March 2026
Audiences, redesigned. Product testing in alpha.
Complete redesign of the audience experience. Every audience now has a detail page with accuracy scores and accuracy badges so you can gauge reliability at a glance. Drill into individual questions to compare ground truth against predictions with paired bar charts. Search and filter across everything.Read more on the blog →Product testing (alpha) gives you simulated users that interact with live websites as specific user segments would. They navigate, convert, get confused, miss things.March 2026
New landing page, new colour language, in-app login
The entire public face of Semilattice has been rebuilt. New landing page with an interactive decision tree hero, animated product walkthroughs, and a colour system built around indigo, pink, and teal.Login and signup now happen inside the app.Design tokens throughout, responsive down to mobile, OpenGraph metadata updated across all routes.March 2026
91% accurate against the FCA Financial Lives Survey
We tested our UK Consumer Finance audience model against the FCA’s most comprehensive benchmark: 207 questions it had never seen, covering trust, financial literacy, product usage, and demographics. Overall accuracy: 91%.The interesting part is where it gets things wrong. The model knows the right answer to financial literacy questions, but real people often don’t. It predicts what people should think, not always what they do think. That gap is the research question.Read the full analysis →February 2026
Decision tool: from question to evidence in minutes
New guided flow for product decisions. Describe what you’re considering, choose an audience, and Semilattice designs the research, runs it against simulated audiences, and returns a report with key insights, survey results, and recommendations. Minutes, not weeks.Built for the moment someone asks on a Sunday whether you should move that feature behind the paywall.Read more →February 2026
16 segments of financial life
16 UK Consumer Finance audience models, from Growing Families to Just About Managing. Each segment built on real research data with distinct demographics, financial behaviours, and attitudes.Every product decision in consumer finance is a “what if,” and the people that matter to you aren’t one group. Now you can ask each segment separately.Explore the segments →November 2025
Semilattice MCP
Semilattice MCP lets AI assistants and agents predict how specific audiences answer questions. Connect your IDE, your agent framework, or any MCP-compatible tool.Four tools:list_population_models, create_prediction, get_prediction, wait_for_prediction. Your AI can ask your audience a question and wait for the answer programmatically.Connect yours →October 2025
Test batches: evaluate accuracy for your use case
New evaluation feature. Upload ground truth data for your specific domain and test how well a population model performs on the questions that matter to you, not just the seed data it was built on.Cross-validation tells you the model’s general accuracy. Test batches tell you whether it’s accurate for your problem.Learn how →September 2025
Batches, 3× faster predictions, simplified API
API v1.1.0 · SDK v0.6.0Batches
Group predictions with a name and description. Fetch all predictions in a batch with/predictions/batch/{batch_id}.Speed
Predictions now return in ~20 seconds, roughly 3x faster than before.New methods
GET /populations— list all available population modelsGET /predictions|tests/batch/{batch_id}— fetch batch details
Simplified naming
We renamed methods and fields to make the API easier to read. Old names still work but are marked deprecated.POST /answers→POST /predictionsPOST /answers/benchmark→POST /testssimulated_answer_percentages→predicted_answer_percentageskullback_leibler_divergence→information_loss
July 2025
The Semilattice API: user insights as infrastructure
API v1.1.0 · SDK v0.5.2V1 release. Predict user behaviour like you make database queries.- Create population models with custom seed data
- Test model accuracy with built-in cross-validation
- Test against external ground truth
- Predict new questions
November 2024
Humans + Time
Human systems are complex, emergent, unpredictable, and fundamentally resistant to the modelling techniques that work for physical and biological systems. The human element has held back modelling because we lacked both the data and the computational models to work with it.Large Language Models change this. They contain enough encoded human behaviour to simulate how specific groups of people would respond to questions they’ve never been asked. That’s the foundation Semilattice is built on.Read the full essay →October 2024