Simulate the consequences of your next product decision

Know which users struggle, who churns, and where trust breaks before you ship. Semilattice runs AI agents through your live product, each carrying the attitudes and anxieties of a real user segment.

How it works

A+4%

B+1%

C-3%

Building is faster than ever. Deciding hasn’t kept up.

AI has compressed development from months to days. But every feature you ship still competes for the same finite pool of real users. The bottleneck isn’t building. It’s knowing what to build.

THE SPEED GAP

Development outruns insight

You can ship a feature in a day. Understanding whether it was the right feature still takes weeks. Your build cycle is 100x faster, but your learning cycle hasn’t changed.

THE COLD START

New territory, no signal

You’re designing for a segment you haven’t served yet. Their attitudes, anxieties, likely reactions. You need signal before you’ve built anything. You can’t A/B test a product that doesn’t exist.

THE COST

Evidence that arrives too late

The only way to know if a decision was right is to ship it and watch. By the time you’ve learned, you’ve already spent the engineering time. The lesson was right. The timing made it useless.

See where they struggle before you ship

AI agents use your product the way real users would. You see every click, every hesitation, every drop-off across every segment you care about.

SIM-328Female, 46 · Spender

Clicked "Personal"

Clicked "Earn cashback"

Clicked "See offers"

“I wanted to compare current accounts first. The cashback offer caught my eye — that’s what got me to sign up.”

Pages 3

Converted

From decision to evidence in minutes

Every simulation produces a structured report: predicted outcomes by segment, key tensions, and the tradeoffs that matter. The evidence you need for your next decision meeting.

Q2. What would you expect in a premium banking subscription?

Higher interest on savings

71%

Advanced budgeting tools

58%

Fee-free international

54%

Priority support

43%

Cashback

39%

Insurance products

22%

Q3. What is the maximum you would pay per month for premium banking?

Nothing (free only)

46%

Under £3

22%

£3-5

18%

£5-10

10%

£10+

Demographic breakdown

Willingness to pay by age

25-3034%

31-3527%

36-4018%

41-4514%

Overall sentiment

Positive23%

Neutral31%

Negative46%

Switching intent

Positive12%

Neutral19%

Negative69%

Recommendations

Position any paid tier as "premium extras" rather than replacing free features — loss aversion is the biggest barrier.

Lead with budgeting and savings tools as the core value proposition for early adopters.

Consider a freemium model: free core banking, paid feature bundles under the psychological threshold.

Methodology

Simulated survey of 2,400 digital twins calibrated to UK adult population (25-45). Model accuracy validated at 87% against ONS financial behaviour data. Confidence intervals: +/- 3.2% at 95% CI.

Generated by Semilattice

SimulationComplete

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Would UK adults switch to a subscription model for their primary banking app?

UK Adults 25-45|2,400 digital twins|Model accuracy: 87%|4 March 2026

Predicted outcome

The majority of UK adults aged 25-45 would not switch to a subscription banking model. Only 23% express willingness, primarily among higher earners who already pay for premium accounts. The strongest resistance comes from the 35-45 bracket who view free banking as a fundamental expectation.

Key insights

Price sensitivity is the dominant factor — 68% cite "I already pay enough in fees" as their primary objection.

Users who value budgeting tools are 3.2x more likely to consider paying, suggesting feature bundling as a viable path.

Trust in traditional banks is low; 41% believe subscription would mean "paying for what should be free".

Early adopters cluster around 25-30, digitally native, already using 2+ fintech apps alongside their main bank.

Question simulations

Q1. How likely are you to pay a monthly fee for your primary banking app?

Very unlikely

42%

Unlikely

26%

Neutral

Likely

16%

Very likely

Every simulated user is grounded in real data

Population models built from real attitudinal data. Each simulated user carries coherent attitudes, preferences, and decision-making patterns that match your actual user segments.

AudienceTested

+ New Simulation

UK Adults 2026 — Consumer Finance

UK Adults·52 questions·Created 18 Feb 2026

90%

Avg Accuracy (1-MAE)

15%

Avg Squared Error (RMSE)

0.0618

Avg Norm Info Loss (NKLD)

Seed data 52

Testing

#QuestionDistribution

1What is your gender?

2Which age band are you in?

3Which region of the UK do you live in?

4What best describes your work situation?

5Do you own your home, rent, or something else?

6Which best describes your household?

7What is your total annual household income?

8What was the main reason you last took out a credit card?

9What is your primary way of paying for everyday purchases?

10Have you sent money to someone in another country?

11Have you used a 'Buy Now, Pay Later' service?

12Which best describes your UK credit history?

Respondent clusters

Audiences16

+ New Model

UK Consumer Finance

16 segment models

All Adults

UK adults, nationally representative

89.6%

52 questionsNKLD 0.062

Established Mid-Career

Ages 30-49, no dependents

90.1%

52 questionsNKLD 0.062

Growing Families

Couples & single parents w/ children

89.8%

52 questionsNKLD 0.057

Financially Stable

No missed payments, 1-6mo cover

89.6%

52 questionsNKLD 0.060

Getting Out of Debt

Prioritising debt reduction

89.5%

52 questionsNKLD 0.058

Building a Safety Net

Prioritising emergency savings

89.3%

52 questionsNKLD 0.060

Growing Wealth

Prioritising investing

89.1%

52 questionsNKLD 0.061

Affluent

Income £60k+, savings £25k+

89.1%

52 questionsNKLD 0.067

Saving for a Purchase

Saving for house, car, holiday

89.1%

52 questionsNKLD 0.067

Financially Comfortable

6mo+ cover, active investments

88.8%

52 questionsNKLD 0.065

Just About Managing

No missed payments, low resilience

88.7%

52 questionsNKLD 0.070

In Financial Difficulty

Missed payments or zero resilience

88.6%

52 questionsNKLD 0.064

Early Career

Ages 18-29, no dependents

88.2%

52 questionsNKLD 0.067

Pre-Retirement

Ages 50-64, employed

88.1%

52 questionsNKLD 0.071

Protecting Assets

Asset protection & retirement

87.9%

52 questionsNKLD 0.072

Retired

Retired adults

86.8%

52 questionsNKLD 0.080

How it works

Describe your decision

Describe what you’re considering. A pricing change, a new flow, a feature gate. Choose which user segments to simulate.

Simulate

AI agents use your product the way your users would. Watch them react across every segment you care about.

See the results

Predicted outcomes by segment, key tensions, and the tradeoffs that matter. Evidence for your next decision meeting, not your next quarterly review.

See what happens before you ship

Every product decision is a bet on how people will react. Until now, you couldn’t check. Semilattice simulates how your users respond to changes before you ship them.

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