Normalized claim
Time: 3 x increase
Query performance became 3x faster.
180 Seguros – Conversational generative AI knowledge base for insurance product professionals (Vertex AI Search)
Use case typeKnowledge managementUpdated Jun 13, 2026
180 Seguros is a São Paulo-based insurtech company that provides an end-to-end infrastructure for businesses to sell insurance policies across Brazil. The company migrated its analytics environment to Google BigQuery to improve data organization, make operational metrics more frequently updated, and reduce manual effort for data environment maintenance. It also developed an experimental conversational knowledge base for product professionals and developer teams in partner companies, integrating the solution into its own APIs and using Google Cloud generative AI resources including Vertex AI Search.
- Organization
- 180 Seguros
- Industry
- Insurance
- Location
- Brazil
- Published
- May 2026
Reported outcomes
3x
timeTime & speed
14 secondstime
Strategic outcomes
Speed & agilityImproved analytics query performanceSpeed & agilityAccelerated table extraction processEmployee experienceIncreased team autonomyNew product / capabilityBuilt conversational knowledge base
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Time: 14 seconds
A table extraction that previously took around five minutes now completes in 14 seconds.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- 180 Seguros
- Provider
- GCP
- Maturity
- Production
- Linked source
- Google Cloud Customer Stories
The company migrated its analytics environment to Google BigQuery to improve data organization, make operational metrics more frequently updated, and reduce manual effort for data environment maintenance
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 5
- 1Knowledge Management
- 2Conversational AI
- 3Search and Discovery
- The company needed better data organization and more frequent updates across a complex analytics environment.
- Teams wanted faster operational metrics tracking and less manual work maintaining the data environment.
- 180 Seguros also wanted to create an experimental conversational knowledge base to support insurance product workflows for product professionals and developers in partner companies.
- Migrated the analytics environment to BigQuery to speed up querying and simplify data management.
- Used Looker Embedded to make it easier to incorporate analytics visuals into internal interfaces.
- Built an experimental conversational knowledge base using Vertex AI Search and other Google Cloud generative AI resources.
- Integrated the knowledge base with in-house APIs and followed guidance from Google Cloud specialists to streamline AI adoption.
- Used Datastream to support the move of data into BigQuery.
- Query performance became 3x faster.
- A table extraction that previously took around five minutes now completes in 14 seconds.
- Teams gained greater autonomy and more time to focus on their own infrastructure.
- Datastream saved the equivalent of three or four full-time workers during data transfer.
- Looker Embedded reduced manual work for incorporating graphics into the company interfaces.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 23, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
Explore related AI use cases
Customer evidence
Provider evidence
AI patterns
Browse the catalog
Was this useful?
Community
Comments
Loading comments...