01
Support triage and resolution
Classify requests, retrieve context, draft a response, route exceptions, and capture feedback.
Measures
First response, resolution time, human minutes, reopen rate
Accountable AI delivery
Turn one expensive workflow into a controlled, measurable AI process.
I help mid-market B2B software and technology-enabled service companies move one customer or service operation from baseline to controlled production in six weeks - without hiring a full-time AI executive.
Where value gets trapped
Customer operations with a baseline, an owner, and a measurable result.
The work starts where operating friction is already visible. The goal is not to add AI everywhere; it is to improve one consequential process and make the result legible to the people accountable for it.
02
Customer onboarding and implementation
Coordinate intake, dependencies, handoffs, status updates, and exception ownership across teams.
Measures
Cycle time, stalled accounts, rework, time to value
03
Knowledge management and internal search
Make approved product, policy, and account knowledge retrievable inside the daily workflow.
Measures
Search time, answer quality, escalations, adoption
04
Product feedback classification
Normalize qualitative feedback, identify themes, connect evidence, and support prioritization.
Measures
Handling time, coverage, theme quality, decision latency
05
Customer health and QBR reporting
Assemble account signals, flag risk, draft narratives, and keep a human accountable for the readout.
Measures
Preparation time, coverage, risk detection, follow-through
06
Service-delivery handoffs
Move work between sales, onboarding, support, delivery, and finance with explicit owners and exceptions.
Measures
Queue age, missed handoffs, rework, customer delay
Engagements
Start with the decision. Expand only after the result is controlled.
01The starting point
AI Workflow Value Diagnostic
$7,500 introductory fee
10 business days
Published next-stage price: $12,500 after the first two clients
A fixed-scope decision package for one high-friction workflow - before anyone buys another tool or starts another pilot.
Current-state workflow and exception map
Baseline economics and measurable success criteria
Use-case, data, integration, and risk scorecard
Build, buy, configure, or simplify recommendation
Human controls, evaluation, logging, and accountability plan
Executive ROI model and six-week implementation plan
Terms 50% at signing and 50% at the executive readout. $5,000 is credited toward a sprint signed within 30 days.
02After the diagnostic
AI Value-to-Production Sprint
$30,000-$45,000
Approximately 6 weeks
One narrowly scoped workflow taken into controlled production for one team, with delivery leadership and measurement included.
Production workflow and required integrations
Human approvals and exception handling
Evaluation, monitoring, and audit logging
Team enablement and operating runbook
Baseline-to-result measurement and executive readout
Terms 40% at signing, 30% at approved design, and 30% at controlled launch.
03After a successful launch
Fractional Head of AI Delivery
$12,000-$18,000 per month
3-month minimum
Limited-scope leadership for the roadmap, executive steering, vendors, governance, adoption, cost control, and value realization.
Prioritized AI portfolio and roadmap
Business cases, baselines, and value reporting
Build-versus-buy and vendor decisions
Governance, cost controls, and human-control patterns
Adoption, training, and executive steering
Terms Monthly in advance with explicit days, decision rights, and a one-to-two-day-per-week cap.
04For deal teams and investors
AI and Technical Due Diligence
$10,000-$20,000
Fixed scope
A private, referral-led assessment of architecture, product, cloud economics, AI claims, security exposure, technical debt, and post-close priorities.
Architecture and scale assessment
AI-claim and product-roadmap validation
Cloud cost and engineering-capacity review
Security, key-person, and technical-debt exposure
Prioritized post-close actions
Terms Scoped to the transaction and decision timeline.
Delivery control
A production result executives can inspect, govern, and measure.
01
Baseline
Quantify the workflow before changing it
Volume, labor, cycle time, rework, errors, escalations, and customer impact become the starting line.
02
Decide
Choose build, buy, configure, or simplify
The answer is vendor-neutral. AI is used only where it improves the economics or operating result.
03
Control
Design approvals, exceptions, and accountability
Security, privacy, evaluation, logging, human review, and failure handling are designed before launch.
04
Launch
Put one workflow into production for one team
A controlled release, explicit owner, team enablement, and operating runbook keep the change usable.
05
Measure
Report the result against the baseline
Executives see operational and financial movement, not a demo count or a vague AI-adoption metric.
A bounded first conversation
Bring one workflow, one accountable owner, and the pressure behind the decision.
The fit call determines whether the workflow has a credible baseline, implementation capacity, decision owner, and budget. The analysis itself begins in the paid diagnostic.