How Stampli cut launch time by 68% with AI agents

When Stampli needed to launch its Deep Finance product—a system that turns procurement data into executive insights—they faced a tight deadline with stretched resources. Their solution wasn’t hiring more staff or cutting corners, but integrating AI agents into their workflow. The result: compressing what would have been 243 hours of human work into just 77, while maintaining full quality control.

The launch challenge

Stampli’s product connects procurement, accounts payable, and vendor management into one platform. Their Deep Finance launch required seven types of materials to be created simultaneously:

• A seven-part blog series
• Email campaigns
• Webinar decks
• Social media creatives
• Press releases
• Sales enablement documents
• Animated explainer videos

With designers and contractors already committed to other projects, the team turned to OpenAI’s Codex (now part of ChatGPT Work) to handle the bulk of content creation. The AI didn’t replace human judgment—every customer-facing piece still went through full review—but it eliminated the grunt work of drafting and formatting.

How the hours broke down

The team modeled what the launch would have taken without AI assistance versus their actual experience:

Beyond one-off launches

What makes Stampli’s approach notable isn’t just the time saved on a single project, but how they built systems for ongoing use:

1. Product knowledge base: Instead of manually tracking product changes through Jira and meeting notes, they connected Codex to their internal systems. It now auto-updates help docs and training materials.

2. Content scaling: Their small marketing team went from producing “a couple pieces of content weekly” to “hundreds” by using AI for first drafts of social posts, blog ideas, and sales collateral.

3. Meeting prep: Employees use ChatGPT Work to summarize relevant context before meetings, pulling from past notes and CRM data like HubSpot.

The executive advantage

One meeting demonstrated the system’s value starkly. When executives needed metrics analysis mid-discussion, an employee queried the AI instead of waiting days for a finance report:

1. Traditional process: 4 hours to compile data + 4 hours to model + review
2. AI-assisted: 20 seconds to query + instant visualization

What this means for beginners

Stampli’s case shows three patterns you can apply immediately:

1. Augment, don’t replace: They kept humans in the loop for all final decisions, using AI for the “middle miles” of work.

2. Connect your tools: By linking Codex to HubSpot, Jira, and GitHub, they created a system that improves with use.

3. Measure time saved: Tracking hours (like their 243→77 comparison) proves value beyond vague “efficiency” claims.

Building your own system

You don’t need Stampli’s resources to apply these lessons. Start small with:

1. Document templates: Use AI to draft blog posts or emails based on your past examples
2. Meeting digests: Automatically summarize notes and action items
3. Data queries: Connect simple spreadsheets to AI for instant analysis

The key is treating AI as a team member that handles predictable tasks, freeing you for strategic work—exactly as Stampli’s marketing director now spends “more time advising VPs and C-suite leaders” instead of compiling reports.

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Want to try all of this hands-on? Start with the free Claude Code from Zero course.