Enabling Scalable, Distributed Product Development

A growing AI and machine-learning software company restructured its development workflows to support distributed teams, faster delivery, and sustained growth.

Context

The client is a U.S.-based company developing proprietary artificial intelligence and machine learning software across multiple industries. At the time of engagement, the development team was small, with engineers working locally and processes evolving organically as the company grew.

As customer demand increased, the existing development approach began to strain—limiting scalability, visibility, and coordination across teams.

Challenge

The company needed to scale its product development efforts while transitioning from locally managed code to a shared, cloud-based environment. In parallel, it needed to formalize how incoming requests were captured, evaluated, prioritized, and introduced into active development.

The challenge was not simply technical. The organization needed a cohesive operating model that aligned tooling, process, and communication—one that could support a growing, distributed team while maintaining velocity and clarity.

Solution

Unista assessed the company’s end-to-end product development lifecycle, from request intake through delivery and communication of results. While the team was already using GitHub for source control, their workflows did not fully leverage the platform’s capabilities.

We designed and implemented a structured development framework that aligned tooling, process, and team roles. This included creating multiple issue lists and project boards tailored to different audiences, establishing clear linkages between requests and development work, and automating movement and deployment through GitHub Actions.

From a process perspective, we introduced an agile development model with defined sprint cycles, standups, and a standardized Git flow that teams could follow consistently. The result was a unified system that supported distributed development while remaining flexible as the organization continued to evolve.

Impact

The company gained a scalable, cloud-based development environment that enabled distributed teams to collaborate effectively and deliver work more predictably. Request intake, prioritization, and execution became more transparent, while automation reduced manual overhead and deployment friction.

By establishing a durable development operating model, the organization was able to support growth, increase throughput, and empower its product teams with systems designed to scale alongside the business.