Free tools

Tools for getting AI right, and proving it pays.

Three self-assessments that show where your AI program stands, then a calculator further down that builds an ROI case you can defend, one workflow at a time. No email wall. Nothing you enter leaves your browser.

Start here

AI maturity assessment →

An 18-point self-assessment against the four functions of the NIST AI RMF, mapped to ISO 42001. Score your maturity tier and see the gap by function in about five minutes. No email wall.
Go deeper

AI readiness assessment →

A scored self-assessment across all ten domains, from agent identity and human oversight to audit trail and regulatory alignment. Rate each control for a live maturity scorecard and a prioritized gap list. Nothing you enter leaves your browser.
Before an assessor

AI compliance readiness scorecard →

A red / amber / green readiness check against CMMC Level 2, NIST 800-171, SOC 2, ISO 27001, and/or ISO 42001, with the prioritized gap list to close before your assessor arrives.
Read the playbook

Governing AI in Regulated Workflows →

The ten-chapter playbook behind these tools: how to run AI inside CUI, CMMC, HIPAA, and financial-controls workflows without failing the audit. Every framework current and sourced, with where judgment beats the tool at each step.
Free diagnostic

The Proposal-to-Project Diagnostic →

Sixteen statements across qualification, reuse, drafting and review, the delivery handoff, and the assurance controls that keep it safe to run on client work. Scored profile and the gaps to close first, in about five minutes. Nothing you enter leaves your browser.
Start from the outcome

Business outcomes for professional-services firms →

Three measurable before-and-after changes, each with the workflow, controls, and metrics behind it. The outcome is the product; AI is the enabling technology; assurance is why it can be trusted with client work.
For consulting firms

Grow Delivery Capacity with Governed AI →

A field playbook for management consulting firms to scale expertise, improve delivery, and protect client trust: eleven chapters on the three workflows that decide consulting growth, with cited evidence, the governance patterns that make speed trustworthy, and a 90-day way in.
The industry library

Governed AI Operations for Professional Services →

Eight industry playbooks on one operating lens: consulting, IT consulting, CPA firms, law firms, architecture and engineering, executive search, creative agencies, and managed service providers. More leverage from every knowledge worker, with client trust protected by design.
Build the business case

You already know the vendor's ROI number won't survive your board.

Here is the one that will. At its heart this is a simple trade: you swap expensive human hours for cheaper compute, and free your people and budget to focus on the bottom line, or the mission. The example below runs three finance workflows on one set of licenses. Strip it to a single workflow and you will see why one rarely pays for the setup and seats on its own; the case builds as you add the work these licenses already cover. Walk in with something you can defend, not a hockey-stick.

Your numbers
Your AI program, shared by every workflow
Everyone you give a seat. You pay for these once, whether one workflow runs on them or ten. (e.g., the finance team you would license)
What an hour of this work costs you, blended across everyone who does it. Easiest to picture as a contractor's rate. For staff, use the average fully loaded cost, pay plus benefits and overhead. (e.g., a contracted bookkeeper's hourly rate)
Not who has a license, who really uses it weekly. Treat this as a planning judgment rather than a benchmark: weekly use usually runs well below the share of people who have access, so set it honestly and low. No external adoption figure is published here, because none in the evidence ledger meets the standard. (e.g., be honest about your team)
Most of the value shows up only after people pick it up, which is why day-one math misleads. (e.g., a couple of months, not the first week)
The costs, paid once for the program
What you pay per license, used or not. (e.g., your tool's price per person)
Metered token, message, or agent-run cost on top of the license. Many tools bundle this, so it may be $0; usage-billed and agent tools meter it. (e.g., often $0 on a flat-price license)
Getting it set up and people started: integration and sign-on, a security and privacy review, training, change management. Most of it hits early. (e.g., add up the one-time costs)
Your workflows

These share one set of licenses. Remove any to see the effect, or add your own; the setup and seats are paid once. The three below are illustrative placeholders, not benchmarks and not evidence of what AI saves: time your own workflows both ways and replace every number before reading anything into the result.

What you walk in with Across your workflows, year one
Time savedhours of human effort freed
0 hrs
Labor it replaceswhat that work costs you today
$0
Compute to replace itlicenses, usage, and setup
$0
Net saving, year one
$0
range, low to high
Where the money lands, month by month Cumulative net by month

Modeled your ROI? The Expert Readiness Assessment validates these results against evidence and turns them into a roadmap you can defend.

Book a conversation →
How to defend each number

    This is the upside before the cost of governing and securing the tool, and these are planning estimates, not a measurement. Every input is yours to change.