An AI agent reads a contract, pulls the insurance requirements, checks the payment terms, and decides what happens next. It isn’t guessing. It’s following a prompt, a set of instructions someone wrote telling it what matters.
The trouble starts three months later, when the model updates, or the person who wrote that prompt moves on. Nobody wrote down why it was built that way. Nobody can say for sure if it still gives the same answer today that it gave last quarter. That’s not a small gap. It’s a risk sitting inside every agentic workflow already in production.
What Is Agent Registry
Agent Registry is a solution from Micro Strategies where the prompts driving your AI agents get tested, versioned, and approved before they run in production, and tracked once they do.
Think of it the way you’d think of a model registry or a controlled documents solution. Nothing goes live until it’s been checked. Everything that is live stays connected to its history: who approved it, what document tested it, and what came before.
How It Works
1. Load the prompt. Pull up the version currently running in production, or start from a saved draft.
2. Test it against a real document. Point the prompt at an actual file, see the results, not a guess at what it should return, and run it.
3. Read the real output. See exactly what the prompt pulled, summarized, or flagged, side by side with what you expected.
4. Compare and adjust. Not right yet? Tweak the prompt and run it again until the output holds up.
5. Approve or save as draft. Happy with it? Promote it to production. Still testing? Save it and come back later.
Every step stays linked, the prompt, the test document, and the output, so nobody must reconstruct any of it later.
Everything in One Place
Once a prompt is approved, the full record lives inside M-Files. The prompt itself, the document used to test it, the output it produced, and who approved it all stay connected. If someone asks what ran last quarter, or why an agent made a specific call, the answer is one search away, not a memory someone has to piece back together.
What This Means for Your Team
Your agents keep working the way you expect, even after a model update or a staff change. Compliance and audit questions get a real answer instead of a shrug. And the people building your workflows spend their time improving them, not rebuilding what already worked once.
Frequently Asked Questions
What is agent registry?
Agent registry is a system for testing, versioning, and approving the prompts that drive your AI agents, and for keeping a record of every version once it’s live.
How is this different from a prompt engineering tool?
Prompt engineering is the skill of writing the prompt. Agent registry is where that work gets tested, tracked, and controlled once it’s doing real work in production. The two aren’t competing, the registry gives the prompt engineer a structured place to do the job, not a replacement for the job itself.
Does this work with our existing M-Files setup?
Yes. It’s built directly on M-Files, so the prompt, the test document, and the output are all stored using the same platform you already use for records and content.
What happens if the underlying AI model changes?
You can re-test any approved prompt against the new model before it touches production, using the same document and comparing the output side by side with the old result.
Can more than one person approve a prompt before it goes live?
Yes. Drafts stay open for anyone to test and refine. Only an approved version runs in production, and that approval step is controlled.
Is there a record of every version and who approved it?
Yes. Every draft, every approval, every test document, and every output stays linked together inside M-Files, so the full history is searchable later.
See It in Action
Reach out to Micro Strategies to explore what Agent Registry looks like inside your environment.
Related Topics: Artificial Intelligence | Content Management Optimization | M-Files | Digital Business Process Automation