Proaction⁠(opens in a new window) builds software for businesses that manage fleets of vehicles, from cars and trucks to construction machinery. Because every fleet operates differently, showing prospects how Proaction’s platform fits their business is an essential part of selling it.

But personalized demos required engineering time the team couldn’t spare. The founders had to rely on conversations and slide decks to explain what was possible. Codex flipped the script.

“As a non-technical person, I used to have to loop engineers in if I wanted a demo,” says Colin Knudsen, co-founder and COO of Proaction. “Now I do it myself in Codex.” Colin creates four to six customized, interactive demos a month, with each taking 30 to 45 minutes to build. He estimates that this avoids 40 to 60 hours of engineering work.

After a sales call, Colin directs Codex to the Granola recording, prospect email threads, and any spreadsheets the prospect has shared. Codex uses that context to customize an HTML demo environment that mirrors Proaction’s product and the customer’s own fleet.

When Colin shares his screen, prospects see their own cars, trucks, or equipment, organized around how they work. They can point to what needs adjusting and help build the solution. “You work together to generate the end solution without getting engineering involved at all,” Colin says.

Offering prospects a demo with their own data gives them a concrete reason to move forward. Colin estimates that the percentage of deals moving from initial contact into solution development, rather than nurture, has increased by 50% to 60% with the custom demos.

If Proaction’s engineers produced comparable demos, it would take about 10 hours each, according to Colin. Since Proaction does about four to six demos monthly, that represents 40 to 60 hours of engineering effort spared every month.

The demo also saves time on the back end. When a prospect becomes a customer, Colin gives engineers the customized demo as a visual reference. That reduces questions and back-and-forth about what to build.

Using Codex, Proaction also built a customer solution center where prospects can log in, explore workflows tailored to their business, and review sales materials. This empowers customers to explain what they need and gives non-engineering teammates a way to turn those conversations into clearer requirements. By the time engineers get involved, they have a more concrete picture of what to build.

Colin’s daily work spans sales, customer support, and product management. Through Codex plugins for tools including Granola, Gmail, Slack, Linear, GitHub, and HubSpot, Colin brings together customer context and acts on it within Codex.

He pulls call transcripts and email history to prepare follow-ups, creates Linear issues, and updates HubSpot opportunities. He also set up a scheduled automation that reviews recent calls and prepares sales updates for the team.

Previously, his heavy workload meant jumping between tabs and copying information from one tool to another. Now, Colin can describe what he needs and use Codex to gather the context and execute the next step. “Everything that I do is centered around working in Codex. I don’t leave it much,” says Colin. Estimating he has 15 to 20 distinct tasks a day, Colin believes Codex saves him 25–33 hours a month.

Proaction also uses OpenAI models across its platform. When customers submit photos with vehicle issue reports, ChatGPT‑5.6 Sol helps identify damage. And with GPT‑Live‑1, Proaction is building agents that handle more of the day-to-day work of running a fleet. The company calls this its Managed Execution Layer.

Customers can ask specialized agents to handle things like tolls or service, or set up workflows that put the right agent to work automatically. The agents use OpenAI models, including GPT‑Live‑1 and GPT‑6 Astra, to make voice calls, review documents and images, analyze text, and respond in chat.

One agent, Marty, is designed to coordinate vehicle maintenance. Marty talks with a driver about a problem, calls repair shops, arranges service, and helps get the estimate approved and paid. Proaction’s team steps in when the work needs human review or intervention.

GPT‑6 Astra also enables Proaction to build these experiences for customers faster. Danny O’Halloran, Head of Product, says, “Astra’s computer-use runs are more succinct. With GPT‑5.6 Sol, I had a much longer run to execute the same work.”

Codex and GPT‑6 Astra give Proaction more time to sell, support customers, and move the business forward. And with agents built on GPT‑Live‑1, Proaction gives more time to fleet managers, too.

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