Theo Conjecture

Automated mathematical conjecturing

Explore the underlying structure of data to generate plausible relationships for further investigation.

A guided path from “here is my dataset” to “here is a statement worth investigating.”

Automated conjecturing

How it Works

Start with your research domain

Work within established mathematical fields or upload your own structured datasets to explore relationships across known objects and properties.

Define the conjecturing universe

Select the invariants, properties, and targets you want to investigate, guiding the search toward questions relevant to your research.

Explore conjectures with context

Review candidate conjectures alongside their supporting evidence, definitions, and assumptions to evaluate which statements are worth pursuing further.

The Output

Candidate conjectures

Every result represents a relationship that survived the selected data and search conditions, providing structured starting points for further investigation.

Inspectable evidence

Inspect the supporting examples, assumptions, hypotheses, and metadata associated with each conjecture to understand why it was surfaced.

Counterexamples surfaced

As new examples are added, identify outdated results, potential violations, and conjectures that may require refinement.

The best research tools are shaped by the people who use them.

More on Conjecturing

Conjecturing

Automated conjecturing: How machines are exploring mathematical structure

Before a theorem can be proved, someone has to decide what is worth proving. For decades, the formation of a conjecture remained largely outside the reach of machines. In Automated Conjecturing with TxGraffiti, Randy Davila explores how that boundary has shifted.