Turn scattered science into executable causal worlds
CausalForge transforms fragmented research papers and hypotheses into manipulable causal world models. Simulate interventions, expose contradictions, and discover the next decisive experiment.
How it works
Four steps from literature to discovery
Ingest Science
Feed research papers, abstracts, or structured notes into CausalForge. Extract structured claims, variables, and mechanisms.
Build Causal World
Transform extracted claims into an explicit causal graph with variables, edges, signs, uncertainty scores, and evidence counts.
Simulate Interventions
Choose an intervention and observe predicted downstream effects. See how confidence propagates through the causal structure.
Discover Next Experiment
Identify the highest-information-gain experiment. Know exactly what to measure next and why it matters.
Technical Depth
Not a chatbot. Not a search engine.
Scientific infrastructure for the age of AI-native research
Explicit Causal Graphs
Real causal structure, not hidden in a prompt. Variables, edges, signs, strength, and uncertainty are all inspectable.
Contradiction Detection
Automatically identifies conflicting claims, incompatible mechanisms, and evidence gaps across literature.
Counterfactual Simulation
Choose interventions and observe modeled downstream effects with confidence propagation and sensitivity analysis.
Experiment Ranking
Information-gain scoring to identify which experiment would most reduce uncertainty and change the field.
Evidence Inspector
Every edge and recommendation traces back to source documents, excerpts, and confidence levels.
Grounded Assistant
Ask CausalForge anything about the model. Answers come only from the graph, claims, and simulations — never hallucinated.
The Vision
Humanity stores science in documents. Documents are readable but not executable. This slows discovery and hides contradictions.
The future is not just AI answering questions about papers. The future is AI turning science into manipulable causal worlds. CausalForge is a first prototype of that future.
Enter the Causal World