Benjamin Harvey, Ph.D. has experience in data science and artificial intelligence, with a background in academia, government, and the private sector. Because the CEO and Founding father of AI Squared, he oversees a team working on integrating AI and machine learning into web-based applications.
AI Squared goals to support AI adoption by integrating AI-generated insights into mission-critical business applications and every day workflows.
What inspired you to found AI Squared, and what problem in AI adoption were you aiming to resolve?
With my background on the NSA, where I saw firsthand that almost 90% of AI models never made it to production, I founded AI Squared to handle 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 allows businesses to embed AI insights seamlessly into their existing applications without heavy engineering resources. By bridging this gap, we empower organizations to unlock the complete potential of AI, improving decision-making and operational efficiency across industries.
What were the most important challenges in launching AI Squared, and the way has the corporate evolved since 2021?
The largest challenge in launching AI Squared was developing an answer that simplifies AI adoption while maintaining the flexibleness required for enterprise-scale applications. Organizations often struggle with integrating AI into their workflows attributable to technical complexity, resource constraints, and infrastructure limitations. Drawing from my experience leading AI initiatives in government and personal sectors, I ensured that AI Squared evolved to handle 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 approach 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 each the facility 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 companies can profit from the most recent AI advancements with no need deep technical expertise. By leveraging my background in academia and government AI research, we give attention to 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 motion could be taken. This delays decision-making and reduces the general 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 could be time-consuming and expensive. AI Squared eliminates these bottlenecks by providing a no-code/low-code platform that permits enterprises to deploy AI seamlessly into their existing workflows. Our platform enables business users to leverage AI-driven insights with no need to jot down complex code or manage infrastructure. By simplifying deployment and reducing technical barriers, AI Squared accelerates time-to-value, allowing businesses to quickly realize the advantages of AI without unnecessary delays.
Why is no-code/low-code integration essential?
No-code/low-code integration is crucial for AI adoption at scale since 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 permits 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 higher business outcomes without encountering unnecessary technical roadblocks.
How do AI Squared’s Data Apps transform AI deployment?
Data Apps are a key innovation inside AI Squared, offering a light-weight and versatile approach 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 could be easily added to existing workflows. My experience on the NSA reinforced the importance of creating AI insights available and actionable, which is why AI Squared’s Data Apps are designed to offer 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 take care of their accuracy and effectiveness in dynamic environments. AI Squared provides real-time monitoring, feedback loops, and performance tracking to assist businesses fine-tune AI applications over time. Our platform allows organizations to trace 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 proceed to offer high-value insights, stopping 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 since it ensures that AI-generated insights do not stay trapped in data warehouses or dashboards but are actively pushed into operational systems where they’ll 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 instance, AI-driven customer insights could be embedded into CRM systems, providing sales teams with real-time recommendations. By operationalizing AI through reverse ETL, AI Squared ensures that companies can fully capitalize on the worth 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 have to be addressed to take care of trust in AI-driven decisions. AI Squared incorporates advanced bias detection, explainability tools, and governance frameworks to make sure 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 construct trust in AI solutions while mitigating risks related to biased or opaque algorithms.
What’s next for AI Squared?
AI Squared is concentrated on expanding its platform with enhanced automation, deeper monitoring capabilities, and more seamless enterprise integrations. As businesses proceed to embrace AI at scale, we’re committed to creating AI adoption much more frictionless and impactful. Our roadmap includes advancements in AI-driven automation, improved monitoring tools to trace AI performance, and broader integration capabilities to support a various range of business applications. By staying on the forefront of AI innovation, AI Squared will proceed to empower organizations with cutting-edge solutions that drive efficiency, intelligence, and business growth.
