Agents that do your actual work
Each one is built for a specific workflow your assessment picked out as worth automating, not a generic assistant you have to find a use for. A narrow job is also what keeps its access narrow.
Command Center
Operate your AI. Don't just experiment with it.
Scattered AI experiments become one system you can run, measure, and defend. Command Center is the pattern we build your AI on: every agent scoped to least privilege, every risky action gated by a named human, every action logged as it happens. It is built inside your own cloud, AWS, Azure, or GCP, so your data stays in your environment.
- 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.
We wrap that capability with the controls a real business needs, so the work still gets done and the exposure does not come with it.
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 work.
What we deploy
The work gets done, and you can show exactly how it was done.
Accountable oversight
Every agent reports what it did, where it did it, and under whose authority, so oversight is a record you can read rather than a reconstruction.
Human-in-the-loop control
Nothing with real consequence leaves without a person behind it. Approval gates sit on the decisions you decide are worth a signature, and everything below that line keeps moving.
Compliance evidence
Audit trails and logs captured continuously, ready when you need to show your work.
This is also the part your assessors ask about. A SOC 2 Type II examination cannot test a control that has no population to sample from, and a log written as the system runs is that population. If your obligations run through the NIST AI RMF functions, govern, map, measure, and manage, or through the ISO/IEC 42001 control structure, the same record is what an assessor reads. IntellaGrow holds no certification or attestation against either framework and will not imply one. What we build is the evidence your own auditors ask for.
Once it is running, the next question is how to measure whether a governed system is working .
Deployed today, and in development
What ships today, and what we are still building.
Everything on this page that concerns your deployment ships today: agents scoped to least privilege in your own cloud, approval gates on the actions that carry risk, structured audit logging written as the system runs, and evidence your compliance team can hand to a reviewer. The base system stands up in your cloud within days of the assessment, so you are not waiting months to see something running. The single console, the shared memory layer, and the prebuilt connector library are in active development and are not part of what you buy today. We tell you which is which before you sign, and again at every review.
Deployed in your engagement today
What you buy now
- Governed agents running in your own cloud account AWS, Azure, or GCP. The work happens where your data already lives, so nothing has to leave your boundary to get done.
- Least-privilege identity, scoped per agent Each agent gets the access its job needs and nothing more, mapped to the identity provider you already run.
- Approval gates on the actions that carry risk A named person signs the decisions with consequences attached. Everything below that line keeps moving.
- Structured audit logging, written as the system runs The record exists before anyone asks for it, and it is retained inside your environment.
- Compliance evidence assembled from that log Your audit and risk teams get dated artifacts they can hand to a reviewer instead of a reconstruction.
- Infrastructure as code, with CI/CD Versioned, reviewable, and rebuildable. Secrets are brokered through your own secret manager, never ours.
- A handover runbook Your team can operate what was built. That is the test we design to, whether or not a retainer continues.
In active development
What is coming
- A single console that every agent runs through
- A live oversight view across the whole business
- The agent registry as a shipping module
- The compounding memory layer
- The prebuilt library of skills, plugins, and MCP connectors
- A packaged compliance engine
None of these is part of a current engagement, and none of them is counted in a price.
How early access works
Nothing on the development side is priced, dated, or written into a statement of work. If you want a module as it is built, we tell you what exists, what does not, and what it would take, and it enters a contract only once it runs. Roadmap work is never a reason to sign today.
What we are building next
Beyond the agents: the memory layer and the connector library we are building next.
Roadmap
A memory that compounds.
Most AI forgets, or at best remembers what happened. The memory layer we are building 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.
Roadmap
A library built from the work itself.
A growing library of reusable skills, plugins, and MCP connectors, built from the work itself rather than assembled as a catalogue. Anything reusable from one engagement becomes available to the next. We will show you exactly what exists for your stack before you buy, and we will not count what does not.
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.
You are not locked to one vendor's model, and you are not exposed by the one you pick. The pattern is deliberately model-agnostic and uncompromising about control. We build 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
The Command Center pattern is how we build and embed.
An assessment tells us what to deploy. The build stands up your governed agents and the controls around them. The fractional engagement keeps it governed, maintained, and expanding as your needs grow. It is the delivery system behind every tier of the work.
The delivery system behind every tier
01 Assess 02 Build 03 Embed
The governed system runs underneath: maintained and 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 control point 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 we build the evidence capture and encryption into the deployment, so the audit-ready trail exists before anyone asks for it.
- Is the console, the memory layer, or the connector library part of what I buy today?
- No. What you buy today is a governed deployment in your own cloud: scoped agents, approval gates on risk-flagged actions, audit logging written as the system runs, and the compliance evidence assembled from it. The single console, the compounding memory layer, and the prebuilt connector library are in active development. We tell you which is which before you sign and again at every review, and nothing on the roadmap enters a statement of work until it runs.
- Which capabilities are proven, and which are still being built?
- PresidioFlow is validated in testing, and enterprise adoption is underway. In measured runs on a fixed test corpus it auto-resolved 48 percent of malformed records. That figure is a tested result, and we confirm it against your own data before we quote it back to you. 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 twenty minute intro call is the simplest first step. No pitch, just a clear read on where you stand and what is worth doing next.
If AI is not the right tool for your problem, you will hear that from us.
Just have a question? Call, text, chat, or send a note.