AI-Ready, Audit-Ready Datafor Federal & Enterprise Organizations
TREES Technologies LLC helps mission-driven organizations transform fragmented data into secure, governed, and decision-ready assets aligned with DAMA DMBOK principles — before an implementation dollar is obligated.
No cost · No obligation · TS/SCI cleared team · Response within 24 hours
Data Readiness Dashboard
AI Readiness Score
3 governance gaps must be resolved before AI deployment
Company Overview
AI Technology with Purpose
A 30-second look at how TREES Technologies delivers AI-ready, audit-ready data for federal and enterprise organizations.
The Root Cause
Most Organizations Are Not Ready for AI Because Their Data Is Not Ready
The technology is ready. The vendors are ready. But the data foundation that determines whether AI succeeds or becomes an audit finding — that is where the gap lives.
Fragmented Data
Data lives in silos across legacy systems with no unified ownership, no shared definitions, and no authoritative source of record. AI models trained on this data produce unreliable outputs — and no one can explain why.
Weak Governance
Without defined data stewardship, access controls, and policy enforcement, agencies cannot demonstrate to auditors who owns the data, who has touched it, or what standards it was held to.
Limited Lineage
When no one can trace a data element from origin to consumption, AI outputs are legally and operationally indefensible. Inspectors General have cited lineage gaps as a primary failure mode in federal AI programs.
DAMA DMBOK-Aligned
Premium Data Consulting Services
Three service lines designed to address the specific data conditions that determine whether a federal AI initiative succeeds or becomes an audit finding.
Data Governance & Compliance
We establish formal governance structures that survive federal audits — from initial design through every subsequent oversight cycle.
- DAMA DMBOK-aligned governance policy development
- Data stewardship roles, accountabilities & escalation paths
- Regulatory alignment: FISMA, FedRAMP, NIST 800-53
- Defensible audit trails and records management frameworks
Data Quality & Lineage Engineering
We establish measurable quality standards and document every data element from origin to output — creating the evidentiary record your IG requires.
- Data profiling, scoring & quality baselining across domains
- End-to-end lineage documentation and traceability mapping
- Metadata cataloguing aligned to agency data dictionaries
- Continuous data quality monitoring and alerting pipelines
AI Readiness Data Platforms
We conduct structured readiness assessments before implementation — identifying the gaps that would otherwise surface as program failures or GAO findings.
- Structured AI readiness assessment (4-week fixed delivery)
- Legacy data modernization strategy & sequencing roadmap
- Cloud data platform architecture for federal AI workloads
- Independent vendor oversight and deliverable accountability
Industry Standard Framework
Aligned With the DAMA Data Management Framework
The Data Management Body of Knowledge (DAMA DMBOK) is the internationally recognized standard that federal auditors, program managers, and oversight bodies use to evaluate data maturity. Every engagement we deliver is structured around its six core knowledge domains.
"The agencies that get AI right are the ones that got their data right first."
After 30 years inside the federal data systems now targeted for AI modernization, we know precisely which foundations hold and which ones collapse under the weight of a modern AI workload.
Results & Outcomes
Mission Outcomes We Help Deliver
Federal agencies don't measure consulting success in deliverables — they measure it in risk avoided, audits survived, and initiatives that reach operational status on time and within appropriated funding.
What our clients gain
- Improved data trust across your organization
- Reduced audit risk and IG exposure
- Clear data ownership and stewardship roles
- AI-ready datasets that meet model input standards
- Secure cloud data foundations aligned to FISMA
- Better executive decision-making with reliable data
- Documented lineage for every mission-critical dataset
- Governance policies that survive outside scrutiny
Federal & State Agencies in Our Engagement History
What Federal Agencies Pay for Skipping This Step
A Data Readiness Assessment is not an optional pre-engagement activity. It is the difference between a federal AI program that succeeds and one that becomes a line item in the next oversight report.
Federal AI programs that launch without validated data foundations routinely experience cost growth of this magnitude before the first usable output is delivered.
Data quality, lineage, and governance failures are consistently among the most cited findings in Inspector General and GAO reviews of federal IT modernization programs.
Discovering data problems post-contract adds an average of one to three years to federal AI timelines — time spent remediating what an upfront assessment would have surfaced in four weeks.
A 4-week assessment costs a fraction of what unresolved data problems cost after implementation begins.
Federal decision-makers who engage us before implementation avoid the findings, overruns, and delays that define the programs that don't.
Why TREES Technologies LLC
The Credential Gap Most Consultants Cannot Close
There is no shortage of data consultants. There is a significant shortage of consultants who operated inside the federal systems they now advise agencies to modernize — under real security constraints, with real mission consequences.
Currently supporting the Defense Health Agency (DHA).
TS/SCI Cleared Leadership
Active clearance grants access to classified data environments where the most consequential federal AI work happens. No security boundaries. No uncleared handoffs.
Federal & DoD Mission Experience
30 years managing DoD databases at NAVAIR, DPAA, and MISA — and currently supporting the Defense Health Agency (DHA).
SQL Server, Azure & Cloud Data Expertise
Deep technical fluency across the data platforms federal agencies actually use — from legacy SQL Server environments to modern Azure and cloud-native architectures.
Security-First Delivery
Every engagement is designed around security from the first day — not bolted on at the end. FISMA, NIST 800-53, and FedRAMP compliance built into the workflow.
Ready to Know If Your Data Is AI-Ready?
Start with a 30-minute executive Data Readiness Review. No cost, no obligation — a real conversation about your data risk before implementation begins.
About the Founder
Rótìmí Shódíyà, MBA
Founder & Chief Executive Officer
Pronounced: Mí-Dò-Mí | Mí-Mí-Dò
For 30 years, Rótìmí managed mission-critical databases for federal defense agencies where failure was not measured in downtime — it was measured in mission compromise. He managed and secured mission-critical database systems at NAVAIR, DPAA, and MISA, and currently supports the Defense Health Agency (DHA).
He observed the same pattern across three decades: agencies committing hundreds of millions to new technology before establishing the data foundation required to support it. In 2022, he founded TREES Technologies LLC with a specific mandate: intervene before the investment is made, not after.
Simultaneously, he served as a Maryland Executive Service appointee under the Governor, leading statewide IT modernization — giving TREES unique operational credibility across both federal and state government environments.
Schedule a Data Readiness Review
Before your agency commits to an AI investment, you need an honest, independent assessment of your data foundation. Start with a no-cost 30-minute consultation — we will tell you directly what is ready, what is not, and what the risk exposure is.
✅ No cost, no obligation · ✅ TS/SCI cleared advisory team · ✅ Response within 24 hours
🔒 Security Notice: All inquiries are reviewed directly by our team. This form is protected against automated submissions.
Phone
+1 (240) 381-0055Location
Washington, DC Metro AreaBusiness Hours
Ready to Know If Your Data Is AI-Ready?
Start with a 30-minute executive Data Readiness Review — before a single implementation dollar is obligated.