AI data platform Aware has unveiled Generative AI Summaries that offer secure, reliable, and traceable insights from unstructured digital workplace discussions. Using Aware's specialized platform, businesses can harness the potential of Generative AI to provide practical and precise business insights that streamline the transition from analysis to action.
“Aware's generative AI capabilities are embedded and airtight within our secure AI/ML Platform and allow teams to intentionally leverage generative AI, without fear of hallucinations or their data falling into the wrong hands. Enterprise users can now condense weeks of analysis into actionable insights within minutes to solve use cases ranging from the employee experience and business operations to cybersecurity and GRC,” said Matt Pasternack, Chief Product Officer at Aware.
Handling the main challenges of GenAI adoption
While 67% of IT leaders aim to integrate Generative AI in the next 18 months, the adoption has been slow and inconsistent. The challenges with current Generative AI solutions, especially those based on general-purpose Large Language Models (LLMs), include data security and privacy, accurate business insights, and cost efficiency.
Aware addresses these challenges through its embedded AI/ML Platform, AwareIQ, which provides purpose-built generative AI with real-time, context-rich, event-driven architecture and proprietary foundational machine learning models, enabling efficient and secure AI solutions.
Ensuring data quality and privacy
Aware's platform has the ability to collect and standardize unstructured data from various sources, including collaboration platforms, social media, and open-text survey responses. This data is then organized and managed securely by Aware's Intelligent Data Fabric. It respects privacy controls while segmenting the data, enabling various use cases such as eDiscovery collections and survey analysis.
Furthermore, an additional filtering layer, leveraging Aware's specific machine learning models, enhances the data quality and ensures that only the highest-quality information is presented to users.
Aware's foundational machine learning models are trained specifically on digital workplace conversations rather than generic public datasets. This results in accurate models, smaller in size, and cost-effective. Their embedded AI/ML Platform, designed for conversation data, allows for ongoing model development and refinement, ensuring that the models remain up-to-date and relevant.
Responsible AI
Aware's new generative AI capability is constructed with a strong commitment to responsible AI. Throughout the entire process, from development to deployment, Aware highly emphasizes safeguarding data and ensuring data quality. For this reason, Aware offers access to verbatim data, allowing for easy tracking of summarized information while adhering to the existing data access permissions for individual users.
"Companies are looking at generative AI as a single solution that will help solve all their problems. What’s emerging is that companies are finding that many of these models aren't enterprise-ready, and they don’t have the resources in place to operationalize them. Our unified, scalable platform architecture, compliance with AI standards, and our access to timely, relevant workplace data enables Aware’s generative AI to be ready for deployment, right out the box,” said Jason Morgan, VP of Data Science at Aware.
