Labs · Concept lane in review

Research & benchmarks

Peer-review-style benchmark layouts, research directions, and evaluation notes for the LeanLogix concept surface. Public artifacts should only remain here when methods, provenance, and reproducibility materials are actually available.

3

Working notes in the concept lane

5

Checklist items before any benchmark headline

0

Audited production benchmarks claimed

Review

Status — methods and provenance required first

Research notes

Working notes, framed as questions to verify

Each note frames what a team should establish before a packaged-model or benchmark claim earns trust — not a finished result, but the discipline that has to come first.

May 2026 · LeanLogix working note

Small-model packaging questions for private AI teams

A planning note on what teams should verify before claiming a smaller packaged model is ready for a real environment: runtime targets, memory limits, latency method, quality rubric, and reviewer boundaries.

PackagingPrivate AIMethodology

May 2026 · LeanLogix working note

What a credible benchmark package would need to include

A checklist for evidence-first benchmark publication, including hardware profiles, source prompts, evaluation criteria, artifact provenance, and change-control notes so readers can understand what was actually tested.

BenchmarksEvidenceProvenance

April 2026 · LeanLogix working note

Deployment-pattern review for controlled environments

A directional note on when private or edge deployment patterns become useful, how approval boundaries affect runtime design, and what should stay conceptual until supporting artifacts exist.

DeploymentControlled environmentsReview

Benchmark format preview

Request a technical review before trusting a benchmark headline

LeanLogix should only publish benchmark-grade numbers when the supporting methodology and artifacts are available to review. Below is the evidence a credible benchmark package would have to carry.

Request a technical review to discuss methodology, target hardware, and what evidence would be required before publishing benchmark claims.

01Target hardware and runtime profile
02Latency method and test conditions
03Quality rubric and evaluation prompts
04Model, dataset, and artifact provenance
05Approval boundary for public publication