Booz Allen Hamilton is primarily known for its expertise in consulting, analysis, and engineering services, particularly in the fields of government contracting, intelligence, AI, and digital transformation. I was fortunate enough to have an engagement at BAH and left with 2 major successes including creating and executing go-to-market strategies for AI/ML integrations on AWS GovCloud Marketplace.

Booz Allen Hamilton (BAH) had developed numerous AI/ML solutions for government clients, but these solutions remained siloed within individual projects. BAH lacked a process to monetize this intellectual property beyond their original use cases. Valuable technology sat unused while they continued creating similar solutions from scratch for new clients.

As Technical Product Manager, I led the initiative to identify marketable AI/ML solutions and develop a business model for selling them through the AWS GovCloud Marketplace and the GCP Marketplace. This required establishing new internal processes for revenue collection and support, evaluating existing intellectual property (IP) for commercial viability, and developing go-to-market strategies.

I started by conducting an internal audit of AI/ML solutions across BAH’s government projects. Working with project leads and technical teams, I identified over 20 potential candidates for commercialization. The audit identified several solutions that addressed common problems across various agencies and industries. Market research was conducted to evaluate commercial demand, and I interviewed the project owners to gather more details on the core AI/ML engines and determine if they could be repurposed for general use or were purpose-built for military applications.

The business model development proved challenging as BAH had no existing framework for marketplace sales. I worked with finance, legal, and operations teams to create new processes for revenue collection and distribution. This included establishing funding models for the support team, defining service level agreements, and creating pricing structures that worked for both government and commercial clients.

The support structure presented unique challenges. I developed a tiered support model that balanced customer needs with our resource constraints. This included creating documentation, training materials, and support escalation paths. We established a dedicated support team, funded by marketplace revenue — a new concept for BAH.

Pricing strategy required careful consideration. I analyzed competitor pricing, conducted interviews with the business team to gauge budget expectations, and collaborated with finance to determine profit margins. We created flexible pricing tiers that accommodated both small agencies and large enterprise customers that would include support fees from BAH.

Within eight months, we successfully launched four AI/ML solutions on AWS GovCloud Marketplace. The first win came from a Toyota deal which proved our commercial viability, generating NDA-$$ in first-year revenue from a solution that had previously been used for just one government project.

The new business model transformed how BAH approached intellectual property (IP) development. Project teams now design solutions with future commercialization in mind. The support team structure we created became the template for all future marketplace offerings. The project created a new revenue stream for BAH and changed the company’s approach to IP development. We have established processes that continue to identify and commercialize valuable solutions that would have previously remained project-specific.

This experience demonstrated how traditional government contractors can adapt to modern software business models. The success came from carefully balancing technical requirements, business processes, and customer needs while maintaining the high standards required for both government and commercial markets.