Openstream.ai, a leader in Conversational AI, has received a new patent for its Multimodal Collaborative Plan-Based Dialogue System. This innovation enhances its AI platform, Eva (Enterprise Virtual Assistant), by using a unique combination of neuro-symbolic AI to prevent AI hallucinations—errors where AI generates false or misleading information.
Businesses need AI systems that can accurately interact with users and carry out tasks reliably. Eva’s neuro-symbolic AI combines the data-processing power of Neural AI with the logical reasoning of Symbolic AI. This ensures the AI operates based on known facts, providing clear and transparent responses without the risks associated with traditional AI models.
Magnus Revang, Chief Product Officer at Openstream.ai, said, “This advancement allows enterprises to use Multimodal AI agents that learn and improve with every interaction, delivering fast and accurate results augmenting large language models (LLMs).”
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Eva’s approach ensures that AI-driven systems make decisions grounded in real data, making it particularly useful for industries like Healthcare, Finance, Insurance, and Government, where accuracy and compliance are critical.
David Stark, Chief Marketing Officer, added, “With Eva, companies get Multimodal AI agents that can act with empathy based on facts, avoiding the risks and costs tied to less reliable AI models. Eva provides the perfect balance of scalability, quality, and safety.”
AI Agents and autonomous systems built with Eva seamlessly interpret and respond to natural language and multimodal inputs, while recognizing intricate patterns in user behavior. They can reason with abstract concepts and relationships, leveraging knowledge graphs to retain information gathered across complex, multi-turn conversations. These systems engage in empathetic interactions with users and collaborate effectively with other AI agents, ensuring a deeper, more intuitive understanding of the humans they serve.
Eva’s Multimodal AI agents can understand natural language, and facial expressions, recognize patterns in user behavior, and engage in complex conversations. These systems are ideal for enterprises looking to improve the quality of engagement, reduce risks, stay compliant, and maintain transparency.
SOURCE: PRNewswire
