boost.ai Puts AI Agent Control Back in the Hands of CX Teams

New conversational AI platform release introduces LLM model testing, AI-assisted integration building, and a fully configurable chat panel - all without writing a line of code

boost.ai, the enterprise conversational AI platform for regulated industries, today announced version 14 of its platform, introducing a new set of capabilities that give CX and AI operations teams direct control over how their AI Agents are built, tested, and presented to customers. The update will begin rolling out to customers in the coming weeks.

The release reflects a shift in how enterprises manage conversational AI at scale. As AI Agents take on more complex, transactional work, the teams accountable for their performance increasingly need to move quickly — adjusting models, building integrations, and updating customer-facing experiences on their own timelines. This release is built around that reality.

"The question enterprises are asking is no longer whether conversational AI can handle complex, transactional interactions; it can. The real challenge is whether the teams responsible for those interactions can move at the speed the business needs," said Jerry Haywood, CEO of boost.ai. "At boost.ai, we are giving our customers the tools to make better model decisions, keep AI investment proportionate, and stay in control of how their AI Agents evolve."

Test the model before you trust it

Large Language Model (LLM) testing within the platform's Test Studio now lets teams take any use case or guardrail in their AI Agent, run it against multiple AI models simultaneously, and see exactly how each one performs, comparing quality, response speed, and cost side by side.

While public benchmarks measure how a model performs in general, they do not measure how it handles a specific organisation's use cases, with their specific guardrails in place. This update allows CX teams to identify where simpler, more cost-effective models perform just as well as premium alternatives, and where a more capable model is genuinely needed, before either decision reaches a customer.

The result is a more deliberate approach to model selection: one grounded in evidence rather than assumption, and one that keeps costs proportionate to the demands of each task.

Build integrations without the developer queue

The boost.ai platform also includes a major upgrade to the AI assistant built directly into its API Connector. Teams can now describe the integration they need in plain language - from CRM systems like Salesforce to automation platforms like UiPath - point the companion at the relevant API documentation, and receive working integration code, step by step.

Across the industry, integrations are where transactional AI use cases have historically hit their limits. Checking a balance, processing a change, or retrieving a policy detail all require a connection to a backend system, and building that connection has traditionally required writing code - which has meant waiting on a development cycle. The boost.ai API Connector Companion removes that dependency, and teams can now build and refine integrations themselves, in the time it takes to describe them, with no coding knowledge required.

Configure the customer experience yourself

The update also includes a new version of the boost.ai chat panel, paired with a redesigned configuration interface. The chat panel is now available as a floating widget, a full-page experience, or embedded directly in a page - with all configuration managed through the platform's UI.

Teams can maintain multiple configurations and apply each to specific pages by URL — so one AI agent can behave differently across different parts of the customer journey, with business users controlling those changes directly through the UI. New additions include a landing page view with suggested topics and a fixed area for system messages and disclaimers — joining existing platform features that clearly indicate to end users when a response is AI-generated, in support of EU AI Act transparency requirements.

"With this release, we focused on the places where our customers told us they were losing time. Model selection was guesswork, integrations required code, and interface changes required front-end resources," said Clay Cardozo, VP of Product Development at boost.ai. "All three of those are now something a CX team can do themselves, and are all built on the same principle: the people closest to the customer experience should be able to shape it."

About boost.ai

boost.ai is the trusted leader in AI-powered customer experience solutions for regulated industries. Built for security, speed, and scale, the platform enables fast deployment, high-resolution rates, and full hybrid control through seamless orchestration of traditional NLU and LLMs. With over 650 successful deployments, 600 live AI agents, and more than 150 million automated conversations, boost.ai helps enterprises around the world resolve with confidence, automate at scale, and trust every conversation. Proven performance and enterprise-grade reliability make boost.ai the partner of choice for leading brands across the world, including Nordea, Credit Union of Colorado, Sage, DNB, Trading 212, and more. boost.ai is recognized as a Leader in Gartner's 2025 Magic Quadrant for Conversational AI Platforms. Learn more at boost.ai.

SOURCE boost.ai