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Databricks Public Sector United States

Hawaiian Electric Company

Document Processing · Enterprise Knowledge Search · Real-time Analytics

The utility company faced operational inefficiencies due to the time-consuming manual referencing of extensive regulatory documentation.

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2 weeks Implementation time to go from zero to RAG
5 seconds Time spent individually querying regulatory documents — down from five minutes
Hawaiian Electric (HECO), responsible for delivering power to 95% of Hawaii’s residents, grappled with a significant challenge: managing and efficiently accessing a vast trove of regulatory documentation.

Reported impact

Business outcome

Hawaiian Electric Company achieved measurable business impact on Databricks, including 5 seconds Time spent individually querying regulatory documents — down from five minutes; 2 weeks Implementation time to go from zero to RAG; Hawaiian Electric (HECO), responsible for delivering power to 95% of Hawaii’s residents, grappled with a significant challenge: managing and efficiently accessing a vast trove of regulatory documentation..

  • Compliance
  • Productivity Improvement
  • Scalability

Solution

Hawaiian Electric Company (HECO) seeks to create a green Hawaii, providing communities with reliable and renewable energy. The utility company faced operational inefficiencies due to the time-consuming manual referencing of extensive regulatory documentation. HECO leveraged the Databricks Data + AI Platform to develop a retrieval augmented generation (RAG) model proof of concept (POC), streamlining question-answering by integrating relevant data into the generation process. This allowed the regulatory team to quickly and accurately cross-reference documentation and provide answers to information requests about regulatory requirements and how HECO is staying compliant.

Data flow

Unstructured documents and reference data lands in Databricks and is transformed through managed pipelines

Solution architecture

2 components · 1 layer
  1. Compute
    • Agent Bricks Supports agentic or GenAI applications that Hawaiian Electric Company uses to automate or accelerate work.
    • Apache Spark Declarative Pipelines Runs declarative transformations that prepare source data for production analytics and AI.

Architecture clues

  • Cloud: Azure
  • Key product: Agent Bricks
  • Key product: Apache Spark Declarative Pipelines
  • Real-time or streaming data processing

Evidence from the source

2 weeks Implementation time to go from zero to RAG
5 seconds Time spent individually querying regulatory documents — down from five minutes
Hawaiian Electric (HECO), responsible for delivering power to 95% of Hawaii’s residents, grappled with a significant challenge: managing and efficiently accessing a vast trove of regulatory documentation.
Hawaiian Electric Company (HECO) seeks to create a green Hawaii, providing communities with reliable and renewable energy.
Joel Wasson, Manager of Enterprise Data and Analytics at HECO, described the scenario in more detail.
Transparency Evidence & methodology 90/100 reference value · 89% 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 value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    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
    3 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • 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 provenance10/10
    The publication date comes from the source page or publisher.
  • 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. Databricks

    Hawaiian Electric Company customer story

    First-party
    https://www.databricks.com/customers/hawaiian-electric-company
    Source type
    Vendor-published customer story
    Published
    Jul 23, 2024
    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 Jul 23, 2024 · Databricks · First-party
    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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