk performance with each new agent release.

Parloa’s Automated Simulations & Evaluations and Automated Agent A/B Testing are designed to strike the balance between optimizing and expanding. Now, you can reduce the manual effort needed to evaluate your agents, ensure full test coverage, and automate the comparison of your current and new agent versions, while speeding up your improvement cycles and ensuring reliability along the way.

Test all of your AI agents in a fraction of the time 

18 months ago, Parloa was first to market with Agent Simulations & Evaluations, letting our customers create thousands of synthetic conversations to battle-test agents before launch. But as the complexity and number of agents continues to grow, we recognize that the time required to build simulations can become a bottleneck.

That’s why we advanced the testing capabilities into Automated Simulations & Evaluations. Now, when an agent is created or changed, Parloa Navigator automatically drafts a tailored set of simulations and evaluations within minutes. The draft covers the agent’s intents, tool calls, handoffs, and conversation paths, and provides evaluations for outcomes, instruction-following, guardrails, and business boundaries.

Anonymized historical transcripts can also be added as examples of how customers speak in live conversations, so the simulations can evaluate the agent’s performance based on real customer interactions.

Draft tests are made available for review and editing before they’re used. Human experts decide whether the scenarios reflect the experience and standards of the business, and if they do, the simulations can be used to evaluate the agent before release.

Building confidence in each new agent version release

A new version can pass its evaluations but still leave an important question unanswered: Did it improve the version you have today?

Automated Agent A/B Testing compares the two versions, old and new, against the same evaluation scenarios and quality metrics. The results appear side by side, making it easier to see where the new version improved, regressed, or stayed the same.

You can review scores by established criterion and trace a result down to the conversation behind it to understand exactly what changed. With this information on hand, you can judge whether the gains are worth any trade-offs before releasing the new version.

Faster improvements, with more reliability

Automated Simulations & Evaluations reduce the manual effort of creating an agent-specific test suite. Automated Agent A/B Testing gives you a consistent way to compare the current version with its proposed improvement. Together, agent improvement cycles become repeatable and faster, so you can always feel confident that you’re delivering the best experience to your customers.

Interested in learning more about Automated Simulations & Evaluations and Automated A/B Testing? Talk to our team.