LookML issue detection
Finds the problems in your codebase — unused explores, anti-patterns, fan-outs — and ranks them by severity.
P0 / P1 / P2
LKMind
by
RavenCoreX
AI for Looker & BigQuery · Built for data teams
Your LookML, reviewed before it costs you.
LKMind reads your LookML and your BigQuery spend, flags the issues that burn money (P0/P1/P2), and reviews your PRs automatically — so a bad explore never reaches production.
Phase 0 — read-only · GitHub webhooks · powered by Claude
IMG-22 · LKMind dashboard
Issues (P0/P1/P2) · Cost · PR review
Issues by severity, projected BigQuery cost, and an automated comment on the open PR.
The problem · 01
A single bad query can lead to a bill nobody saw coming.
Half your explores are never used. Your seniors are doing FinOps by hand instead of building. And the LookML that drives the cost gets reviewed — when someone has time. Nobody does.
How it works · 02
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It reads the code, the cost, and every PR.
BigQuery cost prediction
Sees the spend a query will cause before it runs against your warehouse — not after the invoice.
Automated PR review
Comments on every pull request via GitHub webhooks. Bad LookML gets caught in review, not in the bill.
Claude-powered explanations
Each issue comes with the why and the fix — in plain language, not just a rule code.
The result · 03
The waste was always there. Now you can see it.
30–60% BigQuery cost reduction — the method RavenCoreX runs by hand, automated.
RavenCoreX's data practice cuts BigQuery costs 30–60% by hand. LKMind is that method, automated and running on every PR.
Honest framing: 30–60% is what the RavenCoreX method detects — measured on our own data engagements. LKMind is in Phase 0 with an open waitlist, not a track record. We're putting the method in the product, not quoting results it hasn't earned yet.
The method, automated. Your exact range comes from your codebase.
Your stack · 04
Sits on top of Looker, BigQuery, and GitHub.
Read-only access to your LookML and warehouse. A GitHub webhook for PR review. No migration, no rip-and-replace — LKMind works with the stack you already have.
Looker / LookML
BigQuery
GitHub PRs
Read-only, zero commitment. LKMind never copies your data out, and never uses it to train models.
Join the waitlist · 05
Find the waste before the bill does.
Join the waitlist, or book a demo and we'll run it against your codebase. Read-only. Zero commitment.
LKMind by RavenCoreX