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Snowflake Software / SaaS Cologne, Germany

Cleverbridge

Sales Automation

give customer-facing and analytics teams faster natural-language access to global commerce data so they can spot conversion and renewal opportunities without constant SQL help from engineers.

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13–21 Months saved developing agentic capabilities with Cortex AI
33% Faster time to insight

Reported impact

Business outcome

Cleverbridge achieved 13–21 Months saved developing agentic capabilities with Cortex AI and 33% Faster time to insight.

  • Productivity Improvement
  • Speed to Market

Solution

Cleverbridge uses Snowflake, Cortex AI, Cortex Analyst, and Cortex Search on Snowflake to give customer-facing and analytics teams faster natural-language access to global commerce data so they can spot conversion and renewal opportunities without constant SQL help from engineers. Payment, checkout, conversion, and renewal data are centralized in Snowflake so customer-success, revenue, and analytics teams can work from a faster, more reliable operating view. Cortex AI adds in-platform LLM and agentic capabilities for classification, summarization, retrieval, or natural-language analytics on top of the curated data foundation. Keeping ingestion, storage, transformation, and governed access on one platform reduces handoffs, simplifies operations, and makes it easier to reuse trusted data across analytics, reporting, and AI. Cleverbridge achieved 13–21 Months saved developing agentic capabilities with Cortex AI and 33% Faster time to insight.

Data flow

payment, checkout, conversion, and renewal data flow into Snowflake, Cortex AI, Cortex Analyst, and Cortex Search; curated data, reports, and model outputs are then served to customer-success, revenue, and analytics teams.

Solution architecture

4 components · 3 layers
  1. Compute
    • Cortex AI Provides in-platform AI functions used for summarization, classification, generation, or model-assisted analysis.
  2. Storage
    • Snowflake Provides the centralized data platform that stores governed datasets and serves analytics or AI workloads.
  3. Serving
    • Cortex Analyst Turns natural-language questions into governed analytics against Snowflake data.
    • Cortex Search Provides semantic or keyword retrieval over governed enterprise data for AI experiences.

Architecture clues

  • Cortex AI adds in-platform LLM and agentic capabilities for classification, summarization, retrieval, or natural-language analytics on top of the curated data foundation.
  • Cortex Analyst allows business teams to ask natural-language questions against governed semantic models instead of relying on hand-written SQL.
  • Cortex Search helps turn curated business content into searchable context for analysts and internal users.
  • Integrates with AWS as part of the broader delivery workflow.

Evidence from the source

13–21 Months saved developing agentic capabilities with Cortex AI
33% Faster time to insight
As an early adopter of Snowflake Cortex AI, Cleverbridge is accelerating internal decision-making, helping teams identify revenue opportunities faster and building a stronger foundation for agentic commerce
Cleverbridge achieved 13–21 Months saved developing agentic capabilities with Cortex AI and 33% Faster time to insight
For more than 20 years, Cleverbridge has helped software companies manage that complexity
Transparency Evidence & methodology 100/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Snowflake

    Cleverbridge customer story

    First-party
    https://www.snowflake.com/en/customers/all-customers/case-study/cleverbridge/
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • Sitemap last modified Aug 13, 2026 · Snowflake · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Aug 13, 2026 · Snowflake · Unknown Legacy extracted date without source-page confirmation.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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