kama.ai announces Release 3 of its graph-based Responsible AI platform powered by human experience and human values.
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kama.ai’s Designed Experiential Intelligence platform, kama DEI Release 3 includes new advanced intelligence capabilities with human-like reasoning, chain of thought, and automated two-way user conversations detecting and validating contextual situations users may be facing. Release 3 continues to deliver these Advanced Virtual Assistant features with its zero-code, graph-based state machine, that is informed by enterprise teams in natural language making it an accessible and inclusive technology that accurately reflects the voice of enterprise or communities using the system.
Release 3 also includes the advancement of kama DEI’s “Draft Assist” Retrieval Augmented Generation (RAG) with introduction of Enterprise RAG where users can generate draft answers to frequently asked questions based on their own private documents in Microsoft SharePoint or other enterprise document repositories. After generation, human verification and fact-checking, the information is approved for insertion into the kama DEI knowledge graph for safe, accurate, and actionable information delivery to enterprise stakeholders through omni-channel conversational interfaces.
Founder and CEO, Brian Ritchie said, “As an Indigenous company, we continue to focus on building accessible, transparent and understandable machine intelligence that can be programmed and operated by non-technical knowledge holders and business teams. Release 3 delivers a level of Experiential Intelligence that we have been envisioning since we began our journey. Our advanced inference, incorporates two-way human value guided conversation, and prioritized issue validation and handling, representing the most natural and intuitive reasoning available in the industry based on our market intelligence.”
Regarding the new Enterprise Draft Assist function, kama.ai’s Head of AI Development, Dr. Jacky Wang, said “We were driven by our customers to provide a flexible way to manage the enterprise documents that feed into the Retrieval Augmented Generation process. Customer ‘Collections’ can include a combination of specific sites, folders, or documents from which they can generate responses. We also ensure that each customer’s information is kept private from other customer data to deliver our Responsible AI approach for the enterprise market. In the end, it is humans that give credibility and truth to the final information and make available to end-users through our transparent natural language knowledge graph solution.”
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Inspired in part by the Canadian government’s Code of Conduct for the Responsible Development of AI, kama.ai has outlined the requirements necessary to achieve an ethical, responsible, and sustainable conversational AI platform in is white paper called The Quest for Responsible AI that can be accessed on the company’s website at kama.ai.
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