AI Squared
Augmenting the Cognitive Process of Decision Making

How can we empower organizations to accelerate the integration of AI/ML models into their employees' workflows and enrich, evaluate, and scale this experience in their existing business-critical applications?

The question remains unanswered, as most AI product owners and organizations spend months optimizing the AI/ ML experience of end-users during experiments or studies and even longer to gather feedback and scale the outcomes to the entire enterprise. Also, existing tools in the last mile of the AI/ML lifecycle are designed to support expert-level developers, not citizen data scientists. Without proper tools, novice developers depend on siloed systems or a separate infrastructure to train, deploy, gather inferences and integrate results. This generates out-of-context insights and elongates development cycles, making them question whether introducing AL/MI models into the end-user’s existing workflow is worth the effort.

Solving this multi-faceted challenge is the AI specialist, AI Squared.

AI Squared empowers dev teams with a powerful AI integration and experience platform capable of integrating any AI/ML model—computer vision or natural language processing— into web-based business applications. Built on proprietary low-code, no-code frameworks, it runs inference, integrates the output, gathers end-user feedback, and contextualizes model results quickly, all within existing business applications, collectively enhancing the decision-making process.

“Our goal is not to make decisions for users but augment the cognitive process of decision-making and help companies lay the groundwork for integrating, evaluating, and scaling innovative AI/ML and analytics technologies that drive business growth,” says Dr. Benjamin Harvey, CEO of AI Squared.

AI Squared’s powerful integration and experience platform streamlines the path to integration and reduces the time to market by tenfold. Unlike the traditional route, where dev teams create separate mechanisms to integrate inference results against the deployed model, it helps users of the platform integrate, evaluate, and scale models in real-time. This enables end-users to have an optimized experience with AI in their existing business-critical applications. Take Vanguard, a financial service provider, for instance. AI Squared brought down their ML model’s last-mile integration time inside Microsoft Dynamics 365 from multiple months to hours while ensuring a custom and optimized user experience.

The platform facilitates an intuitive end-user experience across different user groups for various operations. To further cut down the workload of citizen data scientists, AI Squared offers a low-code Python framework that enables them to tailor the entire integration experience inside the application in less than ten lines of code.This eliminates cross-functional challenges and accelerates last-mile integrations. Clients can then govern how, when, and where those integrations must be within the existing applications. They can test, evaluate, and validate those models and gain insights regarding how they behave within the operational environment inside a pre-existing business application.

“An end-user can use the no-code editor with a drag-and-drop interface in our platform to describe or specify the path of integration, and they can fully source the results of their AI and ML models in currently existing applications,” adds Harvey.

What makes the platform unique is its feedback loop that enables clients to gather data from end-user AI/ML model usage in real-time regarding the performance, impact, and value delivered through the integrations. These accurate and actionable insights are instrumental in identifying whether the ML model development is on the right track. Dev teams and data scientists can then push improvements, updates, or redeploy models better aligned with user expectations directly into the end-user workflows.

Our goal is not to make decisions for users but augment the cognitive process of decision-making and help companies lay the groundwork for integrating, evaluating, and scaling innovative AI/ML and analytics technologies that drive business growth

Since AI Squared caters to clients that often work with third-party and legacy applications where full access to the code base may be unavailable, it conducts a proof process to uncover development, integration, and scaling bottlenecks. Here, team AI Squared takes clients' ML model and runs it in their sandbox environment to devise a solution that mitigates development constrictions and showcases the ease of creating the perfect AI experience. If the end-user application is 3rd party, AI Squared provides a browser extension to quickly communicate with local models in the platform or deployed models across the enterprise and carries out integrations. The results are then directly overlaid with the end-user application, typically in a few hours using the integration platform.

AI Squared’s immense value proposition has been instrumental in scripting numerous client successes across various industry verticals, including defense, health care, life sciences, and financial services. Data scientists, seasoned experts from the intelligence community, and professionals with a deep understanding of human-machine teaming and cognitive neuroscience are the force behind AI Squared's success. The combination of industry expertise, powerful no-code, low-code frameworks, and purpose-built AI integration and experience platform makes AI Squared an ideal partner for organizations looking to streamline their business operations and provide the perfect experience with intelligent applications that propel human-in-the-loop models.