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TKOSolutions
20 Years of Regulated Operations · Human Approval Before AI Outreach

When work gets complex, model calls are cheap. Decision governance is what prevents disaster.

Todd Kovalsky spent 20 years in high-consequence enterprise operations: Apollo Global Management after the 2008 restructuring cycle, Goldman Sachs Asset Management at Sapient, JPMorgan, and national health plan transformations. TKO constructs the deterministic fact layers, exception workflows, and human approval gates required to run mission-critical operations safely.

Inspect the Healthcare Decision LabSee RachelOS Architecture (~2,400 Commits)

20+ Years

Regulated Operations

~2,400

RachelOS Commits

0 Sends

Autonomous AI Outreach

Single Principal

No Delegated Associates

The Industry Contrast

Between Big SI Slide Decks and Fragile AI Wrappers.

The market is drowning in two extremes:

  • 1. Corporate Advisory Fluff:Multi-million dollar roadmaps from legacy consultancies that produce 80-slide decks while delivery teams remain paralyzed by unmodeled exception paths.
  • 2. Twitter AI Agency Slop:Fragile Zapier webhooks and unmonitored ChatGPT API wrappers sold with zero governance, zero audit logging, and zero understanding of regulatory liability.

TKO represents the third way: an enterprise operator who writes code, understands reconciliation under pressure, and bounds automation with deterministic controls.

The Core Thesis

Why autonomous AI fails in high-stakes businesses—and what actually works:

Model Calls Are Commodities

Calling Claude or GPT is a commodity utility. The value sits in what precedes and succeeds the call: the deterministic fact extractors, entity reconciliation, provenance tracking, and failure classification.

Fail-Closed Human Approval Gate

When a model hallucinates in a demo, people laugh. When it hallucinates in a $20M transaction or a clinical determination, you face regulatory investigation. In our systems, model-drafted messages require authenticated human approval. Zero autonomous sends.

Commercial Architecture

The Two Operating Engines

Fixed-price, principal-led engagements built around undeniable operational proof.

Commercial Engine A$15,000 Fixed · 3–4 Weeks

Enterprise Transformation & Readiness Sprint

For Health Plans, Payers & Regulated Healthcare Organizations

For leaders facing CMS-0057-F, state prior-authorization mandates, or core platform migrations. When the executive dashboard is reported green, but nobody can produce the traceable claims artifacts that prove clinical review was safely waived.

The 9-Part Implementation Chain

Policy → Obligation → Capability → Workflow → System → Control → Owner → Evidence → Outcome

  • Obligation Register & Cross-System Impact Map
  • Gap, Dependency, and Accountable Ownership Matrix
  • Executable Implementation Backlog with traceable acceptance criteria
  • Synthetic Decision Lab trace without PHI
Explore the Readiness SprintRun Decision Lab Trace →
Commercial Engine B$7.5K–$15K Build + $1.5K–$3K/mo

Owned Demand & Governed AI Engine (RachelOS)

For Wealth Advisory (RIAs), Boutique Practices & High-Consideration Firms

For firms closing $50,000 to $500,000+ fee transactions tired of the aggregator trap: paying Zillow, SmartAsset, or Angi $40,000+/year for commoditized leads auctioned to four competitors simultaneously.

The Governed Operating Model

Research-Phase Capture → Computed Relationship Graph → Fail-Closed Human Approval Cockpit

  • Captures buyers 60 days before form-fills via long-form domain authority
  • Computed relationship graph with source quote provenance
  • Deterministic Canonical Queue replacing human memory
  • Exact-message human approval cockpit · Zero autonomous sends
Explore Private Client OSInspect RachelOS Codebase →

Living Technical Proof

Inside RachelOS: ~2,400 Commits in Production

RachelOS is a single-operator production proof asset. These redacted screenshots show its workflows and system health; they are snapshots, not live telemetry. AI outreach requires human approval, with zero autonomous outbound sends.

Loading walkthrough…
Walkthrough: See the governed architecture in action: relationship context, visible exceptions, exact-message human review, and reusable domain knowledge. Redacted proof; no live client data.
Exact-Message Human Approval

Zero autonomous sends

Exact-Message Human Approval

Model outputs draft outreach with cited facts, but an authenticated human operator approves the exact message before a single byte leaves the server.

The Canonical Priority Queue

Computed next-best action

The Canonical Priority Queue

A deterministic queue recomputing active work and relationship state across 114 database migrations. No unowned leads or buried follow-up.

Computed Relationship Memory

Institutional continuity

Computed Relationship Memory

Persistent timeline, source quote provenance, and open intelligence gaps held inside the operating system, rather than trapped in an employee's head.

System Health & Orchestration

Observable daily runs

System Health & Orchestration

Scheduled jobs, failure classification, audit spans with correlation IDs, and rate-limit alarms. Running software with inspectable telemetry.

Read the Full RachelOS Case Study & Technical Breakdown

Execution Rigor

The 9-Link Implementation Chain

The method used to reconstruct operational truth across complex payer transformations:

Policy
Obligation
Capability
Workflow
System
Control
Owner
Evidence
Outcome

One principal · Priced up front

Ready to turn complex obligations into executable systems?

Bring one regulatory deadline under pressure or one high-consideration pipeline losing momentum. Work directly with Todd Kovalsky.

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