Ideate, incubate, pilot. Scale only what the evidence supports.
Where new ideas — AI in the customer path included — are incubated and piloted with real customers. Every cycle ends in a decision: scale, iterate, or stop.
Every cycle ends in a decision: scale, iterate, or stop.
Usually starts with
The Lab runs on its own cadence; governance attaches to any pilot.
Hands off as
Scale-or-stop evidence back to Strategy, proven concepts to the Studio.
01Which new ideas deserve a prototype at all?
02Does it work with real customers and live models before we commit the year?
03Is it governed and adopted enough to scale?
How it runs
The lab pipeline.
Four stages, a gate between each. Most ideas should stop — cheaply, and early.
Worth a prototype?Worth a pilot?Worth scaling?
“Which ideas deserve a prototype?”
Horizon scans, journey pain and competitive white space turned into framed bets, scored before anything is built.
What leavesOpportunity portfolio
GateWorth a prototype? Scale, iterate, or stop — decided on criteria agreed before the stage began.
Solutions behind it
“Does it work in front of real people?”
Concepts built as working prototypes — with live models where the idea depends on them — and tested against criteria set first.
What leavesWorking prototypes · test findings
GateWorth a pilot? Scale, iterate, or stop — decided on criteria agreed before the stage began.
Solutions behind it
“Does it hold up with real volume?”
A bounded pilot in production: real customers or agents, guardrails on, evaluation running from day one.
What leavesPilot results against the gate
GateWorth scaling? Scale, iterate, or stop — decided on criteria agreed before the stage began.
Solutions behind it
“Is it governed and adopted enough to grow?”
Responsible-use policy, red-team evidence and enablement in place, then handed to the Studio and back to Strategy.
What leavesScale-or-stop pack · responsible-use policy
Solutions behind it
Offerings, deliverables & outcomes
Five offerings. Every one named, measured, and owned.
Each offering is a real engagement: four named deliverables, the outcomes we
agree to be measured against, and the conditions that make it the right call.
Solution 20 · Core practice
CX Innovation Lab & Experience Prototyping
A cadence for testing experience ideas cheaply — concept to prototype to real customer feedback in weeks, so the big commitments rest on evidence.
Deliverables
Opportunity portfolioFramed bets scored on customer value, differentiation, and feasibility
Working prototypesClickable and, where it matters, live-model experiences customers can use
Customer test findingsWhat people did, not what they said they would do, against set criteria
Scale-or-stop packThe evidence, the recommendation, and what it costs to take it further
Outcomes it answers to
Every sprint ends with a decision, not with a request for another sprint
Concepts are tested with real users before any scale commitment
The stop rate is healthy — a lab that never kills anything is not testing anything
Use it when
Innovation currently means an annual offsite that produces slides
A large bet is about to be funded on conviction
Ideas die in year two of a program rather than in week three
Engaged asRepeated sprints, a decision each cycleCommercialFixed fee per cycleCadenceTwo-week sprintsIn the roomProduct, design, service, engineering
Interfaces that assemble themselves around the request — where the screen is composed at the moment of need rather than pre-built, and the design work moves from screens to rules.
Deliverables
Generative UI opportunity mapWhere composed interface earns its keep, and where it does not
Component & composition rulesThe kit, the slots, the constraints, and the refusals
Intent-to-interface patternsHow requests resolve into surfaces people can act on
Evaluation & guardrail setHow you test an interface that assembles itself
Outcomes it answers to
Composed surfaces stay inside the component kit and the brand rules
People can see why a surface was assembled and correct it
Evaluation covers the assembly rules, not just individual screens
Use it when
The product surface is expanding faster than screens can be designed
Users arrive with intent that no fixed navigation anticipates
An assistant is answering in text where it should be handing over a control
Engaged asRepeated cycles, one surface at a timeCommercialFixed fee per cycleCadenceTwo-week build cyclesIn the roomProduct, design, engineering, AI, risk
The design behind AI agents that face customers: what they resolve, when they hand off, how they sound, and how you know they are safe.
Deliverables
Intent & containment designWhich contacts AI resolves, which it never touches, and why
Orchestration blueprintHow the agent reaches your systems, and what happens when one is down
Escalation & tone playbookHandoff rules, context payload, and the brand’s voice under pressure
Evaluation & launch planTest sets, adversarial cases, gate criteria, and the rollout sequence
Outcomes it answers to
Containment measured as resolution, with repeat contact tracked alongside it
Escalations arrive with context in the agent’s hands, verified in QA
No launch without the agreed gate criteria met on the evaluation set
Use it when
An agent platform is bought and nobody has designed what it does
Containment is being measured as customers giving up
The handoff to a human loses everything the customer already said
Engaged asFixed scope, set by the intents in playCommercialOutcome-priced projectCadenceTwice-weekly build reviewsIn the roomService, digital, data, risk
The guardrails, evidence, and change work that decide whether an AI-led service model survives risk, legal, and the people running it.
Deliverables
Responsible-use policyWhat the AI may do, must not do, and who owns each boundary
Evaluation set & red-team reportThe cases it must pass, the ones it failed, and what changed
Human-in-the-loop designWhere a person reviews, approves, or overrides — and how fast
Enablement & adoption planRole changes, training, comms, and the adoption measures
Outcomes it answers to
Risk and legal sign the design without a late-stage rewrite
Every customer-facing path has a documented guardrail and owner
Adoption measured on the floor, not assumed from a training completion rate
Use it when
Approval is a wall at the end of the program rather than a step in it
Nobody can answer how a customer-facing decision was made
The floor has not been told what their role becomes
Engaged asAttached to the engagement it governsCommercialAttaches to any engagementCadenceRisk forum every 2 weeksIn the roomRisk, legal, compliance, service, HR
A proof of concept for digital forms transformation across customer onboarding.
What it settledPaper-to-digital proven before the platform spend was committed.
West Coast energy utility
A working customer experience proof of concept in place of a written proposal.
What it settledThe buyer judged a working concept, not a slide.
IT services firm
A digital innovation lab stood up with its operating model and intake.
What it settledA repeatable lab cadence with a funding route behind it.
Global pharmaceutical company
Design thinking workshops incubating patient and clinician concepts.
What it settledConcepts tested with stakeholders before any build decision.
Patterns from studio, lab and strategy work our founders have led across enterprise clients. Client names are withheld; outcomes are described as illustrative composites, never a named client’s result.
What customer experience are you trying to get right?
If your team is weighing where to invest in AI across the customer experience — or trying
to move from pilots to something that actually runs in the service floor — a short conversation is
usually the fastest way to find out whether we can help.
