Benjamin Harvey, Ph.D. has experience in data science and artificial intelligence, with a background in academia, government, and the private sector. As the CEO and Founder of AI Squared, he oversees a team working on integrating AI and machine learning into web-based applications.
AI Squared aims to support AI adoption by integrating AI-generated insights into mission-critical business applications and daily workflows.
What inspired you to found AI Squared, and what problem in AI adoption were you aiming to solve?
With my background at the NSA, where I saw firsthand that nearly 90% of AI models never made it to production, I founded AI Squared to address the critical gap between AI development and real-world deployment. Many AI solutions remain siloed in research environments, failing to integrate into operational workflows, which significantly limits their potential impact. AI Squared simplifies this process by providing an intuitive platform that enables businesses to embed AI insights seamlessly into their existing applications without heavy engineering resources. By bridging this gap, we empower organizations to unlock the full potential of AI, improving decision-making and operational efficiency across industries.
What were the biggest challenges in launching AI Squared, and how has the company evolved since 2021?
The biggest challenge in launching AI Squared was developing a solution that simplifies AI adoption while maintaining the flexibility required for enterprise-scale applications. Organizations often struggle with integrating AI into their workflows due to technical complexity, resource constraints, and infrastructure limitations. Drawing from my experience leading AI initiatives in government and private sectors, I ensured that AI Squared evolved to address these challenges by enhancing no-code/low-code solutions, expanding industry reach, and integrating cutting-edge AI research into our platform. Today, AI Squared provides businesses with an accessible and scalable way to deploy AI effectively, transforming how organizations leverage AI for operational success.
How does your background in academia and research shape AI Squared’s mission?
My research at institutions like Johns Hopkins and NSA focused on applying AI to complex problems in cybersecurity, data analytics, and decision intelligence. This experience has given me a deep appreciation for both the power and the challenges of AI implementation. At AI Squared, our mission is to bridge the divide between AI research and real-world application, ensuring that businesses can benefit from the latest AI advancements without needing deep technical expertise. By leveraging my background in academia and government AI research, we focus on making AI more accessible, practical, and responsible, helping organizations harness AI-driven insights to drive meaningful change.
Why is embedding AI insights into business applications critical?
Many AI projects fail because insights remain isolated in dashboards or analytics platforms, requiring manual interpretation before action can be taken. This delays decision-making and reduces the overall impact of AI initiatives. AI Squared embeds AI insights directly into business applications, ensuring that employees can act on real-time insights without leaving their workflow. Whether it’s optimizing customer interactions, improving supply chain operations, or enhancing cybersecurity measures, embedding AI into business applications maximizes efficiency, increases user adoption, and significantly improves return on investment (ROI).
How does AI Squared streamline AI deployment?
Deploying AI models into production environments often requires extensive engineering, integration, and infrastructure development, which can be time-consuming and costly. AI Squared eliminates these bottlenecks by providing a no-code/low-code platform that allows enterprises to deploy AI seamlessly into their existing workflows. Our platform enables business users to leverage AI-driven insights without needing to write complex code or manage infrastructure. By simplifying deployment and reducing technical barriers, AI Squared accelerates time-to-value, allowing businesses to quickly realize the benefits of AI without unnecessary delays.
Why is no-code/low-code integration essential?
No-code/low-code integration is essential for AI adoption at scale because it democratizes access to AI, enabling domain experts and business leaders to operationalize AI without requiring dedicated AI engineers. The shortage of AI specialists often slows down implementation and innovation, creating dependency on technical teams. AI Squared reduces this reliance by offering an intuitive platform that allows non-technical users to integrate and utilize AI models efficiently. This accelerates AI adoption across industries, making AI more accessible and ensuring organizations can leverage AI to drive better business outcomes without encountering unnecessary technical roadblocks.
How do AI Squared’s Data Apps transform AI deployment?
Data Apps are a key innovation within AI Squared, offering a lightweight and flexible way to integrate AI insights directly into business applications. Many organizations struggle with AI deployment because their models require extensive integration with existing software systems. Data Apps eliminate this challenge by embedding AI-driven insights as modular components that can be easily added to existing workflows. My experience at the NSA reinforced the importance of making AI insights readily available and actionable, which is why AI Squared’s Data Apps are designed to provide real-time, in-context intelligence that enhances decision-making across industries without requiring extensive retraining or infrastructure changes.
How does AI Squared ensure AI models remain effective?
AI models require continuous monitoring and optimization to maintain their accuracy and effectiveness in dynamic environments. AI Squared provides real-time monitoring, feedback loops, and performance tracking to help businesses fine-tune AI applications over time. Our platform allows organizations to track model performance, detect drift, and implement automated feedback mechanisms that improve AI accuracy based on real-world data. This ensures that AI models remain reliable and continue to provide high-value insights, preventing degradation and ensuring businesses achieve sustainable AI-driven success.
How does AI Squared’s reverse ETL improve AI-driven decision-making?
Reverse ETL is a game-changer for AI adoption because it ensures that AI-generated insights do not remain trapped in data warehouses or dashboards but are actively pushed into operational systems where they can drive real-time decision-making. AI Squared’s reverse ETL solutions integrate AI insights directly into frontline applications, eliminating data silos and enabling businesses to act on intelligence without switching between tools. For example, AI-driven customer insights can be embedded into CRM systems, providing sales teams with real-time recommendations. By operationalizing AI through reverse ETL, AI Squared ensures that businesses can fully capitalize on the value of AI-driven intelligence.
How does AI Squared ensure responsible AI deployment?
Ensuring ethical and responsible AI deployment is a top priority for AI Squared. As AI becomes more pervasive, concerns around bias, transparency, and explainability must be addressed to maintain trust in AI-driven decisions. AI Squared incorporates advanced bias detection, explainability tools, and governance frameworks to ensure that AI models produce fair and interpretable outcomes. Our platform provides transparency into AI decision-making processes, helping businesses comply with ethical guidelines and regulatory requirements. By prioritizing responsible AI deployment, we help organizations build trust in AI solutions while mitigating risks associated with biased or opaque algorithms.
What’s next for AI Squared?
AI Squared is focused on expanding its platform with enhanced automation, deeper monitoring capabilities, and more seamless enterprise integrations. As businesses continue to embrace AI at scale, we are committed to making AI adoption even more frictionless and impactful. Our roadmap includes advancements in AI-driven automation, improved monitoring tools to track AI performance, and broader integration capabilities to support a diverse range of business applications. By staying at the forefront of AI innovation, AI Squared will continue to empower organizations with cutting-edge solutions that drive efficiency, intelligence, and business growth.
Thank you for the great interview, readers who wish to learn more should visit AI Squared.
