Vantage RuntimeAI · Solutions

Internal engineering & analytics

Agents that do engineering, data, and analytics work inside your company — SQL, pipelines, ML readouts. Pick cost-effective models that pass deterministic rubrics on every PR; avoid frontier-by-default spend.

11 live scenarios · daily cadence

Example check-rides

Published starting points below — open any in the Simulator, or run the same check-ride via API and CI/CD. When none match your stack, build your own from repo fixtures (same rubrics).

Check-ride

rai001 · Train/Serve Skew · Complex

training and production use different encoders for the same categorical feature (e.g. one-hot in training vs hash at inference) — find the mismatch, explain the precision drop, and recommend a safe fix.

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Check-ride

rai002 · Feature Leakage Review · Complex

review churn-model features for label leakage relative to prediction time.

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Check-ride

rai003 · Lineage Impact Review · Complex

assess downstream mart impact of dropping legacy_account_id and migration plan.

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Check-ride

rai004 · Pipeline Incident Triage · Complex

triage failed dbt production run from log fixture — root cause + remediation.

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Check-ride

rai005 · Freshness SLA Breach · Moderate

explain freshness SLA miss on fct_orders — upstream blocker, blast radius, restore steps.

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Check-ride

rai006 · dbt Test Failure · Moderate

diagnose duplicate order_id unique test failure from dbt log and propose fix.

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Check-ride

rai007 · SQL Optimization · Moderate

model receives a slow Snowflake query fixture and produces root cause + rewrite.

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Check-ride

rai008 · Schema Drift Review · Moderate

model compares two schema catalog JSON snapshots and summarizes breaking changes.

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Check-ride

rai009 · Null Rate Alert · Simple

triage overnight null-rate spike on shipping_country_code — cause, validation SQL, comms.

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Check-ride

rai010 · Partition Filter Fix · Simple

add missing event_date partition filter to stop full-table scan.

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Check-ride

rai011 · Experiment Readout · Simple

exec summary of A/B JSON with significance, caveats, and calibrated recommendation.

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For search engines and LLMs
RuntimeAI analytical use case family.