// about TuneView
Built to turn measured evidence into the next clear revision.
TuneView is a LambdaWorx LLC product founded by Ryan Lippmann in Orange County, California. It reviews an engine datalog, returns prioritized revision instructions, and uses the next log to judge what actually changed.
Origin
A real truck exposed the need for a repeatable loop.
Ryan began building TuneView while learning to self-tune his own 416ci Whipple-powered 2015 GMC Sierra. The practical need was not another generic score. It was a process that could connect a measured condition to a specific edit, then test that advice on the following log.
The published Sierra case study includes the uncomfortable outcomes too: one recommendation improved, two held, and two measured worse. That is the standard TuneView is built around: verdicts stay attached to the evidence.
Read the Sierra revision-loop case study →The operating principle
Evidence first. Revision second. Verification next.
01
Measure the condition
TuneView starts with the channels and operating range present in the uploaded log.
02
Explain the revision
The report ties prioritized P1–P4 instructions to the evidence that supports them.
03
Re-log and verify
The next round checks whether the prior recommendation improved, held, or made the result worse.
Founder
Ryan Lippmann
Outside TuneView, Ryan works in construction project management and project controls. That discipline asks the same core questions: What changed? What evidence supports the forecast? What decision comes next? TuneView applies that measured, traceable approach to the engine-tuning revision cycle.
His published healthcare construction case study explains a source-backed framework for baselines, phasing, cost, risk, and owner decisions.
TuneView does not hide a disappointing result. It records it, learns from it, and makes the next revision more defensible.
Explore Full Tune →