back_office_ops · saas · workflow
Grab Integrity Analytics team automates metric reports and fraud investigations with RAG-powered LLMs
Data Analysts at Grab's Integrity Analytics team faced growing stakeholder demand for data queries, with manual repetitive SQL query writing making analytics slow and inefficient.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits prompt or query
A user submits a prompt or query to initiate a data analysis or fraud investigation.
Tools used
SpellVaultData-ArksRAGA* bot
Outcome
Automated report generation saves an estimated 3-4 hours per report, and fraud investigations that were previously time-consuming can now be completed in a matter of minutes via the A* bot.
Results
Time saved3-4 hours per report
Cost replacedreduced to a matter of minutes
Grounding & classification
Source type: technical build writeup
24 fields verified against source quotes.
ai agentragsummarizationknowledge basemetric backednamed customerproduction runtime claimedtools describedworkflow describedfinancial servicessoftwarecycle time reductionemployee productivitytime savedtechnical build writeupback office opscompliance monitoringrag answering