The four stops
01 · Diagnose
Find your best AI starting point.
First step: Diagnostic for one function, on your real roles
- A per role call: automate, augment, keep, or re-source
- A costed roadmap over the horizon you set
- A client ready report your board can read
02 · Adopt
Help your team use AI with confidence.
First step: Adoption kickoff: readiness check, foundations workshop, policy starter
- Learning tracks completed by team, verified by managers
- An acceptable use policy adapted with you
- One list of every AI workflow, its owner, and who approved it
03 · Build and run
Turn AI ideas into working workflows.
First step: One workflow, built and run for a quarter
- Working workflows with a named owner and a standard procedure
- Monitoring, drift checks, and updates
- One place to see what is live and what changed
04 · Prove
Measure what AI is improving.
First step: Quarterly value review
- A value report each quarter: forecast, measured, variance
- The plan revised as people and tools change
- A results record you can show a board
Why you can trust the numbers
Grounded
Built on peer-reviewed labor-economics and AI research, and U.S. government labor data.
Risk-adjusted
Every projection is discounted for real-world friction, not modeled at best-case.
Stress-tested
Recommendations are checked across conservative and aggressive AI scenarios. We only act on the calls that hold either way.
Traceable
Every figure ties back to its source, so the result stands up to scrutiny.
For reviewers: what we can prove, how we treat people, and how we handle data
What we can prove
Golden master
Every analysis stores its inputs unchanged at run time. Any result we have given you is reproducible on demand from the same inputs.
Orphan-number check
Every figure in the report traces to a logged calculation. If a number cannot be verified against the engine, it does not appear.
Your data kept apart by design
Isolation is enforced at the database layer. Your data is structurally inaccessible to other clients, not just kept apart by policy.
Unmeasured stays unmeasured
A move with no realized figure is stored as no figure. It renders as not measured, never as zero, and never enters a total.
Decisions carry their assumptions
Every recorded decision is stamped with a fingerprint of the assumptions it was made under. When those move, the decision reads as stale, not current.
Conflicts are kept, not resolved
Where stated and observed practice disagree, the register stores the disagreement. Nothing in the product resolves it automatically.
People and decisions
You decide, not the model
PractOps OS scores the work and shows its reasoning. Every decision about a person stays with a named human.
A path for every person
Each role that changes comes with a destination and a way to get there. Never a bare headcount cut.
Open to challenge
Any score can be questioned and reviewed. The result has to hold up when someone pushes back on it.
Blind to who people are
Scores are built from the work itself, not who does it. No demographic data is used, ever.
Security and data
Your data stays yours
Isolated to your organization, never sold, and never used to train models for anyone else.
Cleared sources only
Public baselines (BLS, O*NET) are included. Licensed feeds appear in client deliverables only under a signed agreement.
Built for review
Designed from the start for audit and bias review. SOC 2 is on the roadmap, and we will tell you plainly where we are on it.
We walk reviewers through the full methodology, the data sources, and how we validate, under NDA. Request the full methodology