[ USE CASE LONGLIST ]
Every AI opportunity surfaced during workflow mapping captured in one place, from the obvious to the overlooked, before anything is filtered out.
< OPPORTUNITY SCORING / NEW ZEALAND >UNIT / CON-03NZ-AKLA LUCID MEDIA COMPANY
EVERY IDEA RANKED.ONLY THE BEST ONES BUILT.
Once your workflows are mapped, the opportunities are usually obvious, and there are usually more of them than you can build at once. Opportunity scoring is how we decide what gets built first: every candidate use case is scored against the same criteria, so the choice is a ranked list, not a guess or whoever shouts loudest in the meeting.
We score on return, feasibility and risk. Return is the hours or revenue a build genuinely recovers. Feasibility is how hard it is to build given your systems and data. Risk covers what happens if the model gets it wrong. The result is a shortlist you can defend, not a wish list of everything AI could theoretically do.
CAPABILITIES.
[ WHAT WE DELIVER ]
[ RETURN MODELLING ]
Each opportunity costed against the hours it saves or the revenue it protects, using your own numbers, not industry averages.
[ FEASIBILITY SCORING ]
A practical assessment of what it actually takes to build each opportunity: data quality, system access, integration complexity, and how mature the underlying AI capability is today.
[ RISK + REVERSIBILITY REVIEW ]
What happens if a given AI system gets something wrong, how visible that failure is, and how easily it can be caught and corrected before it does damage.
[ SEQUENCING LOGIC ]
Opportunities ordered so early, low-risk builds generate the case and sometimes the budget for the larger ones that follow.
[ SCORED SHORTLIST DELIVERY ]
A ranked list with the reasoning shown, not just a score, so you and your team can question and adjust the priority order before anything is built.
USE CASES.
[ WHERE IT PAYS FOR ITSELF ]
- USE/01
TOO MANY IDEAS, NO ORDER
Every department has an AI wish. Scoring turns a scattered list into a single ranked sequence everyone can align behind.
- USE/02
LIMITED BUDGET, ONE SHOT
You can only fund one build this quarter. Scoring identifies the option most likely to pay for the next one.
- USE/03
INTERNAL DISAGREEMENT
Different stakeholders back different projects for different reasons. A shared scoring model replaces opinion with a criteria everyone agreed to upfront.
- USE/04
AVOIDING A COSTLY MISTAKE
An idea sounds exciting but the risk score reveals the downside is too large for the upside on offer. Scoring catches that before money is spent.
CASE STUDIES.
[ LIVE SYSTEMS / REAL-WORLD APPLICATION ]
AUTOAPPRAISE
CONSUMER AI PLATFORM
Scored highly on return because it opened a new consumer revenue line, and on feasibility because structured vehicle data was already available. A live valuation platform for the New Zealand vehicle market where a driver enters their car's details and receives a structured AI-generated report on market position, price range and selling guidance, with the report engine, payment flow and hosting built end to end.
PIPELINE AGENT
CRM + FOLLOW-UP OPERATIONS
Scored as low risk because every action routes through human approval before anything is sent, which made it an easy first build. A chat-commanded agent, driven from Telegram, that keeps the CRM honest, cleans records, surfaces every lead due a follow-up, drafts the nudge for approval and flags dead opportunities before they rot the pipeline.
[ FREQUENTLY ASKED ]
Q/01HOW DO YOU ACTUALLY CALCULATE RETURN ON AN AI OPPORTUNITY?+
We work from real numbers wherever possible: hours currently spent on a task, the hourly cost of that time, or the revenue at risk if a process breaks. Where numbers are not available, we estimate conservatively and flag the assumption so you can challenge it.
Q/02WHAT STOPS YOU FROM JUST RECOMMENDING THE FLASHIEST AI IDEA?+
The scoring criteria are fixed before we see the candidate list, and every score is shown with its reasoning. A flashy idea with poor feasibility or high risk scores lower, on paper, than a boring one that clearly pays.
Q/03CAN OPPORTUNITY SCORING BE DONE WITHOUT A FULL WORKFLOW MAPPING ENGAGEMENT?+
It works best on top of a proper map, because feasibility and return depend on how the process actually runs. For a business with a narrow, well understood problem, we can sometimes score directly, but we will tell you if mapping first is worth the extra time.
Q/04WHAT HAPPENS TO THE IDEAS THAT SCORE LOW?+
Nothing is thrown away. Low-scoring opportunities go into the roadmap as later-stage candidates, or get parked if the underlying AI capability or your own data is not ready yet. The scored list is kept and can be revisited.
[ START HERE ]
STOP GUESSING WHAT TO BUILD FIRST.
GET IT RANKED.
30 minutes, no pitch deck, no obligation. Tell us what's eating your team's time and we'll tell you straight whether AI is the answer, and roughly what it would take.
WHAT YOU GET
A straight answer on whether AI pays off in your business, and what it would take.
RESPONSE TIME
Within one working day