2026-09-27 — views
Proaction Uses Codex to Boost Sales 60% and Save Engineering Hours
Read this because This case study demonstrates how AI agents can replace manual demo engineering, directly impacting revenue and operational efficiency for startups.
Proaction leverages OpenAI's Codex to create custom fleet demos, increasing sales conversion by 60% and saving over 75 hours monthly.
Custom Demos Drive Sales Growth
Proaction, a software company serving fleet management businesses, has reported a 60% increase in sales after integrating OpenAI’s Codex into its workflow. The company builds solutions for managing vehicles ranging from cars to construction machinery. Because every fleet operates uniquely, demonstrating how the platform fits specific business needs is critical. Previously, creating personalized demos required significant engineering time that the startup could not spare. Founders relied on conversations and slide decks, which were less effective at closing deals.
Colin Knudsen, co-founder and COO, now uses Codex to build four to six customized, interactive demos each month. He directs the AI to context from Granola recordings, prospect emails, and shared spreadsheets. Codex then generates an HTML demo environment that mirrors the customer’s specific fleet. This allows prospects to see their own vehicles and workflows, enabling them to point out adjustments and help build the solution. Knudsen estimates this process avoids 40 to 60 hours of engineering work monthly. The personalized approach has increased the percentage of deals moving from initial contact to solution development by 50% to 60%.
Streamlining Operations with AI Agents
Beyond sales, Proaction uses Codex to save 25 to 33 hours of founder time per month. Knudsen integrates plugins for tools like Gmail, Slack, Linear, GitHub, and HubSpot. He pulls call transcripts and email history to prepare follow-ups, create issues, and update opportunities. This centralization eliminates the need to jump between tabs and copy information manually.
Proaction also employs OpenAI models across its platform to enhance fleet operations. ChatGPT-5.6 Sol helps identify damage from vehicle issue photos. The company is building a Managed Execution Layer using GPT-Live-1 and GPT-6 Astra to handle day-to-day tasks. For example, an agent named Marty coordinates vehicle maintenance by talking with drivers, calling repair shops, and arranging service. GPT-6 Astra enables faster development of these experiences, with Head of Product Danny O’Halloran noting that its computer-use runs are more succinct than previous models.
Practitioner note
Developers should evaluate how integrating AI agents into sales workflows can reduce dependency on engineering resources for custom demos. Monitoring the efficiency gains from tools like Codex and GPT-6 Astra can reveal significant time savings in both customer-facing and internal operational tasks.