S. residential solar company, had experienced hyper-growth through the 2010s but struggled to ship product effectively within its R&D organization.
Leadership suspected technical debt was the cause but lacked the data to prove it or act on it with conviction. Across the broader organization, there was a deep disconnect between how leadership believed resources were being spent and how work was actually happening, a gap that blocked effective AI transformation planning entirely.
Parable built a contextual knowledge graph for Sunrun by integrating M365, Salesforce, ERP, Jira, Git, and other systems into a dedicated virtual private cloud, capturing not just outcomes but the flow of work across systems to give leadership a quantitative view of how R&D time was actually allocated.
Through a combination of organizational redesign decisions and AI transformation initiatives informed by Parable's data, Sunrun generated over $80 million in cost savings. This was driven by the platform's ability to quantify inefficiency, specifically, how much of the R&D team's capacity was consumed by technical debt vs. roadmap work, enabling leadership to act with conviction rather than intuition.
Over the period Parable worked with Sunrun, the company's stock price increased 2.5x. Sunrun leadership acknowledged Parable as a foundational component of the operational transformation that contributed to this result, though Parable does not claim sole credit. This reflects broader business performance improvement driven by clearer operational decision-making.
Parable's graph gave Sunrun's leadership a clear, data-backed explanation for why the R&D team wasn't shipping at the expected rate: a disproportionate share of engineering capacity was servicing technical debt. This diagnosis shifted the conversation from conceptual frustration to convicted action, enabling resource reallocation and credible executive-level decision-making.
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