Customer service
Today
Agents search several systems to answer the same questions.
With AI in place
Draft answers come from your own knowledge base, and a person approves them before they go out.
AI enablement · Consulting & fractional leadership
Put AI to work where it moves your numbers.
AI aimed at faster, lower-cost work inside your company, and at loyalty, revenue, and market position with your customers. Chosen for your business, built on your data, and measured on your numbers.
AI Value Diagnostic · Week 4
Ranked AI opportunities
| Use case | Value |
|---|---|
| 1Support ticket triage and draft replies | |
| 2Quote and proposal drafting | |
| 3Field-service fault diagnosis | |
| 4Invoice and contract review | |
| 5Demand forecasting |
What your company gets
What an engagement aims to move, measured on your own numbers.
Results land in two places: inside the company, and with your customers. Every engagement starts by agreeing which numbers should move. Where a number can be measured today, that baseline is how we both judge the work. Where a result only shows up later, we agree up front when and how it will be measured.
Inside the company
Run the business better
Better quality of work
AI checks documents, data, and decisions, and people review the exceptions. The goal is fewer errors and less rework.
Measured byError rate, rework hours
Faster execution
Routine steps in quoting, triage, reporting, and approvals move to AI, so work waits less.
Measured byCycle time, turnaround
Time and cost savings
The aim is to return hours spent on repetitive work and lower the cost of each unit of work.
Measured byCost per ticket, order, or claim
More effective people
Your team is trained to work with AI, so skilled people can spend more of their time on judgment calls.
Measured byHours returned to skilled staff
With your customers
Grow the business
Smarter products and services
AI built into what you sell, designed around your customers and your own data.
Measured byAdoption, attach rate
Better customer experience
Aimed at faster, more accurate answers and service, with a person behind every decision that matters.
Measured byResponse time, satisfaction
Loyalty and revenue
Aimed at service that keeps customers and follow-through that turns interest into sales.
Measured byRetention, revenue per customer
Stronger market position
Capabilities built on your own data and process, which are harder for competitors to copy.
Measured byWin rate, share of target accounts
What it can look like in your business
Less busywork. Faster answers. People on the work that matters.
The right use cases depend on your business and your data. These are the kinds of changes a Diagnostic looks for.
Sales
Today
Quotes and proposals are rebuilt from scratch every time.
With AI in place
First drafts are assembled from past wins and your pricing rules, ready for a rep to finish.
Operations & field service
Today
Finding the cause of a fault depends on your most experienced people.
With AI in place
Equipment and ticket history point technicians to the likely cause before they roll a truck.
Finance & back office
Today
Invoices, contracts, and reconciliations are keyed and checked by hand.
With AI in place
Documents are read and matched automatically, and only the exceptions go to a person.
Product & engineering
Today
Engineers spend hours on boilerplate instead of the product.
With AI in place
AI coding tools are used with review and testing standards, aimed at more output without losing quality.
Risk & compliance
Today
People use AI tools with customer data and no policy.
With AI in place
A clear policy, approved tools, and a record of every model in use.
What we build together
From agents to your own private AI.
Everything is designed around your data, your systems, and your people, including AI that runs on your own hardware when your data can't leave the building.
01
Agents and automation loops
AI agents that carry out multi-step work across your systems, designed with feedback loops that measure their work and feed corrections back in.
02
Guardrails and governance
Evaluation, human review, approvals, and policy built around every AI system, so you can see how it performs and explain it to a board or auditor.
03
Private AI on your own hardware
Help defining and designing your own internal AI model, running on your hardware, with agents built on your own data sets.
04
Training and capability building
Customized training and coaching so your people can run, extend, and govern what gets built.
How an engagement runs
From idea to working system to your team.
Every phase ends with something you can hold, use, and measure.
- 1
Weeks 1–4
Diagnose
Interviews with your leaders, a review of your data and systems, and a ranked list of AI opportunities, each with a dollar target and an owner.
You'll have
- Opportunity map
- Risk register
- 90-day plan
- 2
Weeks 5–12
Deliver
The top one or two use cases built into daily work over 4–8 weeks, with evaluation, monitoring, and human review from the start.
You'll have
- Working AI workflows
- Evaluation scorecard
- Before-and-after measurement
- 3
After delivery
Run and hand off
Your team is trained, owners are named, and results are reviewed monthly. If you need a leader in the meantime, the seat is filled part time.
You'll have
- Handoff playbook
- Monthly value scorecard
- A team that runs it
What you walk away with
Assets you keep, not slides you file.
- 01
Opportunity map
Every AI idea worth considering, ranked by value, feasibility, data readiness, and risk.
- 02
90-day plan
What gets built first, who owns it, and the number it has to move.
- 03
Working AI workflows
Systems in daily use by your people, not demos waiting for approval.
- 04
Evaluation scorecard
How accurate the AI is on your own work, and an alert when it drifts.
- 05
AI policy and approvals
Which tools are allowed, with what data, and who signs off.
- 06
Trained team and playbook
People coached to run and improve it, and a playbook for after the engagement ends.
How we work together
Inside your team, beside your board, or in front of your people.
Each engagement is shaped to your company. A fixed-fee AI Value Diagnostic is the recommended place to start.
Embedded enablement
Senior help inside your team, toward results agreed up front.
The same senior leader you meet in the first conversation works inside your team to collaborate, lead, and guide the work toward results agreed up front. Then comes a handoff, with training, coaching, and mentorship shaped to your people. When you need a leader, this can be a fractional executive seat.
- Hands-on delivery alongside your staff
- Fractional chief AI, product, operating, or executive officer when needed
- Handoff with coaching and mentorship
Investigative Advisory
Advice that starts with knowing your company deeply.
For boards and executive teams. Your business, data, systems, people, and market are studied first, then you get advice on AI strategy and the approach that fits: an independent view from someone who has built AI and run companies.
- Board and executive-team advisory
- Deep review before any recommendation
- Strategy, priorities, and approach
Training & coaching
A team that knows how to use AI well.
Consultative training designed around your goals, your tools, and the people in the room, from executives setting AI policy to the teams using it every day.
- Customized to your needs and your people
- Executives, managers, and front-line teams
- Coaching that continues after the sessions
Supporting evidence
The track record behind the work.
Turnarounds, integrations, and launches from executive, product, and consulting roles.
90%
Technical debt eliminated on an AI identity-verification platform (AuthenticID)
85%
Fewer production defects in five months (AuthenticID)
$15M
Annual recurring revenue retained (AuthenticID)
71%
Technical debt cut across Ford Motor Co.'s Europe, Middle East, and Africa and India product teams (via LiminalArc)
$14M
Net new recurring revenue after eight years without a launch (Henry Schein)
6.5 → 9.2
Customer satisfaction across three merged healthcare IT service providers in nine months (Sunset)
Full track record →
Every figure comes from a role held. No projections, no modeled ROI.
Supporting evidence
Qualified to build it, not just recommend it.
Many AI advisers are strategists who have never shipped, or engineers who have never owned a profit-and-loss statement (P&L). This work is led by someone who has done both.
Hands-on AI
- Autonomous agents: designed and coded an agent built to monitor, diagnose, and self-heal renewable energy assets
- Retrieval-augmented generation (RAG) over pgvector
- Task-level evaluation and A/B testing harness
- Human-in-the-loop review workflows
- Three-tier edge, cloud, and fallback inference architecture
- Evaluated NVIDIA Jetson AGX Orin and AMD edge hardware for on-device AI; planning a move to a self-hosted large language model (LLM)
- Product leadership for computer vision (IREX.AI) and AI identity verification (AuthenticID)
Delivered under
- System and Organization Controls 2 (SOC 2)
- Health Insurance Portability and Accountability Act (HIPAA)
- Payment Card Industry (PCI) standards
- General Data Protection Regulation (GDPR)
- Fair Credit Reporting Act (FCRA)
Industries
- Identity verification and fraud
- Enterprise security and the public sector
- Healthcare IT
- Real estate data
- Automotive
- Renewable energy
- Software as a service (SaaS)
Chief Product Officer Certification, MIT Sloan School of Management · B.S. Information Technology · SAFe Product Owner / Product Manager
Who leads the work
Thomas J. Hanks
Tom leads every engagement personally. He has spent 20+ years turning technology decisions into financial results: twelve years as founder-CEO of a software studio, former chief product officer of IREX.AI, and today founder and CEO of Paragon Energy AI, where he designed and coded the platform.
More about Tom →See where AI would pay off in your business.
A 30-minute call. You'll leave with a view of where to look first, and whether a project or a fractional seat fits better.