Serve approved prompts inside your framework
For agents built with any of the SDKs above, or plain OpenAI and Anthropic clients
Explore the SDK ↗Product loop: a lead approves the Support Ticket Triage and Reply workflow, a rep runs it from Claude, and reps across ChatGPT, Claude, Gemini and Cursor run the team's approved workflows the same way.
76% of small businesses use AI. Only 14% have built it into how they work.
Your team's best prompts become one approved version that everyone runs, in whichever AI tool they already use.
Every new version is checked against standards like AISPA and your Company Policy, with the exact line that needs a fix.
New versions roll out gradually, and every run reports back how it went, so you know what's working before it goes wider.
AirPrompter turns your team's best work into approved AI workflows that everyone runs from ChatGPT, Claude or Gemini, the same way every time.
Save the prompts and workflows your best people already rely on, from chat threads, docs and SKILL.md files, into one shared library.
Answer a few questions about how the work gets done. AirPrompter proposes the steps, and your team reviews them before anything is saved.
Changes go into review. A reviewer approves them, and only then do they go live. Every version is kept.
Approved workflows go into Playbooks. Turn MCP on and every member can reach them from the AI tools they already use.
Ask for a workflow by name in ChatGPT, Claude, Gemini, Cursor or any other MCP client. Everyone runs the same approved version.
Every run is counted in the Hub. Improve a workflow, send the new version to review, and the whole team runs the better one.
AirPrompter checks each version against standards like AISPA and your own Company Policy, and marks the exact line that needs a fix before it goes live.
Checks mark the lines that break a rule, and the ones that protect your customers.
Edit the flagged lines, run the checks again, and the version moves to review once nothing blocks it.
Company Policy is your team's own rules. Every check asks whether each prompt follows them.
Choose, part by part, whether findings only advise or also stop a release.
Keep the framework you already use. AirPrompter adds a delivery layer between your team's approved prompts and your agents, so every prompt change ships the way code does: signed, ramped and measured, while prompts and answers stay on your systems.
Your framework still builds and runs the agent. AirPrompter sits between it and your team: it serves each prompt slot the version your team approved, ramps changes, and gets back counts (tokens, latency, errors, tool calls, feedback), never text.
For agents built with any of the SDKs above, or plain OpenAI and Anthropic clients
Explore the SDK ↗For prompt changes going to live traffic, one gated step at a time
For production agents that need proof before a change goes wider
Explore run telemetry ↗We're opening AirPrompter to a small group of teams before launch. Early teams get a direct line to the founders, a say in the roadmap, founding-team pricing and hands-on setup.