Reported impact
Business outcome
Increased productivity in depots
- Customer Experience
- Productivity Improvement
MicrosoftRetailEnterprise Knowledge SearchAI and Machine LearningGenerative AI / LLMCustomer ExperienceProductivity Improvement2025 MicrosoftMS#0078d4RetailUnited KingdomWe see Chip as a very exciting start to an exciting journey. Adoption will continue to grow, as will the power of these models—enabling us to go and solve our customers biggest problems.Jan 14, 20254Enterprise Knowledge SearchAzure AI Search · Azure AI Services · Azure OpenAI Service0 2025-01-14 4
Howdens
Enterprise Knowledge Search
We see Chip as a very exciting start to an exciting journey. Adoption will continue to grow, as will the power of these models—enabling us to go and solve our customers biggest problems.
Solution
We see Chip as a very exciting start to an exciting journey. Adoption will continue to grow, as will the power of these models—enabling us to go and solve our customers biggest problems. Howdens deployed the Microsoft Azure OpenAI Service with other Azure tools to create a tool that can be queried using natural language in a chat interface. “Last year has really allowed us to hone in on our business model,” says David Sturdee, Chief Customer Officer at Howdens. “This has allowed us, in turn, to become the trade’s first choice when it comes to kitchens.” Howdens used Azure AI Search, Azure AI Services, Azure OpenAI Service to support enterprise knowledge search with a governed operating model that connected the relevant data sources, automation logic, and employee-facing experiences without custom point-to-point tooling.
Data flow
Content from enterprise documents and knowledge sources is ingested into Azure AI Search, Azure OpenAI Service, Azure AI Services, where it is indexed, enriched, or reasoned over before grounded answers are returned to employees through business applications.
Solution architecture
- Compute
- Azure AI Search Indexes enterprise content and retrieves grounded context for search and copilot experiences.
- Azure AI Services Supplies language, vision, and other AI APIs that classify, interpret, or enrich source content.
- Azure OpenAI Service Provides large language model inference for natural language search, drafting, summarization, and recommendations.
Architecture clues
- Azure AI Search: Indexes enterprise content and retrieves grounded context for search and copilot experiences.
- Azure AI Services: Supplies language, vision, and other AI APIs that classify, interpret, or enrich source content.
- Azure OpenAI Service: Provides large language model inference for natural language search, drafting, summarization, and recommendations.
Evidence from the source
Howdens deployed the Microsoft Azure OpenAI Service with other Azure tools to create a tool that can be queried using natural language in a chat interface.
Increased productivity in depots
Microsoft Azure and Azure OpenAI
We see Chip as a very exciting start to an exciting journey. Adoption will continue to grow, as will the power of these models—enabling us to go and solve our customers biggest problems.
“Last year has really allowed us to hone in on our business model,” says David Sturdee, Chief Customer Officer at Howdens. “This has allowed us, in turn, to become the trade’s first choice when it comes to kitchens.”
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 value62/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity12/20Measures 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 confidence85%
- 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 evidence20/205 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity6/10Rewards 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.microsoft.com/en/customers/story/19779-howdens-azureMicrosoftFirst-party
Howdens 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
- Publication date
Date evidence
- Published on source page Jan 14, 2025 · Microsoft · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
Related
Similar use cases
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