01
Role-specific tooling
Tools matched to the leadership, operations, finance, and risk roles that actually touch the workflow. No blanket-license rollout that leaves most seats unused.
New, with Accorian: a real-time AI governance framework for control drift in enterprise AI.Read the framework
Service
AI Fluency
Make the workforce fluent where the work changed: role-specific tooling, workflow training, pattern libraries, and adoption telemetry, with a fluency score every manager can read. Fluency is the measurable capability of an employee to do their actual job better with AI, not sessions completed, seats activated, or prompts written.
Spectrum3
Trust layerbuilt-in
Ownersnamed
Measured in production, not just shipped.
Every claim in the report traces back to source evidence, ownership, and the workflow decision it supports.
Valuefund next
Riskcontain now
Fluencytrain where work changed
What you get
Tooling, training, and telemetry make it stick.
Training on its own decays the week after it ends. Fluency lasts because three workstreams run together, and the evidence layer is built in rather than bought separately.
02
Hands-on training and pattern libraries
Workflow patterns the team can repeat, manager enablement, and refreshes as the tooling changes underneath them. Practice on the real work, not generic prompt drills.
03
Adoption telemetry and fluency scoring
Per-role and per-manager dashboards that show who is getting value from AI and who is stuck, so enablement goes where it moves the work instead of across the org at a flat rate.
04
Continuous, framework-agnostic evidence
Behavior, policy, drift, and proof feed the same trace pipeline the rest of the work runs on. Evals and governance are built into the build, not a separate purchase.
The curve
Five stages from awareness to compounding.
Workforce fluency is a curve, not an event. Each stage has its own bottleneck, its own intervention, and its own telemetry proof, so enablement lands where the curve actually bends.
Awareness
shared map of approved toolsassigned populations
Activation
per-role activation rateseats convert to first real use
Workflow integration
depth of useworkflow coverage
Quality lift
manager-rated quality, role by role
Compounding
cross-team reuse of role librariescurve bends without new cost
Where it shows up
Where fluency changes the day's work.
Fluency is owned at the role, not the company. Each of these workflows gets its own tooling, its own pattern library, and its own scoring rubric, fed by the same assessment.
01
Deal and investment-committee teams
Portfolio-wide analysis, deal-memo drafting, and board-ready summaries. Scored on time-to-decision and the quality of the analysis, not the count of seats activated.
02
FP&A and the financial close
Close, forecasting, and reporting patterns paired with manager-validated quality checks. Scored on cycle time and whether the output stands up when audit pulls it.
03
Insurance claims and underwriting
Claims triage and underwriting patterns with the review path built in, so the workflow moves faster without giving up the human judgment call on the exceptions.
04
Operations and IT rollout
Tooling rationalization, role-mapped license allocation, and manager rollout playbooks. Scored on per-role activation and how much of the real workflow AI actually covers.
05
Risk and compliance
The approved-tool footprint, sanctioned usage patterns, and telemetry that flags shadow use early. Scored on coverage of sanctioned use and time-to-detect drift.
06
Reporting and disclosure
Recurring reporting, disclosure drafting, and reconciliation work, with pattern libraries that keep the output consistent across a team and defensible when someone asks how it was made.
The evidence
Experienced AI users work differently.
Anthropic's March 2026 Economic Index found that longer-tenure AI users bring more complex work, collaborate more, and reach higher success rates than people who just received access. That is the public signal behind fluency scoring: measure the curve role by role, not the seat count.
New AI userLong-tenure user
WorkSimple, one-shot delegationComplex, collaborative work
PatternAsk once, accept the outputAsk, check, revise, validate inside real work
OutcomeLower conversation successHigher conversation success
What we fix
What makes fluency fail to stick.
Most enablement stalls in a handful of predictable places. Fluency work is built around fixing each one, with telemetry to show whether the fix held.
01
Training that does not stick
Seats activated and sessions completed measure attendance, not capability. Without role-specific tooling and telemetry underneath it, the training decays the week after it ends.
02
Review uncertainty stalls the work
People often have the tool and still will not ship, because they are unsure the output will survive review. A representative assessment showed roughly eleven roles stalled at exactly this point (illustrative of the assessment shape, not a single customer's measured result). Naming the review path is what lets the work move.
03
Blanket rollouts waste spend
A license for everyone spreads cost evenly and value unevenly. Matching tools to the roles that actually touch the workflow is what turns spend into capability.
04
No manager-visible signal
Without per-role and per-manager scoring, leaders cannot tell who is getting better at the job and who is stuck, so enablement ships at a flat rate instead of where it changes the work.
Common questions
Direct answers.
Training is one of three workstreams. The other two are role-specific tooling rolled out to the populations that need it most, and adoption telemetry with a fluency score every manager can read. Training without those two is what fails to stick.
Specialist AI builder, across the board
One builder, across the board.
We take your AI from strategy to outcome, with governance, audit, and evals built into every build. Start with a discovery call, or a quick audit.