Platform
MCP Server Build
A production MCP server for one of your systems, with up to 8 tools, secure sign-in, action logging and tests in AI…
Platform
AI Prompt Management
Prompts versioned, tested and deployed from one place, outside your codebase, so changes don't need a release.
When prompts live inside application code, every small wording fix needs a developer, a review and a release. AI Prompt Management moves your prompts into a versioned library where they can be tested against real examples and deployed on their own. Old versions are kept for quick rollback. Your team controls what goes live, and the configuration stays in your version control.
- Prompt changes deployed without a code release
- Every change tested against real examples before it goes live
- Full version history with quick rollback
$2,900
20–30 working days
Optional maintenance $249/mo
What it is
AI Prompt Management is a build that moves the prompts your AI systems use out of hardcoded application code and into a versioned library, where changes are tested and deployed without a code release. Every version is kept, so a change that performs worse can be rolled back quickly.
Why businesses buy it
Prompts are the part of an AI system that changes most often, yet they are usually buried in code. Each tweak waits for a release, nobody remembers which version is live, and a bad change is hard to undo. After this build, prompts sit in one versioned library with a testing step, so the people who understand the wording can improve it safely. The Scope Card sets the applications, prompts in scope and controls in writing before you order, so the migration has clear edges.
Problems this solves
Prompts are hardcoded, so every tweak needs a code release
Prompt Management moves prompts out of application code into a versioned library. Changes are tested and deployed without waiting for the next code release, so small fixes go live sooner.
A prompt change makes results worse and nobody can undo it
Every prompt version is kept. If a change performs worse, the earlier version can be rolled back quickly from the library. No developer needs to redeploy the app.
Nobody knows which prompt version is live in which app
The library covers up to three systems or AI applications. The admin console or written report shows the version each one is using, and when it last changed.
A good fit if
Your prompts are currently hardcoded in application code, so any wording change needs a developer and a deploy.
You have more than one AI workflow and want prompt versions tracked, so you can see what changed and roll back if needed.
You want to test a prompt change before it goes live, against real examples, rather than shipping straight to production.
You have a named technical owner who can supply cloud access and review the prompt library before launch.
Not the right fit if
You need the full integration layer for routing requests across providers, not prompt versioning specifically. See AI Gateway.
Your priority is deciding which model handles a request, not managing the prompts sent to it. See AI Model Router.
You need agents to retain memory across sessions, not a prompt library. See AI Agent Memory System.
You need structured retrieval from your own documents, not prompt versioning. See AI Agent Knowledge Layer.
How it works
- We inventory the prompts currently hardcoded across your AI applications, so nothing is missed when they move into the library.
- Each prompt is migrated into a versioned library, with the current production version tagged as the baseline.
- A testing step is configured, so a prompt change can be run against real examples before it's promoted to production.
- Applications are updated to pull prompts from the library at runtime instead of from hardcoded strings in the codebase.
- Version history and rollback are set up, so a prompt change that performs worse can be reverted without a code deploy.
- A control test log documents the migrated prompts and the testing workflow, reviewed with your technical owner before launch.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Written authorization confirming which applications and prompts are in scope for the migration.
- A list of the AI applications and systems whose prompts should move into the managed library.
- Your existing prompts, or access to the code where they currently live, for the migration.
- Cloud or hosting access needed to deploy the prompt library alongside your existing infrastructure.
- A named technical owner who can review the migrated prompts and sign off before launch.
- Admin access and API keys for every connected provider, shared by adding our team as a user or creating a key you control, never by email.
- Your business information (company basics, hours and brand voice), shared during intake, and one decision-maker who can approve the final configuration.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified, applications and prompts in scope confirmed.
Weeks 1–2
Prompts migrated into the versioned library with baselines tagged.
Week 3
Applications connected to the library and the testing workflow configured.
Weeks 3–4
Control test log produced and shared with your technical owner.
Week 4
Your review and two rounds of changes applied to the setup.
Go-live
Live, recorded handoff session, 30 days of support begins.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $2,900 |
| Express | 15–25 working days | $3,400 |
| Rush | 10–20 working days | $3,900 |
What you receive at handover
- AI Prompt Management configured and deployed, with a versioned prompt library for up to three applications
- A test-then-deploy process for prompt changes, with rollback
- Up to five controls configured from your policies, such as who can publish a change
- A test report with a control test log for the agreed scenarios
- An admin guide and a recorded 60-minute handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can let your team improve prompts without waiting on developers.
- Helps you recover quickly when a change goes wrong.
- Gives a clear history of what changed and when.
- Time to ship a prompt change
- Compare request-to-live time for prompt changes before launch and after.
- Rollbacks
- Count rollbacks each month from the library history to see how often changes misfire.
- Prompt changes per month
- Count published versions to see how often teams now improve prompts.
Before you start: List where prompts live in each application today. Time how long the last few prompt changes took to reach production.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running Prompt Management afterward costs roughly $20 to $300 a month in your own accounts, covering hosting, logging and monitoring tools, and it scales with how many prompts and workflows are managed.
AI model usage during the build and testing is billed to your own accounts too, so every provider relationship stays yours, not ours.
Ask about running costsCustom requirements
Need more than three systems in scope, more than five controls configured, or a second admin console? Add a note at checkout and you get a written Change Quote, only starting once you accept it. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionKeep it running
Monthly maintenance covers monitoring, fixes and a monthly allowance of change hours, enough to test and deploy new prompt versions as workflows evolve. It starts once the 30 days of support end and can be cancelled any month.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A prompt management platform charges a monthly fee per seat or per project | A systems integrator quotes per project after a discovery phase | Ours is one fixed price, shown on this page before you buy |
| Scope | A prompt platform is a workspace your engineers configure and adopt themselves | An integrator agrees scope during the project | Ours is written on the Scope Card before purchase |
| Migration | A prompt platform gives you the tool; migrating existing prompts is on you | An integrator build depends on who is staffed on it | Ours migrates your existing hardcoded prompts as part of the build |
| Delivery | A prompt platform is live once your team finishes onboarding it | An integrator usually takes several weeks to staff and start | Ours has a fixed delivery time shown before you buy, with faster options |
Questions about this product
How much does AI Prompt Management cost?
The fixed price for each delivery speed is shown in the price and delivery panel on this page before you order. It covers everything on the Scope Card: migrating the existing prompts from up to three applications, configuring the testing workflow and version history, and the control test log you review before the library goes live.
Does AI Prompt Management migrate our existing hardcoded prompts?
Yes. We inventory the prompts currently hardcoded in your AI applications and migrate them into the versioned library, tagging the current production version as the baseline. Applications are then updated to pull prompts from the library at runtime, so a wording change no longer needs a developer and a code deploy.
What does AI Prompt Management cost to run each month?
Roughly $20 to $300 a month in your own accounts, covering hosting, logging and monitoring tools such as Langfuse or Grafana. You pay providers directly, so there's no markup from us. A small number of managed prompts sits toward the bottom of that range, a large library toward the top.
How is AI Prompt Management different from AI Model Router?
AI Prompt Management versions and deploys the prompts your systems send to a model. AI Model Router decides which model receives a given request, by cost, capability and latency. The two solve different problems and can run together: managed prompts sent through routed requests, each configured independently and changed without touching the other.
Can we test a prompt change before it goes live?
Yes. The testing workflow configured during the build lets you run a prompt change against real examples before it's promoted to production, and version history means a change that performs worse can be rolled back without a code deploy. This is the core reason prompts move out of hardcoded application code.
Can we add more applications to AI Prompt Management later?
Yes. The standard build covers up to three systems or AI applications, and adding a fourth or beyond is quoted as a Change Quote once you are ready to expand. We suggest migrating the prompts you change most often first, confirming the testing workflow fits how you work, then bringing in further applications.
What do we need to provide before AI Prompt Management can launch?
Written authorization for the applications and prompts in scope, a list of the AI applications whose prompts should move into the library, and your existing prompts or access to the code where they live. We also need a named technical owner and admin access shared by adding our team as a user or creating a key you control, never sent by email.
Can I cancel maintenance for AI Prompt Management?
Yes, any month. Maintenance starts after the 30 days of post-launch support end and runs month to month with no cancellation fee and no lock-in. It covers monitoring, fixes, updates, a monthly health report and a monthly allowance of change hours.
Stop shipping code every time a prompt needs a word changed.
Order AI Prompt Management and your prompts move into a versioned, testable library on a fixed delivery date. The scope above is what you get, in writing, before you pay.
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