(NASDAQ: KLTR) has announced the general availability of Dynamic UI, a new capability for its Conversational Agents platform that combines AI avatars, enterprise video, multimedia content, and dynamically generated interactive interfaces. The technology allows organizations to create personalized digital experiences that adapt in real time to users’ questions, interests, and objectives. Instead of relying on predefined websites, applications, or content journeys, Kaltura’s approach enables AI agents to assemble videos, presentations, animations, interactive galleries, and quizzes within conversations, targeting enterprise learning, customer engagement, digital commerce, and entertainment applications.
Kaltura Brings Dynamic Interfaces to AI Conversational Agents
The next phase of enterprise AI interfaces may involve more than conversational responses. As businesses experiment with AI agents, a growing challenge is translating an agent’s ability to understand questions into experiences that help users complete tasks, explore information, and make decisions.
Kaltura is addressing this opportunity with Dynamic UI, now generally available as part of its Conversational Agents offering. The technology combines AI-powered avatars, enterprise video, multimedia assets, and dynamically generated visual interfaces, allowing digital experiences to change according to the context of a conversation.
The announcement moves Kaltura beyond conventional chatbot interactions toward multimodal AI experiences in which dialogue, visual content, and interactive components operate together.
From Static Interfaces to Dynamically Generated Experiences
Traditional digital experiences typically require organizations to design websites, application screens, menus, and navigation paths in advance. Users must then locate relevant information by moving through those predefined structures.
Kaltura’s Dynamic UI introduces a different interaction model. Rather than directing users through fixed content journeys, its Conversational Agents can select, generate, and assemble visual elements during an ongoing conversation.
These elements include video demonstrations, presentations, animations, interactive galleries, and quizzes. The interface can evolve as users ask questions, express interests, or make progress toward specific objectives.
For example, an employee completing corporate training could interact with an AI avatar that explains a subject, presents a relevant video demonstration, and generates a quiz based on the learner’s understanding.
A prospective customer exploring an enterprise product could receive a tailored presentation with video demonstrations and product comparisons. Similarly, entertainment platforms could use conversational agents to deliver personalized recommendations and content previews.
The distinction is that the agent is not limited to retrieving an answer or recommending an existing asset. It can orchestrate how information is presented through a combination of conversational and visual interactions.
Multimodal AI Connects Conversation With Enterprise Content
Dynamic UI builds on three capabilities within Kaltura’s Agentic Digital Experience Platform.
The first is multimedia integration. Kaltura draws on its experience in enterprise video and media technology to combine video, audio, visual assets, and interactive components with AI avatar interactions. This creates an alternative to text-heavy conversational interfaces.
The second is enterprise-grounded intelligence. The company’s Conversational Agents use organizational content libraries, metadata, and enterprise knowledge to select and assemble relevant experiences. This approach is intended to keep AI interactions connected to trusted business information rather than relying exclusively on general-purpose model knowledge.
The third is goal-oriented personalization. Instead of treating every question as an isolated request, agents can adapt their responses to an individual’s context, interests, progress, and objectives.
Together, these capabilities point toward a more sophisticated application of multimodal generative AI. The system determines not only what information to provide but also how that information should be delivered.
Enterprise Applications Extend Beyond Customer Support
The technology has potential applications across several business functions.
In corporate learning and development, AI agents could combine instructional videos, explanations, and adaptive assessments to support personalized training. This could help organizations create learning experiences that respond to individual progress rather than relying exclusively on standardized course structures.
In sales and customer engagement, conversational interfaces could assemble product demonstrations, presentations, and comparisons based on a prospect’s specific requirements. This could make complex product discovery more interactive.
Media and entertainment represent another potential application. AI-powered entertainment guides could combine conversational recommendations with video previews and personalized content discovery.
Interactive kiosks and digital signage could also use conversational agents to provide context-aware visual guidance in physical environments.
These examples illustrate the potential scope of the technology, although actual deployment outcomes will depend on integration, content quality, personalization controls, and the reliability of generated interfaces.
Agentic AI Moves Toward Experience Orchestration
Kaltura’s announcement reflects a broader transition in enterprise AI from conversational assistance toward agentic applications capable of coordinating multiple actions and information sources.
The distinction between a conventional chatbot and an agentic experience is becoming increasingly important. A chatbot primarily responds to prompts, while a more advanced agent can interpret objectives, retrieve relevant information, coordinate tools, and adapt its approach as an interaction progresses.
Dynamic UI adds another layer by making the presentation itself adaptive. This connects conversational AI with generative user interfaces, multimodal models, enterprise search, and personalized digital experience platforms.
The direction also creates competition with established enterprise technology providers. Microsoft, Google, Adobe, and Salesforce are investing in AI capabilities that connect enterprise information with customer and employee workflows. Kaltura’s positioning is more specialized, emphasizing video-native experiences, multimedia intelligence, and conversational avatars.
The commercial opportunity is particularly relevant as organizations look for ways to move AI beyond experimentation into customer-facing and employee-facing applications.
However, dynamic interface generation introduces practical considerations. Enterprises will need to evaluate the accuracy of generated content, consistency of branding, accessibility, data permissions, and safeguards against presenting misleading information. Organizations operating in regulated industries will also need appropriate controls over the information agents can retrieve and display.
General Availability Opens the Door to Enterprise Deployment
Kaltura says Dynamic UI is now generally available through its Conversational Agents offering. The company has not disclosed specific pricing, deployment metrics, or independently measured productivity improvements in the announcement.
The launch positions Kaltura within an emerging market for multimodal and agentic digital experiences, where the competitive advantage may increasingly come from combining enterprise knowledge with adaptive interfaces.
The longer-term test will be whether dynamically assembled experiences deliver measurable improvements in learning outcomes, customer engagement, and task completion compared with conventional chatbots and static digital interfaces.
For enterprise technology buyers, the announcement highlights an important development: AI interfaces are beginning to evolve from systems that simply answer questions into experiences designed to help people accomplish specific goals.
The market opportunity is reinforced by enterprise adoption forecasts. Gartner predicts that 40% of enterprise applications will feature task-specific AI agents by the end of 2026, compared with less than 5% in 2025. Gartner McKinsey’s 2025 research also found that 62% of respondents said their organizations were at least experimenting with AI agents.
These figures suggest that the market is moving toward agent-based interfaces, although adoption and successful enterprise-scale deployment remain separate challenges.
Market Landscape
The market for agentic digital experiences is evolving across three connected areas:
- Generative UI: AI systems dynamically create interface components instead of relying exclusively on predefined application screens.
- Multimodal AI: Conversational agents combine text, voice, video, images, and interactive elements to deliver richer user experiences.
- Enterprise-grounded AI: Organizations connect agents to internal content repositories and knowledge systems to deliver contextually relevant responses.
Kaltura is competing in an emerging segment that overlaps with enterprise AI platforms, digital experience management, conversational AI, and video technology.
Its differentiation lies in combining multimedia infrastructure with enterprise content intelligence and dynamically generated interfaces. However, the market will also reward platforms that demonstrate reliable personalization, low latency, strong integrations, accessibility, and governance.
Top Insights
- Kaltura Dynamic UI brings generative user interfaces to conversational agents, combining AI avatars, multimedia, and interactive components within real-time conversations.
- The platform can dynamically assemble videos, presentations, animations, galleries, and quizzes based on individual questions and objectives.
- Enterprise-grounded intelligence connects conversational experiences with organizational content libraries, metadata, and existing knowledge resources.
- Corporate learning, product discovery, entertainment recommendations, and interactive kiosks represent potential applications for dynamically generated AI experiences.
- Gartner forecasts that 40% of enterprise applications will feature task-specific AI agents by the end of 2026.
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