Explainable, Transparent and Reliable Insights
An Insight Engine that fuels your decision intelligence with Composite AI
>An Insight Engine that fuels your decision intelligence with Composite AI
Explainable, Transparent and Reliable Insights
In the enterprise context, where traceability of information and fact-checking are required, the black-box algorithms of traditional AI cannot provide reliable insights.
ChatGPT is the most recent example, showing how generative AI can revolutionize our understanding of AI and its potential overnight. Next to the very impressive capabilities in summarization and question-answering space, it also clearly shows some significant limitations, when applied in specific enterprise domains, where reliability, explainability and security are key and lack of those can cause significant operational and financial risks:
- Lack of traceability of the relevant information: it’s not visible, which information was considered for a specific reply.
- Hallucination: The system might produce answers, which look plausible at first sight, but which are in fact erroneous.
- Shortcomings with regard to compliance with company internal access rights regulations, and security and privacy constraints.
All this clearly indicates the need for assistants, which are based on comprehensible domain models instead of opaque pattern recognition. Such assistants can provide enterprise-wide relevant knowledge for critical processes and decisions in risk management, internal audit and regulatory compliance; support critical R&D processes; dramatically improve efficiency in customer service management or sales management, or bring the cross-functional collaboration, knowledge discovery and knowledge sharing to a completely new level.
Our latest generation of insight engines is able to tap into content where conventional search engines and recommendation systems reach their limits. Squirro’s Composite AI Insight Engine combines the strengths of data-driven AI with symbolic and generative AI to harness your organization’s content for intelligent decision-making.
Explainable, Transparent and Reliable Insights to Augment Your Knowledge Life Cycle
Effective and efficient knowledge acquisition supported by the next generation of semantic enterprise search.
Support content creation with recourse to the company’s own content inventory.
Seamless and personalized human-machine dialogue in employee and customer interactions.
Effective AI tools help in lifting noble knowledge from large blocks of information.
Decisions are based on an accurate and deep understanding of the company’s knowledge base.
In-depth sentiment and context analyses identify risk potentials along the entire value chain.
Composite AI – A Unique Technological Approach
After an initial hype-driven wave of machine learning applications, the second generation of AI has recently shown that techniques from different developments can mesh to the benefit of the user. Building on this, our XAI Insight Engine is based on two proven AI concepts: statistical and symbolic AI.
We combined Squirro’s machine learning, natural language processing and enterprise search with PoolParty’s graph-based metadata and text mining approaches to create the worldwide first Composite AI Insight Engine of its kind. A solution that differs significantly from conventional AI approaches in four ways:
Leverage domain knowledge and human expertise by applying ML models in a particular context. This can be achieved by applying business rules, knowledge graphs and physical models.
By combining the content with the user's intent and context, the composite insight engine delivers more relevant and personalized insights for each user in each functional domain.
Search and recommendation systems that identify multidimensional knowledge objects based on search intent and context.
Composite AI Insight Engine unlocks the full power of AI in the enterprise context, which typically lacks access to large amounts of historical or labeled data but does have extensive human expertise.
Learn More About Explainable Insights
How Squirro and Poolparty Create Semantic Knowledge Objects That Power Your Decision Intelligence
Each piece of content is classified in a first step by Squirro’s ML according to the user’s intended insights and decomposed into corresponding content blocks. PoolParty’s knowledge graph technology contextualizes this content and links it to other meaningful concepts and data. Finally, the system packages the generated semantic knowledge objects for further use in search, recommendation, and dialogue applications.
Gartner: "By 2024, 70% of organizations relying solely on ML for AI initiatives will spend more money per model than those leveraging composite AI techniques."
Innovation Insight for Composite AI, Hamer, Brethenoux, Ramos, 2022
Are you interested in learning how Composite AI can be used within your organization to help improve business intelligence? Schedule a call today!