When selling software to businesses with vehicle fleets, nothing beats showing how it works with their actual trucks, cars, or machinery. Proaction, which builds fleet management software, used to rely on engineers to create these custom demos—until they discovered AI tools could handle it instead.
Custom demos in minutes, not engineering days
Proaction’s founders needed personalized demos to show prospects how their platform could fit unique fleet operations. But with limited engineering bandwidth, they often resorted to slides and conversations instead.
Now, using Codex, co-founder Colin Knudsen builds interactive demos himself in 30-45 minutes by feeding the AI:
- Call recordings (via Granola)
- Prospect email threads
- Shared spreadsheets with fleet data
The AI generates an HTML demo environment populated with the prospect’s actual vehicles and workflows. During screen shares, prospects point out adjustments, and Colin modifies the demo live—no engineers required.
Tip
AI-generated demos let non-technical team members prototype solutions during sales calls, reducing back-and-forth later.
Closing more deals with tangible examples
Before AI demos, only about 40% of initial contacts moved into solution development. Now, 60-70% progress—a 50-60% increase. Seeing their own data in action gives prospects confidence to move forward.
Key metrics:
| Metric | Before AI | After AI | Change |
|---|---|---|---|
| Demos built per month | 0-2 | 4-6 | +300% |
| Engineering hours saved | 0 | 40-60 | 100% |
| Deals progressing | ~40% | 60-70% | +50-60% |
From demo to production—faster
When a demo converts to a sale, engineers inherit a working prototype. This cuts clarification time and speeds up development. Proaction also built a customer solution center where prospects:
- Log in to explore workflows
- Review tailored sales materials
- Refine requirements before engineering starts
This reduces misalignment and rework, letting engineers focus on building rather than interpreting needs.
AI as a daily productivity hub
Colin uses Codex plugins to streamline his work across sales, support, and product management:
- Granola: Pulls call transcripts for follow-ups
- Gmail/Slack: Gathers email/chat history
- Linear/GitHub: Creates and tracks issues
- HubSpot: Updates opportunities automatically
An automation reviews recent calls and prepares sales updates, saving Colin 25-33 hours monthly—time he reinvests in growing the business.
Voice agents for fleet operations
Beyond demos, Proaction integrates OpenAI models into its platform:
- ChatGPT-5.6 Sol: Analyzes vehicle damage photos
- GPT-Live-1: Powers voice agents for toll payments, maintenance coordination
- GPT-6 Astra: Builds agents faster with more concise code
One agent, Marty, handles maintenance workflows end-to-end:
- Talks with drivers about issues
- Calls repair shops
- Arranges service
- Manages approvals/payments
Human staff only step in for complex exceptions.
Why this matters for beginners
- Non-technical prototyping: AI lets you build functional demos without coding
- Faster iteration: Prospects co-create solutions during sales calls
- Engineering leverage: Save dev time for core product work
- Voice interfaces: New models make conversational agents viable
Important
While powerful, these tools still require clear prompts and oversight—especially for voice agents handling real-world tasks.
Proaction’s story shows how AI can transform bottlenecks (like demo creation) into differentiators. For beginners, it underscores that you don’t need deep technical skills to start building—just the right tools and a clear workflow.
Read next
- What Google Cloud API Gateway’s MCP Support Means for Beginners
- What OpenAI Academy Means for Beginners Learning to Build with AI
Want to try all of this hands-on? Start with the free Claude Code from Zero course.
Source
Based on OpenAI’s announcement, “Proaction boosts sales 60% and saves 75+ hours with Codex”. Written for people learning to build with these tools.