01
Spend baseline
Pulls external service spend, tooling costs, and internal headcount into a single baseline so comparisons start from real numbers, not anecdotes.
ROI
A return-on-investment tool that quantifies what structured AI and process improvement is actually worth — translating in-house cycle times, external service spend, and avoided incidents into a defensible ROI number so leaders can justify investment and show where process change pays off.
A model for showing what a AI or process investment actually returns — baseline spend, cycle-time change, avoided cost, and the scenarios in between — in a form a finance team will accept.
It is deliberately conservative: assumptions are explicit and adjustable rather than buried.
01
Pulls external service spend, tooling costs, and internal headcount into a single baseline so comparisons start from real numbers, not anecdotes.
02
Measures how review, intake, or escalation workflows change time-to-resolution before and after a process or tool is introduced.
03
Estimates the value of incidents, regulatory exposure, and contract leakage avoided through earlier intervention — the ROI piece teams struggle most to quantify.
04
Compares unit costs and cycle times against peer benchmarks for similar matters so leaders can see where they over- or under-perform.
05
Lets teams model the budget impact of adding headcount, adopting a tool, or shifting a matter type in-house before committing to the change.
06
Rolls the analysis into a one-page ROI summary with assumptions visible, so finance and leadership can stress-test the numbers rather than trust a black box.
The inputs that make the output useful. Missing any of these usually shows up as a vague result.
Representative outputs, with illustrative examples. Every output is reviewed by a qualified professional before it is relied on.
Net benefit over a defined period with payback point.
Net $412k over 12 months; payback at month 5.
Conservative, expected, and optimistic cases side by side.
Conservative 1.6x, expected 3.1x, optimistic 4.4x return.
One page with the numbers, assumptions, and risks stated plainly.
Assumes 60% adoption; sensitivity: below 35% adoption returns turn negative.
We tailor each tool to your playbooks, thresholds, and review requirements before it goes live.