Keep improving what you’ve built.
Ongoing development, support, and optimization for the AI systems, apps, workflows, and tools we build with you.
Launch is not the finish line.
v1 ships · v2 beginsThe first version gets a working AI system into the business. Once people start using it, the real opportunities and gaps show up in ways no plan could predict.
Managed AI gives clients a defined way to keep improving the system after launch, without restarting a project every time something needs to change.
A monthly team for the systems we build.
Managed AI is a defined monthly development and support agreement for the AI systems, apps, websites, workflows, agents, and tools we build with you.
Instead of starting a new project every time something needs to change, we keep a monthly scope open for improvements, fixes, new workflows, user feedback, and ongoing development.
This is not outsourced AI leadership. It is not a loose advisory retainer. It is a way to keep useful systems improving after they are live.
Improve, extend, support, and manage the backlog.
Each month, we agree on the highest-value work inside a defined scope. The work changes as the system, users, and business needs evolve.
Improve what is live
Fix issues, refine the interface, tune AI behavior, and make the system easier to use based on real feedback.
Extend the system
Add new workflows, automations, agents, pages, screens, integrations, or features as new opportunities emerge.
Support the users
Help teams use what has been built, answer questions, resolve friction, and keep the system moving.
Manage the backlog
Maintain a shared list of improvements, prioritize what matters, and agree on what gets done within the monthly scope.
The systems we build do not stand still.
Managed AI applies to the things we build with you: software, websites, workflows, agents, automations, GPTs, integrations, and internal tools.
Software and internal apps
Custom systems, dashboards, portals, and internal tools that need ongoing improvement.
Websites and digital experiences
AI-enabled websites, conversion flows, content tools, and customer-facing experiences.
Agents, GPTs, and assistants
AI tools that retrieve, draft, route, answer, summarize, or support work inside the business.
Workflows and integrations
Automations, data flows, system connections, and business processes that need to evolve over time.
How the rhythm works each month.
Less process, more clarity on what is getting worked on and why.
Review
We look at usage, feedback, issues, and new opportunities from the live system.
Prioritize
We agree on the most valuable fixes, changes, or additions for the month.
Improve
Our team builds, tests, and releases updates within the defined scope.
Extend
As the system proves value, we add new workflows, features, and integrations.
What you get each month.
A clear way to improve live AI systems without turning every change into a new project.
Defined monthly scope.
The work for the month is agreed up front and visible to both teams.
Prioritized backlog.
A shared list of fixes, improvements, and ideas, ordered by value.
Development and support.
Updates, fixes, refinements, and support for the systems we built.
New workflows and enhancements.
Additional capability added as users find better ways to use the system.
A team that knows the context.
The people, architecture, trade-offs, and decisions stay connected.
Built to continue.
Managed AI works best when it follows a system we helped design and build. The same team understands the architecture, workflow, users, and decisions behind it. That continuity lets us move faster and improve without starting from zero.
Build
The system is designed, built, and put into use.
Managed AI
The same team keeps improving it, month over month.
This is not a handoff. It is an ongoing relationship with the work.
Questions, answered.
Practical questions clients tend to ask before they engage.
Q · 01Is Managed AI required after a build?
Q · 02What does the monthly scope include?
Q · 03What happens if we want to stop?
Want to keep improving what you’ve built?
Let’s talk through the system, the backlog, and whether an ongoing improvement model fits.