back_office_ops · saas · workflow
Cato Networks uses Amazon Bedrock to transform free text search into structured GraphQL queries
Filtering events on Cato's SASE management console required manually adding filters, which was time-consuming and demanded in-depth familiarity with the product glossary—creating a steep barrier for new users.
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 enters free text query
A user switches to free text query mode on the Events page instead of manually adding filters.
Tools used
Amazon Bedrockanthropic.claude-3-5-sonnet-20241022-v2:0GraphQL
Outcome
The free text search feature received positive customer feedback, with query time reduced from minutes of manual filtering to near-instant results; account admins reported near-zero time to value with a minimal learning curve, and non-native English speakers benefited from native multi-language support.
Results
Time savedsignificant reduction in query time—cut down from minutes of manual filtering to near-instant results
Volumebelow 0.05
Grounding & classification
Source type: technical build writeup
18 fields verified against source quotes, 2 dropped as unverifiable.
data extractionknowledge basebuilder submittedfailure mode describedmetric backednamed customerproduction runtime claimedtools describedsoftwarecycle time reductionemployee productivitytechnical build writeupback office opsextract classify route