Runnax facts

Last updated 2026-10-14 · every number here links to how it was measured
What it is
An AI photometric engine for outdoor lighting. For a parking lot it searches pole layouts against your illuminance targets and returns one that passes, or says why none does.
Company
Runnax, founded by Kyan Gao. First customer: Auvolar, a commercial LED manufacturer in California. Contact: kyan@runnax.com.
Stage
Early access. Runs are done on request and returned within one business day. A REST API, an MCP server and a CLI ship together with the API release; they are not public yet.
Calculation method
Point method, the same formula as IES RP-8: E = I(γ, C) · cos θ / d² · LLF, summed over every luminaire head, with intensities interpolated from the IES file. Direct light only: no inter-reflection, obstructions or shadowing.

Parking lots · available

Roadways · calculation

Accuracy

ComparisonResult
Parking lot, 271 points, vs an AGi32 direct-light run of the same lotMin, average and max within 0.5 %
Same lot, vs the AGi32 design delivered to the customerEngine average 1.7 % higher
Roadway area averages, 9 zones from real projects, vs AGi32 and DIALuxWithin 3.6 %
Roadway point values vs AGi32Not validated (median about 4 %, worst points over 30 %)

Method and every sample: Verification.

What a run is not

Your files

Files are used for your run, deleted after 30 days, and never used for training.