01ASSESS
Read the log in context.
The assessment ties a finding to the channel, operating range, and conditions that produced it.
// evidence to revision
TuneView
Log evidence. Tune direction.Your log tells you what to fix. TuneView tells you where.
Start with an initial assessment. Move into P1-P4 prioritized tune revisions. Re-log and let the next drive verify what changed.
P1 HP TUNERS REVISIONVVE / 2,200 RPM
VCM Editor > Engine > Airflow > VVE. At MAP-Baro 0.70, apply +10.9%, calculate coefficients, then save a new calibration.
* Example only. Your revision instructions are based on your log.
START YOUR FIRST CASE
FIRSTCASE unlocks your first full assessment and revision plan.
TuneView assessment
Revision evidence excerpt
OPENVCM Editor > Engine > Airflow > Virtual Volumetric Efficiency
LOCATE2,200 RPM / MAP-Baro 0.70
CHANGEApply +10.9% to the measured cell
P1 HP Tuners revision
Make the measured VVE change, then calculate and save the file.
Smooth the adjacent rows and columns, select Calculate Coefficients, then Save As a new calibration before flashing. TuneView gives you the navigation path, exact cell, and supported change; you enter it in HP Tuners.
* Example only. Your report identifies the table path, cells, and values supported by your own log.
// the revision loop
Assessment, revision, proof.
TuneView is built around the work between one log and the next.
02REVISE
Turn findings into P1-P4 edits.
Prioritized tune revisions identify the table, cells, and supported next change without asking you to guess the sequence.
03VERIFY
Let the next log judge the change.
Re-upload after the edit to see what improved, held, or regressed before deciding on the next pass.
// diagnostic coverage
What the review checks before you make the next edit.
The result is not one generic score. It is a set of evidence-backed findings organized around the systems active in your log.
knock // spark
Knock activity, spark behavior, and the operating range where the event appears.
airflow // MAF and VE
Airflow-model agreement and the measured windows that need calibration attention.
fuel // pressure
Fueling behavior, pressure tracking, and the data needed to separate a limit from a fault.
torque // shifts
Torque behavior, throttle response, and transmission patterns that affect the drive.
thermal // IAT
Heat soak, intake-air temperature, and repeatability across the logged conditions.
startup // drivability
Idle, startup, cruise, and the low-load behavior that a wide-open pull does not show.
Additional review systems
/fueling // lambda
/virtual VE model
/torque model
/transmission shift behavior
/torque-converter clutch
/sensor health
/spark control
/throttle // driver demand
/startup behavior
/log quality // coverage
Each system is evaluated when the uploaded log includes the channels and operating coverage needed to support a finding.
// evidence, not guesswork
Every revision should have a reason you can inspect.
TuneView keeps the recommendation connected to the observed channel, logged operating range, and result on the next upload. That gives you a usable calibration record instead of a disposable verdict.
We have amassed more than 16,000 lines of calibration data from public sources to back the revisions we make, and that database grows every day.
Current comparison set
PUBLISHED FLOOR16,360
calibration entries
877
categories
287
engine families
Browse the public calibration knowledge base behind the comparison set.
BROWSE THE KNOWLEDGE BASE// measured results
See what the next log says.
TuneView tracks case results round over round and publishes the outcome ledger: improved, no change, and worse. The system trends and sample sizes are available to inspect instead of being hidden behind a summary claim.
VIEW MEASURED RESULTSRound-over-round verdict ledger
PUBLIC VIEW
IMPROVED
Measured result moved in the intended direction.
NO CHANGE
The follow-up log did not clear the measured threshold.
WORSE
The result regressed and needs a different next pass.
The parser is the ruler
TuneView's in-house parser applies the same fixed thresholds to every matched round. A general-purpose AI model does not decide whether a customer result improved, held, or got worse.
// where AI fits
AI helps explain. The parser decides.
TuneView is deliberately not a black-box AI verdict. The in-house parser is the decision layer: it ties every finding to the uploaded log, the measured operating range, and the same fixed rules used to check the next round.
the ruler // in-house parser
The parser resolves supported channels, locates the relevant operating range, applies fixed rules, and produces the evidence used for P1-P4 revisions and next-log verdicts.
AI // bounded support
When used, AI is limited to the supplied intake and parser-owned evidence. It can organize context, surface information gaps, and explain the work in direct language.
hard limits // no AI authority
AI does not grade a log, set an HP Tuners value, change a threshold, invent platform behavior, or decide improved, no change, or worse. A new log is the proof.
The standard is simple: evidence first, a specific revision second, and the next log as the verdict. AI cannot replace that loop.
// start the loop
Start with the log you already have.
Your first full case establishes the assessment, the P1-P4 revision plan, and the baseline for the next-log verdict.
FIRSTCASE covers your first full case. A one-time Full Tune covers the whole revision cycle when you need to keep iterating.
// published case study
The 416 Whipple Sierra, verdicts included.
The founder's 416ci Whipple Sierra ran through two real TuneView rounds. One recommendation improved, two held flat, and two got worse. The measured verdicts are part of the story, not hidden behind the win.
See the baseline finding, the applied VVE changes, and what the follow-up log revealed next.
READ THE SIERRA CASE STUDY