Flagship · Built In-House
Simul8. An AI simulation engine.
Simul8 builds a living model of an audience — up to one million AI agents with distinct beliefs, relationships, and behaviours — and shows how they respond to a campaign, a launch, or a crisis before a single pound is spent.
Simul8What it is
Simul8 is our own AI simulation engine — built end-to-end at Uppercut Labs to answer a question most organisations cannot currently answer: how will this audience actually respond?
Instead of relying on survey data, focus groups, or intuition, Simul8 builds a computational model of the audience from real source documents. Each agent in the model carries a distinct belief system, a relationship network, and a memory of prior information — and then the model is run forward to observe how opinion, behaviour, and sentiment evolve in response to a stimulus.
The result is a high-fidelity simulation of audience response that can be run, adjusted, and re-run before a campaign launches, a product ships, or a statement is issued.
Under the hood
Agent Architecture
Dual-Platform
Population Scale
Up to 1M agents
Memory Model
Sequential
Data Foundation
GraphRAG
What it can do
Simulation across the questions that matter most.
Campaign simulation
Model how a target audience responds to a campaign message, visual language, or positioning before creative production begins. Identify which segments respond, which resist, and why.
Launch modelling
Simulate how an audience receives a new product, pricing change, or market entry. Test assumptions against a model grounded in real data rather than intuition.
Crisis response prediction
Understand how different audience segments are likely to respond to an incident, announcement, or controversy — and which communication approach is most likely to contain or repair it.
Segment behaviour analysis
Break audiences into distinct agent populations with different belief systems, information environments, and relationship networks. See how opinion travels between segments over time.
GraphRAG knowledge layer
Agent beliefs and knowledge are grounded in a knowledge graph built from real source documents — not invented by a model. Outputs are traceable to real evidence.
Scale modelling
Run simulations at realistic population scale — up to one million agents — so results reflect statistical properties of real audiences, not the noise of small samples.
Why it exists
We built Simul8 to make a point.
AI Enhancement done properly is a different category to bolting a chatbot onto a page. The question it answers is specific, the data grounding is real, the evaluation is built in, and the system holds up at production scale. That is what this looks like.
Simul8 is available to a small number of partners on a retainer basis. But mostly, it is proof of what we can build for you.
What this means for your project
- Every AI capability we built into Simul8, we can engineer into your product
- The same GraphRAG architecture powers client knowledge systems and document intelligence
- The same evaluation discipline applies to every AI feature we ship
- The same production standards — monitoring, cost controls, fallback behaviour — are in every build
Ready to build something with real AI depth?
Tell us what you're working on. We'll show you where intelligence creates genuine leverage — and build it in properly.
Start a project