Find and fix the money leaking out of your AI and engineering budgets.
I help CFOs, CEOs, and technology leaders stop unpredictable AI invoices, eliminate unmonitored software waste, and protect gross margins before board meetings.
Where is our monthly AI spend actually going?
Which engineering projects produce revenue vs. burn cash?
How do we enforce spending guardrails before budget overruns?
Richard Ewing - Founder of Exogram & CareerWin
11,141+ LinkedIn Followers · 1,400+ Executive Subscribers · 778 AI Citations
10-Second Budget Leak Calculator
Estimate your enterprise's unmonitored AI & engineering capital loss
Based on standard 18%–35% unmonitored inference & labor overhead metrics
From Free Benchmark to Enterprise Governance
15 quantitative questions to score AI cost visibility & maturity.
30-minute rapid-fire sync to pinpoint immediate API & cloud leaks.
60-minute intensive code & PDI evaluation for technical debt.
3-week forensic codebase audit & 40-page written executive brief.
Ongoing CPO/CTO direction, architectural veto, and board defense.
As Seen In
15+ Years Experience
Enterprise product leadership
0-to-1 $25M ARR
Tyler Technologies
Found $840K Hidden AI Spend
CTO, Series C FinTech (verified)
$2.9K/mo API Cap Implemented
B2B SaaS Margin Recovery
As Published In & Cited By
Read by 1,400+ C-suite executives, financial analysts, and technology leadership
Three Problems That Cost Enterprise AI Teams Real Money
These are not hypothetical risks. They are measurable capital leaks I find in every audit.
UNPREDICTABLE AI INVOICES
Unmonitored AI usage is shrinking gross margins.
AI spending is erratic because nobody is tracking cost per transaction.
Uncapped monthly API invoices, unmonitored vendor usage, and runaway computational loops create budget overruns with zero financial accountability attached.
Average unmonitored AI overspend found per audit
UNMONITORED SECURITY RISKS
Unmanaged employee AI tools create compliance and data liabilities.
Employees are sharing company data with public AI tools without oversight.
Unregistered AI tools create data leakage risks. Without explicit administrative controls, internal financial plans and customer records risk exposure to external systems.
of companies lack executive AI data policies
UNVERIFIED AI CODE LABILITIES
AI-assisted software development inflates future maintenance costs.
AI-generated software looks complete - until maintenance bills triple.
Developers using AI assistants often ship high volumes of unverified software. Without technical governance, this creates technical debt that slows future feature delivery.
engineering capacity consumed by software maintenance
How It Works
Three steps. Each one produces a concrete deliverable you can act on.
Diagnose
Measure your financial exposure
Run the free 10-second AI & Engineering Budget Leak Benchmark to estimate your unmonitored overspend. Or book an executive rapid audit for a 30-minute scan of your cloud and AI invoices.
Run free benchmarkAudit
Uncover hidden budget leaks
An Engineering Financial Audit ($2,500 - $7,500) analyzes where your tech budget actually goes. You receive a clear executive report with dollar-denominated findings and immediate savings opportunities.
Review audit packagesGovern
Install automated cost guardrails
Implement automated spending limits, vendor access controls, and real-time usage rules. Move from unpredictable AI invoices to guaranteed, capped operating costs.
Explore cost governanceWhat is an AI Economist?
An AI Economist is the financial strategist operating between engineering production and CFO-level profitability. They audit tech spend, measure AI unit economics, and install automated cost guardrails to protect gross margins.
- Audits LLM inference costs and cloud GPU utilization across engineering workflows.
- Establishes unit-economic visibility connecting API consumption to customer gross margins.
- Installs automated cost-caps and real-time runtime rate limits to prevent budget overruns.
The Reality of AI Investments
Stop guessing where your AI budget is going. Turn chaotic R&D spend into predictable financial assets.
Unknown AI costs
Hidden engineering waste
Shadow AI exposure
Reactive governance
Finance distrusts engineering
Measured AI spend with unit economics
Known R&D capital allocation
Policy-enforced AI access controls
Predictable margins with cost-caps
CFO and CTO aligned on AI ROI
Audit Outcomes - Before & After
Real results from R&D Capital Audits. Dollar-denominated findings with measurable remediation.
maintenance costs reported as “innovation”
AI cost reduction achieved
engineering capacity recovered
Results from anonymized R&D Capital Audit engagements.
See how an audit works for your organizationStop Guessing Your AI ROI.
Inspect the Math.
Whether you need an immediate rapid evaluation or an enterprise governance implementation, we follow a strict diagnostic progression to eliminate wasted spend.
AI Economics Score
Answer 15 quantitative questions to measure your AI unit economics, cost visibility, and governance maturity.
- Immediate 0-100 score
- Estimated margin leakage %
- Printable PDF report export
Rapid Gut-Check
A 30-minute rapid-fire session to review your AWS/API bill, unit economics, and velocity. Immediate verdict on whether your setup is at risk.
- 30-min 1-on-1 with Richard Ewing
- AWS / API billing leak scan
- 1-click Stripe checkout
Fractional CTO / Retainer
Dedicated fractional technology direction, installing deterministic runtime controls, cost ceilings, and board-ready reporting.
- Strict Cost-Cap Architecture Reviews
- Zero Shadow AI Governance
- Board Meeting Representation
The AI Economist Newsletter
Subscribe and get the R&D Audit Checklist - The 15 questions I ask in every $7,500 engagement.
Monthly. No fluff. 2,000+ executives read before they decide.