Enterprise AI — discovered, governed, and delivering.
Advisory and implementation across the full AI lifecycle — utilization, risk, governance, cost, ROI, adoption, and audit — and all in one place, our Eagle AI Command Center.
AI is spreading through the enterprise faster than anyone can track it.
Staff and departments adopt tools on their own, spend accelerates without a unified view, and leadership is left without a clear picture of who is using what, with which data, at what cost — or what it’s returning. Getting a handle on all of it is now an operational necessity, not a someday project.
Most organizations are flying blind.
Three problems, compounding: nobody can see the AI, nobody can prove its value, and the exposure keeps growing.
Two tiers. One command center.
Eagle AI works on two fronts — and unifies them in a single console that keeps a keen eye on every AI in your enterprise.
Govern the AI you already have
Take control of the sanctioned, shadow, and embedded AI already running across your enterprise.
Implement the AI you need next
Select, build, pilot, and adopt high-value AI — expert-led, end to end — then hand it to managed support.
Eagle AI Command Center
One console monitors utilization, cost, and ROI across both tiers — and across your EHR, ERP, and enterprise applications.
Take control of the AI you already have.
Four coordinated moves turn ungoverned, shadow, and embedded AI into a discovered, costed, governed, and audited estate — the foundation everything else builds on.
AI Discovery — utilization & risk
We establish ground truth: every AI tool in use across the enterprise, who is using it, how, and with what data — surfacing PHI and sensitive data leaving the perimeter, and turning the unknown into a complete, evidenced inventory you can defend.
Governance & monitoring
Continuous oversight of all AI through the Eagle AI Command Center — monitoring utilization in real time, flagging misuse the moment usage drifts outside policy, and enforcing that only approved platforms reach your systems and data.
Roadmap, cost & ROI
An implementation roadmap with costs attached — picking the right projects, knowing where AI fits among your enterprise applications, driving adoption, tracking spend tool-by-tool, and tying every AI dollar to measurable return the board can see.
Audit & reconciliation
SOX-style audits of every tool against its contract — remediating misuse, pulling back exposed data that should never have been public, and delivering a completed report with prioritized recommendations to ensure compliance and mitigate risk.
Learn more about AI auditing →Continuous control, not a one-time scan.
The Eagle AI Command Center is an Azure-hosted hub deployed in your environment — watching AI utilization in real time and governing which AI can reach your systems and data, long after the initial assessment is done.
- Monitor & flag misuse — utilization tracked continuously, with alerts the moment usage drifts outside policy.
- Enforce approved platforms — technical controls ensure AI runs only on approved platforms, through approved gateways.
- Govern access — control which AI tools and agents can reach core systems and data, closing the gaps attackers exploit.
Including the AI already inside your systems. The Command Center doesn’t stop at shadow AI or the solutions we build — it monitors the utilization, cost, and ROI of AI embedded in the applications you already run:
31.5% of hospitals already run GenAI inside their EHR, Epic has ~125 GenAI features in development, and Gartner expects 40% of enterprise apps to embed AI agents by the end of 2026 — embedded AI is the fastest-growing blind spot.
People and technology, phase by phase.
Every phase pairs named roles with purpose-built tooling — tap through to see exactly what happens and who does it.
Engage & Intake
We get you started. A dedicated project manager and account executive kick off the engagement, align stakeholders, and set the cadence.
The first thing out the door is an enterprise AI-use questionnaire — issued across the organization to begin gathering usage information before any tooling goes in, so discovery starts with human intelligence, not just network data.
Discover
We establish current utilization and risk. Traffic monitoring, packet inspection, and end-user copy/paste-pattern detection reveal every AI touchpoint — sanctioned or shadow — including what data is flowing into each tool.
The outcome is a defensible, organization-wide AI inventory: who is using AI, how it’s being used, and where PHI or sensitive data is leaving the perimeter.
Command Center
A senior build analyst deploys the Azure-hosted Eagle AI Command Center in your environment — standing up AI-utilization monitoring and approved-platform enforcement.
From this point forward, oversight is continuous: usage that drifts outside policy is flagged in real time, and only approved platforms reach your systems through approved gateways.
Cost & ROI
An AI cost analyst stands up per-tool cost monitors and integrates with your ERP to automate cost capture — or starts with a manual report and scales up.
Spend rolls into one view of total AI cost, tied to ROI tracking — so the return on each investment is measured, not assumed, and finally reportable to the board.
Audit & Reconcile
A legal analyst reviews every tool against its contract and terms, running quarterly SOX-style audits — with remediation of HIPAA violations and engagement of unapproved platforms to erase misuse and pull back exposed data.
A Power BI analyst compiles everything into ongoing reporting: a completed audit with prioritized remediation recommendations, keeping AI compliant and risk contained quarter after quarter.
How the audit works →AI Audit & Reconciliation
Every vendor contract reconciled against command-center telemetry — quarterly, SOX-style, with remediation until the data is provably gone.
Building new AI is where projects die.
Enterprises don’t struggle to want AI — they struggle to pick the right use case and get it into production. Without a disciplined, expert-led framework, the investment quietly disappears.
From idea to adopted, monitored solution.
A disciplined path with domain experts working alongside your operations and technology teams at every step.
Prioritize with a grading system
The biggest opportunities aren’t inside any one platform — they’re in the gaps between them, where work crosses teams, staff do manual effort, and people hunt for information. That’s where AI earns its keep.
We identify roughly five candidate processes and score each against what matters in healthcare — patient safety and care first, then revenue and efficiency — so the roadmap starts with the highest-value, lowest-regret build. Criteria and weights are set with your teams.
Confirm with experts
Deep operational and clinical experts — people from the same fields as your teams — embed with your operations and technology staff to confirm what’s actually needed and design the optimal solution.
A financial analyst validates cost and ROI before a line of code is written — organizations that redesign workflows before choosing models are twice as likely to see returns.
Build & pilot
We build and test the solution, then pilot it with a small team — gathering feedback, adjusting, and confirming the value case before anything scales.
Everything is built in your own Azure environment, so PHI never leaves your boundary and the deployment inherits Microsoft’s certified, audit-ready security — HIPAA, HITRUST, SOC 2 — without months of standing up controls.
Train & adopt
Training, guidance, and adoption support carry the solution from pilot to everyday use — because success in AI is mostly people and process, not the model.
As adoption ramps, the solution is connected to the Eagle AI Command Center on Azure — so utilization, cost, and ROI are monitored from day one of production.
Managed support
Once adoption and utilization are confirmed, the solution transitions to ongoing managed support — maintained, monitored, and continuously reported through the Command Center.
Your teams keep the value; we keep the watch.
Not just a platform — people who know your business.
Every engagement is staffed with experts in the specific verticals of your business — the strategy, the delivery, the technology, and the operations it runs on.
Advisory
Strategic guidance from people who have delivered what they advise on — the right projects, the right sequence, the right investment.
Project Management
Disciplined delivery leadership that keeps complex AI initiatives on schedule, on budget, and honestly reported.
Technical Expertise
Engineers who build and integrate — Azure, networks, security, ERP, and the systems AI has to live alongside.
Deep Operational Expertise
People who have worked inside each vertical of the business — clinical, financial, administrative — and know how the work actually flows.
Visibility and control pay for themselves.
saved per breach by organizations using AI and automation extensively in security — with incidents contained 80 days faster.IBM / Ponemon, 2025
less per breach when issues are found internally rather than disclosed by attackers — visibility only active governance provides.IBM / Ponemon, 2025
integrated governance gives visibility into every AI deployment — including shadow AI — so teams can scale AI with confidence.IBM / Ponemon, 2025
See how this plays out on real projects.
Representative engagements across our four practices — the patterns, the outcomes, and the way we work.
Know what AI you have. Govern it. Prove it.
Eagle AI governs the AI you already have, implements the AI you need next, and monitors all of it — EHR, ERP, and enterprise applications included — from one command center.