We take a very hands-on role in solving critical business problems with AI and intuitive UX.


Product Leaders

You will be assigned a Product Leader with relevant industry experience who serves as liaison and partner for the Product Builders and your designated Product Owner.

Product Owners

You designate a Product Owner who is invested in solving a business problem, an expert in the process, and knows all relevant stakeholders. They work hand-in-hand with our Product Leaders.

Product Builders

Our Product Builders build, maintain and support your bespoke AI software. They include data scientists, data engineers, UI/UX designers, front- and back-end engineers, security experts, DevOps and quality assurance testers.

Your AI journey is a distinct process to ensure organizational buy-in, quick deployment, and maximum impact.

Assess the opportunity

Assess the opportunity.

We start by understanding your industry and business goals. With this insight, our Product Leaders work hand-in-hand with your Product Owner to identify the opportunity, prioritize features, estimate returns on investment, and leverage insights from senior leadership.

Identify the relevant data

Identify the relevant data.

The strength of your data will determine the success of your AI product. We begin this step with a Data Maturity Assessment to understand the type, amount, age, and frequency of available data. This process will identify what additional data gathering tools will be required to maximize your product’s impact.

Walk the shop floor

Walk the shop floor.

One of the most critical aspects of the process is understanding the end user and how your product can eliminate existing pain points and barriers. We create detailed stories to fully understand user responsibilities and a vision for how AI enabled digital products will improve their work. Together we then create very detailed, low-fidelity prototypes to ensure a functional and intuitive UI/UX product they are excited to use.

Do the math

Do the math.

We employ professors from top universities and experienced data scientists to create the best algorithms given the data infrastructure available. We are experts both in machine learning (e.g., predictions, recommendations, and explorations) and more foundational techniques such as operations research and optimization.

Build the AI product

Build the AI product.

Our developers build bespoke AI products for you on free and open source libraries which are often years ahead of legacy tools. Since you own the IP, there are no royalty fees. Additionally, you have full control over feature prioritization and are no longer bound by the constraints of off the shelf software. This process is done in sprints to drive speed and push finished products to stakeholders for immediate feedback and continuous improvement.

Drive adoption

Drive adoption.

Our Product Leaders work with your Product Owners to ensure end user adoption. Together we create training materials including written documentation, in app feature walk throughs, video tutorials, and detailed FAQ. When prototype testing and deploying the product to the entire organization, we provide onsite and remote support to fix bugs in hours, and improve the user experience the next day. Once fully deployed we track user adoption metrics and conduct in person interviews to understand pain points and areas of opportunity.

Secure your investment

Secure your investment.

We take documentation and data security extremely seriously and assume threats can come from anywhere at anytime. Well documented software is easier to extend and maintain in the long run. Data security is achieved through a clear cyber security policy, an understanding of threat models, and mechanisms reinforced by high test coverage in a DevOps pipeline. We will design mechanisms where everything is versioned, time stamped, and every merge request is signed off as a team to minimize security risks.

Deploy and maintain

Deploy and maintain.

Your product is complete and has been deployed to your teams and customers. We will continuously monitor and improve the performance of your AI to ensure that your business outcomes are realized over time through data pipeline maintenance, edge case testing, and applying techniques such as active learning.