Administrative Burden
Prior authorization, utilization management, care management, and provider operations create manual work that slows care and consumes operating capacity.
AI-assisted operations modernization
Turn messy work into an operating system your team and AI can actually use.
TKO helps complex service businesses expose hidden handoffs, decision bottlenecks, and knowledge trapped in people, then builds governed AI-assisted workflows that improve speed, accountability, and execution.
Expose
See the real work, including exceptions and undocumented judgment.
Design
Make handoffs, decisions, ownership, and measures explicit.
Implement
Apply AI with evidence, approval, privacy, and auditability.
20+ years in regulated operations
- Apollo Global Management, Leveraged loan and REIT operations through the post-2008 cycle
- Sapient, Platform transformation for Goldman Sachs AM and JPMorgan AM
- FolioDynamix, Wealth platform product ownership through Envestnet acquisition
- ELLKAY, CMS Cures Act / FHIR interoperability platform for payers
- Cognizant, Large-scale healthcare transformation, AI & analytics
- Full career record
Employment history, not client endorsements. Each role is publicly verifiable on LinkedIn.
The Operating Problem
The operation looks orderly on paper. The real work runs through exceptions, memory, and hidden coordination.
That gap is where decisions slow down, senior people become human APIs, accountability blurs, and AI pilots fail to create measurable operating value.
- Recognize the pattern
- Meetings, email, spreadsheets, Slack, or Teams hold the workflow together
- Undocumented judgment determines how exceptions move
- Systems show activity but no trusted next action
- AI tools exist without a workflow, control model, or measurable outcome
Transformation Recovery
Modernization programs can report progress while dependency risk, decision latency, and adoption gaps accumulate between teams.
Key-Person Dependency
Critical knowledge lives in a few key people. When they are overloaded, unavailable, or leave, execution slows down.
Operational Visibility Gaps
Reports show activity and status, but they do not show where work is stuck, who owns the next decision, or which risk needs attention.
Workflow Friction
Teams spend time reconciling status, chasing handoffs, and managing work instead of advancing work.
AI Without Operational Control
AI can summarize or draft, but it does not become trusted healthcare execution unless human approval, workflow fit, and decision rights are designed in.
Featured proof
RachelOS Operational Knowledge System
The business ran on relationships but had no system of action. The data, notes, and messages existed, yet who needed attention and what to do next lived only in one person's judgment. Every priority call and every follow-up depended on that person being available.
Evidence scope: Live operating environment with relationship memory, priority surfacing, action queues, intelligence gaps, outreach drafts, and daily execution support.
View selected workAnonymized enterprise proof
Prior Authorization Workflow Modernization
Administrative review burden persisted because workflow, decision rights, compliance, and human review tiers were not redesigned together.
Evidence scope: Healthcare operating experience across prior authorization, utilization management, compliance logic, and payer/provider workflow complexity.
View selected workInternal proof
CRE Intelligence Model
A commercial real estate research operation held real market insight, but that insight stayed locked in analyst judgment and one-off documents. Every question restarted from scratch, and the firm's intelligence could not compound or be reused across deals.
Evidence scope: Demonstrates method portability across a non-healthcare intelligence workflow.
View selected workOperational truth
Improve the workflow that actually exists, not the one described in the procedure.
TKO connects strategy, workflow, product, technology, and execution so the business can see what is happening, decide what should change, and use AI without surrendering human control.
01
Expose the real work
Map the official process against the exceptions, handoffs, workarounds, and judgment that keep the workflow moving.
02
Design the better operating model
Make decision rights, ownership, escalation, measures, and the trusted next action explicit.
03
Implement and govern AI-assisted workflows
Apply AI only where evidence, privacy, human review, and auditability support a measurable operating improvement.
Method & Evidence Proof
RachelOS: proof the evidence method holds in production.
RachelOS is the reference implementation of how TKO works, not the product TKO sells. It is a live system, built and audited in public, where every capability is graded implemented, activated, validated, or unvalidated. It shows the same evidence discipline TKO brings to a transformation or program assessment. What transfers is the method and its governance, not the software.
Review the RachelOS evidenceWhy this matters outside real estate
Healthcare credibility lane
The method travels. Healthcare remains a proving ground, not the boundary of the business.
Healthcare payer and provider operations make exceptions, administrative burden, auditability, and multi-team dependencies impossible to ignore. The same operating pattern appears in financial services, enterprise technology, investment operations, property operations, and other complex service businesses.
Advisory background
Healthcare Transformation
Prior authorization redesign, care-management modernization, and interoperability work show why the same operating pattern matters where administrative burden, exception handling, auditability, and multi-team dependencies are real constraints.
Operating lesson: Identify the dependency, make the decision path explicit, and build only after the operating truth is visible.
Review the proof registryWhy TKO
The unresolved problems are usually the ones every specialist can see only in part.
Todd is a cross-functional operator who works across strategy, workflow, product, technology, and execution. He finds the gap between the documented process and operating reality, then creates enough structure to improve execution without adding bureaucracy.
AI matters only when it improves a real workflow with clear ownership, source evidence, privacy controls, human approval, and measurable operating value.
Engagement Path
Start with one critical workflow. Implement only what the evidence supports.
The flagship Diagnostic is a fixed-scope, three-week engagement. A separate three-month implementation installs the prioritized workflow, controls, measures, knowledge system, and first practical AI-assisted use cases.
Step 1 · Diagnostic
Operational Truth & AI Workflow Diagnostic
- Duration
- 15 business days
- Commercial model
- Fixed-scope engagement
In three weeks, identify where one critical workflow is losing time, knowledge, and accountability, then define a governed AI-assisted operating model and prioritized 90-day plan.
Outcome: The real workflow, including exceptions, workarounds, and undocumented judgment.
View diagnosticStep 2 · Implementation
AI-Assisted Operations Implementation
- Duration
- 3 months
- Commercial model
- Separate implementation scope
Install the prioritized workflow, operating cadence, controls, measures, knowledge system, and first practical AI-assisted use cases identified by the Diagnostic.
Outcome: A working operating model for the prioritized workflow.
View implementation
Operational truth conversation
Bring the workflow your best people keep holding together.
Describe the handoffs, exceptions, delays, and decisions under pressure. TKO will help determine whether a focused Diagnostic is the right next move.