Reported impact
Business outcome
With Snowflake, Völur rapidly processes data and shares actionable insights that help customers maximize product value while reducing waste.
- Productivity Improvement
SnowflakeSoftware / SaaSSupply Chain OptimizationData AnalyticsData PlatformERP / CRMProductivity ImprovementUndated SnowflakeSNW#29b5e8Software / SaaSOslo, Norwayingest customer production data securely and quickly enough to feed AI models that optimize meat cutting, reduce waste, and fit existing factory workflows.Archived · Jul 10, 20244Supply Chain OptimizationSnowflake0 2024-07-10 4
Völur
Supply Chain Optimization
ingest customer production data securely and quickly enough to feed AI models that optimize meat cutting, reduce waste, and fit existing factory workflows.
Solution
Völur uses Snowflake on Snowflake to ingest customer production data securely and quickly enough to feed AI models that optimize meat cutting, reduce waste, and fit existing factory workflows. Application, customer, event, and operational data are centralized in Snowflake so supply-chain, pricing, and operations teams can work from a faster, more reliable operating view. The platform also connects with Azure, dbt, Terraform so upstream systems and downstream consumers stay aligned around the same governed data assets. 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. With Snowflake, Völur rapidly processes data and shares actionable insights that help customers maximize product value while reducing waste.
Data flow
application, customer, event, and operational data flow into Snowflake; curated data, reports, and model outputs are then served to supply-chain, pricing, and operations teams.
Solution architecture
- Storage
- Snowflake Provides the centralized data platform that stores governed datasets and serves analytics or AI workloads.
Architecture clues
- Integrates with Azure, dbt, Terraform as part of the broader delivery workflow.
Evidence from the source
In an industry with a complex value chain, nuance can make a big difference. According to Völur’s team, deep industry knowledge is key to making AI algorithms meaningful for their customers
With Snowflake, Völur rapidly processes data and shares actionable insights that help customers maximize product value while reducing waste
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
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 value75/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth25/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact0/250 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence67%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence10/202 direct source quotes retained.
- Date provenance0/10The publication date has no documented provenance.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity8/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.snowflake.com/en/customers/all-customers/case-study/volur/SnowflakeFirst-party
Völur 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
- First archived Jul 10, 2024 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.Open date source
- Sitemap last modified Jul 9, 2026 · Snowflake · Publisher metadata Publisher-reported modification timestamp; not a publication date.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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