Case Study
Map the work. Then automate it.
14,000+ hours/year
of automation-ready effort, measured directly across two core workflows, before any AI was deployed.
401(k), pensions & recordkeeping
Retirement plans managed
Employer clients nationwide
Professionals nationwide
The efficiency hiding in plain sight
In a structured pilot across two core workflows, Skan measured how work actually executes, surfacing a clear, automation-ready opportunity before any AI was deployed.
9,000 hours
5,000+ hours
Core workflows mapped end-to-end, in real time, across every role.
Observation per workflow, drawn from live system activity, with no surveys.
Of observed effort concentrated in a small set of repetitive, automatable tasks.
A retirement-services leader,
scaling through acquisition
- Company
Definiti, one of the largest dedicated retirement-services TPAs in the US.
- Scale
15,000+ retirement plans · 8,000+ employer clients · 350+ professionals nationwide.
- Services
401(k) administration, actuarial consulting, pension outsourcing and recordkeeping.
- Ownership
Backed by Lovell Minnick, a specialist financial-services private equity firm.
- Ambition
Unify operations after rapid M&A growth and position the business for an AI-enabled next phase.
The challenge. Retirement services is a business built on precision — every plan must be compliant, every record accurate, every deadline met. But behind the scenes, operational complexity was outpacing visibility. As Definiti expanded through acquisitions, it inherited a patchwork of systems — Pension Pro, excel, email and external portals all running in parallel — with no single source of truth for how complex, long-running work actually gets done.
The fragmentation was invisible from the top but felt daily on the ground. New business implementation and the client servicing pods were both heavily manual and difficult to baseline. Leadership knew inefficiency existed — they couldn't see exactly where it lived, how much it cost, or what to fix first.
"The biggest thing CIOs and CTOs want right now is an understanding of what the value add actually is. We were being asked to turn on AI, but first we needed to understand what we were automating."
Jennifer Redden — Head of Technology, Definiti
Measure how the work really runs
In October 2025, Definiti engaged Skan through a structured pilot focused on its two most labor-intensive workflows.
New business implementation
Pods
Every step, across every role and system, observed live as it happened.
Where time actually goes, by role, exposing the true cost of each activity.
Which tasks repeat most often, pinpointing the highest-volume, highest-effort work.
A ranked map of where automation or redesign would generate the highest return.
A small set of tasks, driving most of the work
Across both workflows the data surfaced a consistent pattern: a handful of high-frequency, high-time activities drove the majority of operational effort — and almost all were candidates for automation or redesign.
New business implementation, client onboarding, Pension Pro setup and recordkeeper coordination, mapped across every role. ~278 hours/month observed today → 800+ hours/month at full deployment.
The full case lifecycle: email and phone intake, case handling, communication and follow-up. ~387 hours measured in a 3-week window.
95%
From a map of inefficiency to an automation roadmap
The readout quantified the problem and became the structured plan for what to automate, in what order, and how to measure the return. With the readouts complete, Definiti converted from pilot to a full production subscription in January 2026 and moved quickly to prioritize automation.
Pilot engaged
Two core workflows scoped for observation.
Work mapped
Real-time capture across roles, systems & steps.
Full production
Converted to subscription; NBI prioritized first.
First agents live
Automation deployed against the highest-return tasks.
"Before, it was turn on AI and hope. Now we know exactly which processes to automate, what the expected time savings are, and how to measure whether we got there. That changes everything about how we deploy."
Jennifer Redden — Head of Technology, Definiti
A foundation for agentic transformation
As agents move into production and adoption matures through Q3 2026, Definiti expects to confirm and build on its projected efficiency gains.
Scaling the operational understanding
Grounding AI agents
See it in action
Talk to our team about your operations.