Unleashing the Power of AI Process Optimization for Start-Up Success

As their strategic software partner, we guided the Avenew team in devising a phase-one solution approach. We also charted a clear path forward for their infrastructure planning software product. We knew exploring the feasibility of both the market fit and AI-enablement capabilities were the first priorities for building new software that could do what they envisioned.

Using what we learned in product discovery, we built an AI optimizer application. It significantly reduced the time city officials spent on the manual work of generating plans, concurrently maximizing the accuracy and efficiency of road network maintenance using asphalt degradation data.

Leading with Product Strategy

We conducted a five-day Discovery workshop to uncover strategic assumptions, model value creation, define customer needs, generate screen concepts, and explore the potential of AI process optimization. This approach proved invaluable to Avenew. It minimized their risk and investment in a proof-of-concept prototype to take to market.

Our first step in addressing this challenge was determining the feasibility of building software capable of tackling this complex problem. We needed to develop a system to suggest road maintenance plans that optimize a combination of budgets, projected road improvements, and the number of roads touched. We developed and tuned an AI optimizer with automated optimization, data science, and machine learning that evaluates many potential ways to maintain roads.

User-centric and Iterative Design

We conducted extensive user research to validate the market fit, focusing on understanding the needs and expectations of Avenew’s target audience.

Our team met with key stakeholders, including mayors and city engineers from different cities and counties across the state. Our designers created mockups of the desktop app to efficiently gather valuable insights, understand the user experience, and refine the application design.

By better understanding the mental model of the target buyers, our team was able to streamline the user interface and product development plan to accommodate existing workflows more easily, leading to higher adoption rates and an easier learning curve.

Developing a Tech-Enabled Service

Avenew ultimately intends to create a software-as-a-service (SaaS) application. However, our discovery findings steered them first to test market fit with a tech-enabled service: an AI-enabled desktop application. Our work allowed our client to confirm the technology’s viability and test market fit with a smaller initial investment.

The solution uses pruning and heuristic techniques to find optimal answers using compiled road degradation data. The resulting AI-enabled optimizer recommends road maintenance plans. It analyzes these massive amounts of data, evaluates numerous potential maintenance strategies, and then presents them to the user through an intuitive user interface—all within seconds.

The system suggests road maintenance plans based on the data. It provided plans that optimize a combination of budgets, projected road improvements, and the number of roads touched. The tool evaluates many potential ways to maintain roads and a UI that presents those options to the user so they can select a plan within seconds.

Using Prototyping Strategically

Concurrently, we developed a prototype for their other strategic option—a SaaS delivery model for optimized plan generation. The minimalist React single-page application served as a demonstrable Software as a Service (SaaS) model. The prototype showed users could invoke the optimizer and effortlessly download their optimized maintenance plans.