Algorithmic redistricting for professionals.hobbyists.legislators.journalists.students.professors.everyone.

Tessera tries thousands of maps a second and keeps the ones that meet your custom goals, using state-of-the-art algorithms built for speed.

Download for Mac GitHub

You set the rules

Choose what matters, from compact districts and whole counties to competitive seats and partisan balance, and give each one a weight. Tessera searches for the map that does best on your terms.

Tessera redrawing Virginia toward seven goals at once, from compactness and competitiveness to minority opportunity and community dispersion

California, 52 to 0

With no limits, Tessera finds a California map where Democrats win all 52 seats. A plausible mode instead keeps minority opportunity districts, compact shapes and whole counties, aiming as close to the Voting Rights Act as it can.

A Democratic gerrymander of California winning all 52 seats

Better analysis tools

Seat distributions, district-by-district comparisons, swing tests and 3D views of the search, all updating live as the map changes. Built natively for the Mac, on a Rust engine with exact sampling on the GPU.

2.5×faster optimizer than the Python original, same machine
100×faster neutral maps than redist, the standard R package
Exactneutral sampling, not an approximation
The optimization landscape: a 3D surface of map scores with the search path settling into a valley

See how any map compares

Load an enacted map or draw your own, and compare it with thousands of maps drawn without looking at votes. You see right away whether it is typical or an outlier.

Neutral ridgelines: where each North Carolina district would fall across neutral maps, with the enacted map's districts marked