Specialized agents
Purpose-built agents for the specific workflows your assessment identifies, not a generic assistant.
Command Center
Operate your AI. Don't just experiment with it.
Command Center is the hub we deploy to run AI agents across your business, instrumented for oversight, approval, and compliance. It runs inside your own cloud, AWS, Azure, or GCP, so your data stays in your environment, and scattered AI experiments become a system you control.
- AI agents
- Permissioning
- Command Center
- Approval gate
- Audit + evidence
The governance difference
The agent is the easy part. Governing it is the job.
Powerful open-source AI agents are everywhere now, and most of them ship with broad access to your shell, files, and browser the moment they're installed. That's fine on a personal laptop. In a regulated business, an ungoverned agent with that much reach is a liability waiting to happen.
Command Center wraps that capability with the controls a real business needs.
Ungoverned Broad access to your shell, files, and browser. A liability.
Governed Scoped, permissioned, approved, and audited.
- Permissioning Every agent gets only the access its job requires.
- Audit logging A complete, reviewable record of what the system did and why.
- Approval gates A human signs off on the actions that matter.
- Compliance instrumentation Evidence is captured as the system runs, not reconstructed after the fact.
The runtime is a commodity. The governance is the product.
What it does
One surface for the AI running across your business.
Central oversight
See what every agent is doing from one place, with real telemetry instead of guesswork.
Human-in-the-loop control
Approval gates on the decisions that carry risk, so automation never runs unsupervised where it shouldn't.
Compliance evidence
Audit trails and logs captured continuously, ready when you need to show your work.
What sets it apart
It is not just agents. It is memory that compounds, and a library that already knows the work.
A memory that compounds.
Most AI forgets, or at best remembers what happened. Command Center remembers what you tried and whether it paid off. It turns your memory from "what happened and what we know" into "what we tried and whether it worked", the only kind of memory that compounds into better decisions over time.
A library that already knows your business.
Command Center comes with a deep library of custom skills, plugins, and MCP connectors that handle real work across the business, from operations to compliance to data. You are not starting from a blank agent. You deploy capability that already exists, governed from day one.
Any model, one governed surface
Frontier models Open-source agents Your tools & data
Command Center Permissioning · Approval · Audit
Deployed into your environment
Built on your stack, governed by ours
Model-agnostic. Deployed into your environment. Governed by default.
Command Center is flexible about which models and tools it runs, and uncompromising about how they're controlled. We deploy it into your environment with guardrails set to your risk and compliance requirements, so you get the capability without inheriting the exposure.
Where it fits
Command Center is how we build and embed.
An assessment tells us what to deploy. The build stands up Command Center and your agents. The fractional engagement keeps it governed, maintained, and expanding as your needs grow. It's the delivery system behind every tier of the work.
The delivery system behind every tier
01 Assess 02 Build 03 Embed
Command Center runs underneath: governed, maintained, expanding
See it work
Walk a task through the governed loop.
An illustrative demo of the mechanism, not live client data. No real patient information is used. Advance each step to see how the loop keeps a high-risk action permissioned, approved, and recorded.
Trigger: a task arrives
A new task lands in the queue: summarize an inbound patient message for the care team. The governed loop starts here.
Inbound task
Summarize an inbound patient message for the care team.
The agent proposes an action
The agent revised its draft after your requested changes.
The agent drafts the summary and requests only the data it needs to do the job. Least privilege: it cannot reach anything it was not scoped for.
Data the agent requested (minimum needed)
- The message text
- The assigned care team
Not requested: the full medical record, billing, or message history.
A human approves what carries risk
The output will reach a clinician, so it is flagged high-risk and held at an approval gate. Nothing is sent until a named person approves it.
High-risk, awaiting approval
Routed to: Care Team Lead (sample approver)
Approved, the action runs
The summary is delivered to the care team. It ran only after the gate, with only the data the agent was scoped for.
Delivered
Summary sent to the care team.
The record stands on its own
Every step is captured as it happens, not reconstructed later. This is what an auditor sees.
What you are buying, and what you own
Plain answers, before you commit.
Command Center is a configured, governed stack we deploy into your own cloud, not a product you rent and not a document you file away. Here is exactly what that means for what you buy, what stays yours, and who keeps it running.
What you own after the project
- The deployed system, running in your own cloud account.
- Your data, which never leaves your environment.
- The audit trails and compliance evidence it captures.
- The prioritized roadmap and risk register from your assessment.
Command Center · governed flow
Every action runs through the governed hub inside your cloud: permissioned, approved where it matters, and recorded on a continuous audit log you own.
- Is Command Center proprietary software, a reference architecture, a configured stack, or a managed service?
- It is a configured, governed stack we deploy into your environment. Not a multi-tenant product you log into, and not a slide-deck reference architecture. We stand up our governance layer, permissioning, approval gates, audit logging, and compliance instrumentation, together with the specific agents your assessment prioritizes, and configure it to your risk and compliance requirements. The frontier models and open-source agents underneath are swappable commodities. The governed layer is what we build.
- What do you own after the project?
- The deployed system. It runs in your own cloud account, AWS, Azure, or GCP, your data stays in your environment, and the audit trails and evidence it captures are yours. From the assessment, you also own the prioritized roadmap and the risk register.
- Is there a license or platform fee beyond the build and the fractional retainer?
- No. There is no separate platform or license fee beyond the Build project and the Fractional retainer. You own the deployed system in your own cloud account, and you pay your cloud provider and model-usage costs directly, at cost, with no markup from us.
- What happens if you end the retainer?
- The system stays in your own cloud account and keeps running. It is designed to be run by your team or with ongoing senior ownership, so ending the retainer does not switch it off or take it away.
- Who maintains the connectors, agents, prompts, policies, logs, and model changes?
- While the Fractional engagement is active, we do. Keeping the system governed, maintained, and expanding is the engagement itself: connectors, agents, prompts, and policies, and adapting as the underlying models change. The audit logs are captured continuously by the system. Without a retainer, maintenance sits with your team, which is why the system is built to be run by your team.
- How is it secured, and what does the governance enforce?
- It runs inside your own cloud, so your data stays in your environment. Access is scoped per agent through permissioning, the actions that carry risk pass a human approval gate, and the Compliance Engine captures and encrypts audit-ready trails.
- Which capabilities are production-proven, and which are still a prototype?
- PresidioFlow is a prototype. In measured test runs it auto-resolved 48 percent of malformed records, a measured prototype result, not a guarantee and not a production track record. The governed deployment model, permissioning, approval gates, audit logging, and compliance evidence, is what we build and run for you.
Ready when you are
See whether a governed AI system is right for your business.
A short working session is the simplest first step. No pitch, just a clear read on where you stand and what is worth doing next.
Just have a question? Call, text, chat, or send a note.