Proaction turned to Codex to create deeply personalized fleet demonstrations, and the change has reshaped how prospects see product fit and how the company spends engineering time. By feeding Codex with call recordings, email threads and customer spreadsheets, Proaction is able to spin up interactive HTML demos that reflect a prospect’s own vehicles, workflows and organizational layout—what the company says has pushed conversion and accelerated deal progression.
The personalized demos let prospects view their cars, trucks or equipment arranged exactly as they operate in the field. Sales and product teams can modify those demos live in meetings, iterating on layouts and workflows without needing to route requests through engineering. “As a non-technical person, I used to have to loop engineers in if I wanted a demo. Now I do it myself in Codex,” says Colin Knudsen, Proaction’s co-founder and COO.
Proaction reports a material lift in conversion when sales teams present demos populated with a prospect’s data. The company estimates the share of deals moving from initial contact into solution development rose by roughly 50% to 60% when custom demos were used—an outcome that the company frames as both a sales and product win.
A second, immediate benefit has been the reduction in engineering hours required to assemble demo environments. Prior to Codex, an engineering-produced demo took about 10 hours each. Proaction typically generates four to six customized demos each month; by cutting build time to roughly 30–45 minutes apiece, Codex avoids an estimated 40–60 hours of engineering effort every month.
That faster turnaround also improves the handoff from sales to implementation. When a prospect converts, the customized demo becomes a visual reference for engineers, reducing ambiguity and limiting repetitive questions about what to build. This clearer artifact shortens back-and-forth and helps implementation teams move faster with fewer assumptions.
Beyond engineering savings, Codex centralizes routine work for non-engineering staff. Knudsen reports using Codex for sales, support and product-management tasks, estimating a personal time savings of 25–33 hours a month. When combined with the engineering reductions, the company presents the total impact as more than 75 hours saved across roles and functions.
Proaction has integrated Codex with an array of productivity tools to pull context and execute actions without switching applications. Plugins connect Codex to Granola, Gmail, Slack, Linear, GitHub and HubSpot, enabling staff to retrieve call transcripts and email histories, create Linear issues, update HubSpot opportunities and schedule automated reviews from within the same environment. These integrations are an important part of how Codex for demos moves beyond static mockups to become a working source of truth and an operational extension for sales and support teams.
The company also built a customer solution center on Codex where prospects can log in to explore workflows tailored to their business and review sales materials. This self-serve experience extends the demo concept into a persistent environment prospects can revisit and share internally, further reducing friction in the buying process.
Proaction has not limited model usage to demos. The company employs ChatGPT-5.6 Sol for specialized tasks like identifying vehicle damage from photos, and it is developing autonomous agents on GPT-Live-1 within a Managed Execution Layer designed to carry out routine fleet tasks. Those agents can make voice calls, review documents and images, analyze text and respond in chat, and they are intended to be triggered automatically by operational workflows.
One agent already in production, named Marty, coordinates vehicle maintenance: communicating with drivers about issues, calling repair shops, arranging service and managing estimates and payments, with human teams intervening when review or approval is required. Proaction says GPT-6 Astra helped accelerate development of these agent experiences; Danny O’Halloran, Head of Product, notes Astra’s computer-use runs were more succinct than earlier models, allowing the team to execute tasks more compactly and speed iteration.
Across demos, integrations and autonomous agents, Proaction characterizes Codex and newer OpenAI models as time-saving enablers that let the company focus more on sales, customer support and product work while automating routine operational support for fleet managers. Embedding customer data into interactive demos has given prospects a concrete view of product fit and reduced friction in moving from conversation to solution development—illustrating one way generative AI and agentic models can alter go-to-market processes and operational tooling inside SaaS businesses.
Taken together, Proaction’s experience suggests that tailored, data-driven demos and agent-driven automation can change how fleet software is sold and operated: by reducing manual effort, shortening handoffs and letting teams iterate faster around actual customer workflows, the company has found measurable gains in both efficiency and deal momentum.
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