The AXIS Lab
Real AI tools designed, built, and tested for real organizational problems. Every tool in this lab was built on the CAL Framework and the AXIS System™ — and every build is documented so you can see the thinking behind it.
A product of Axis Advisory Co. · Jennifer Williams
I Built a Tool That Solves This
Each tool below started with a real organizational problem. Here’s what I built, why I built it, and how the CAL Framework shaped every decision.
Organizations make high-stakes talent decisions every day — who to promote, who to move, who to place on a performance plan — with no structured methodology and no defensible record of how they got there. This tool changes that. It walks leaders through a structured, multi-dimensional assessment of any candidate or employee, surfaces scoring across weighted criteria, and produces a calibration-ready output you can actually defend.
The TDE was built to close a real capability gap: leaders making consequential decisions without a shared framework for evaluating people or explaining their reasoning. The tool creates the calibration capability — structured criteria, visible weights, a common language — that most organizations are missing entirely.
Who decides — the tool or the leader — is answered explicitly. The TDE structures and surfaces the assessment; it never makes the call. Every weight is visible, every output is traceable, and every decision remains with the human. That’s not just good design. It’s the only design that holds up in a legal or HR review.
How you make talent decisions is a leadership act — not just an HR process. Psychological safety erodes when people believe decisions were political, arbitrary, or made without real evidence. Structured, explainable calibration is how leaders demonstrate that the process is fair, even when the outcome is hard.
Before an organization deploys AI, someone needs to ask: are we actually ready? Not technically — organizationally. Do leaders understand what’s coming? Does the workforce have the capability to absorb it? Is there a governance model in place? This scorecard surfaces the gaps in 10 minutes and tells you exactly where to focus before you commit.
One of five readiness dimensions is dedicated entirely to workforce capability — not just “can the technology run here?” but “do we have people who can operate in, evaluate, and give honest feedback on an AI-augmented environment?” Capability is a readiness prerequisite, not an afterthought to deployment.
Governance readiness is scored as its own dimension: who holds decision rights, what gets monitored, what can be explained, and how authority is designed before anything goes live. Organizations that skip this are the ones that end up with AI making consequential decisions that nobody can defend — to employees, to regulators, or in court.
Leadership alignment is scored as its own dimension because a technically capable organization with misaligned leaders will fail at adoption. The scorecard surfaces trust deficits, psychological safety risks, and communication gaps before they become post-deployment crises that are expensive and slow to reverse.
Employees make high-stakes benefits decisions once a year, under time pressure, with information designed by vendors — not by the people who have to live with the choices. This tool is being built to change that: a guided, plain-language navigator that helps employees understand their options, model tradeoffs, and make decisions they can actually explain and feel confident about.
Follow the Builds
What I’m building, what I’m learning, and what’s happening at the intersection of AI, workforce strategy, and the future of work. No hype. Just the signal.