Vantage RuntimeAI · Solutions
Internal engineering & analytics
Agents that do engineering, data, and analytics work inside your company — SQL, pipelines, ML readouts. Stress-test models on multi-turn fixture tasks (2–6 agent turns with scripted follow-ups); pick cost-effective tiers that pass deterministic rubrics on every PR.
11 live scenarios · daily cadence
Example scenarios
Published starting points below — gate the same scenario in CI/CD or via API; preview in the Simulator if useful. When none match your stack, build your own from repo fixtures (same rubrics).
Scenario
rai001 · Train/Serve Skew · Complex
training and production use different encoders for the same categorical feature — find the mismatch, explain the precision drop, and recommend a safe fix; 6 agent turns with scripted follow-ups.
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Scenario
rai002 · Feature Leakage Review · Complex
review churn-model features for label leakage relative to prediction time; 6 agent turns with scripted follow-ups.
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Scenario
rai003 · Lineage Impact Review · Complex
assess downstream mart impact of dropping legacy_account_id and migration plan; 6 agent turns with scripted follow-ups.
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Scenario
rai004 · Pipeline Incident Triage · Complex
triage failed dbt production run from log fixture — root cause + remediation; 6 agent turns with scripted follow-ups.
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Scenario
rai005 · Freshness SLA Breach · Moderate
explain freshness SLA miss on fct_orders — upstream blocker, blast radius, restore steps; 4 agent turns with scripted follow-ups.
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Scenario
rai006 · dbt Test Failure · Moderate
diagnose duplicate order_id unique test failure from dbt log and propose fix; 4 agent turns with scripted follow-ups.
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Scenario
rai007 · SQL Optimization · Moderate
model receives a slow Snowflake query fixture, then answers scripted engineering follow-ups over 4 agent turns with reviewer sign-off. Compare models on correctness, safety, and reasoning across the thread.
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Scenario
rai008 · Schema Drift Review · Moderate
model compares two schema catalog JSON snapshots and summarizes breaking changes; 4 agent turns with scripted follow-ups and reviewer sign-off.
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Scenario
rai009 · Null Rate Alert · Simple
triage overnight null-rate spike on shipping_country_code — cause, validation SQL, comms; 2 agent turns with scripted follow-ups.
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Scenario
rai010 · Partition Filter Fix · Simple
add missing event_date partition filter to stop full-table scan; 2 agent turns with scripted follow-ups and reviewer close.
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Scenario
rai011 · Experiment Readout · Simple
exec summary of A/B JSON with significance, caveats, and calibrated recommendation; 2 agent turns with scripted follow-ups.
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For search engines and LLMs
RuntimeAI analytical use case family.