About Groow Labs
We build the evidence, not the opinion.
Groow Labs is an independent evaluation practice for LLMs and AI agents. We build private, contamination-free corpora and turn them into a decision an engineering leader can defend, which model, on which harness, for which job.
What we believe
“There is no best model. Only the best model for the job , on this harness, at this price, with this much confidence.”
Principles
How we think about the evidence. contamination. the numbers. independence. your decision.
Freshness beats forensics.
We don't claim to detect contamination, the detection literature is genuinely unreliable, and a sophisticated buyer knows it. We build corpora from your private artefacts, after the model's training cut-off. Data the model has never seen cannot have leaked.
Every number carries an interval.
A bare score can support the opposite decision. We report clustered confidence intervals, paired comparisons, and judges aligned to your human labels, the error bars other evals quietly omit.
We sell a decision, not a dashboard.
Nobody buys a thermometer because they enjoy numbers. Every engagement ends in two artefacts you can act on the same afternoon: a decision table and a cost-quality frontier.
Independence is the product.
A regulator asking for independent model validation cannot be satisfied by the team that built the model. That structural fact is the one thing your in-house team cannot do for itself, and the reason our report can go in a filing.
What we build
Three layers. One decision.
Token cost is a rounding error. Human judgment is everything, which is why our engineering goes into the corpus and the trust machinery, not a nicer dashboard.
Built from your reality, not our imagination.
Sampled from real production traces, stratified by difficulty and segment, PII handled at the boundary, frozen and versioned like code. The corpus is the labour-heavy part, which is exactly why it is defensible.
The part a weekend script cannot do.
Seeded deterministic selection so every model sits an identical exam. A raw-vote store so decisions are derived at read time. Fail-open judging, fail-closed rules, additive checkpointing. This is what we demo.
Thin code. Enormous credibility.
Clustered standard errors, paired difference analysis, power analysis, judge panels over single judges. The difference between a ranking a client believes and one they argue with.
How we engage
From first audit to a standing answer.
Diagnose
A contamination + harness audit of your existing eval, and a written verdict on what it can and can't tell you.
Build the corpus
We sample your production data, align the judge to your experts, and freeze a corpus the model has never seen.
Run the slate
Every model on your shortlist, on your real harness. Decision table and cost-quality frontier, deployed in your VPC.
Refresh
The slate churns every few months. We re-run the frozen corpus against each new model and send the delta.
Not sure which model to trust?
Bring us the model you're not sure about.
A 30-minute call, no pitch, we'll tell you whether your current eval can be trusted, and what a first frontier for your job would take to build.