Use Case Intelligence RSS Search use cases Search
Databricks Telecommunications United States

First Orion

Enterprise Knowledge Search · Fraud Detection · Risk Management

First Orion needed a better way to support caller transparency, spoof mitigation, and AI-powered scam detection because massive call volumes and siloed EMR-based data workflows made fraud detection and new AI features costly to develop and hard to govern.

Read the original story Explore all use cases
$12.7M building trust in mobile communications
5x efficiencies and new product innovations

Reported impact

Business outcome

First Orion improved caller transparency, spoof mitigation, and AI-powered scam detection with measurable results including $12.7M building trust in mobile communications and 5x efficiencies and new product innovations, while giving teams a faster path from governed data to production decisions.

  • Productivity Improvement
  • Revenue Growth
  • Risk Reduction

Solution

First Orion uses Databricks Data + AI Platform to support caller transparency, spoof mitigation, and AI-powered scam detection. The implementation replaced a legacy state where massive call volumes and siloed EMR-based data workflows made fraud detection and new AI features costly to develop and hard to govern. Call traffic data and scam and spoofing signals move through production data pipelines and land in Delta Lake, giving teams one trusted data foundation. Unity Catalog governs access, lineage, and compliance across sensitive datasets. Databricks SQL, MLflow, and Agent Bricks operationalize models, agents, and analytics that deliver caller transparency products and fraud and compliance analytics. First Orion improved caller transparency, spoof mitigation, and AI-powered scam detection with measurable results including $12.

Data flow

Call traffic data and scam and spoofing signals land on a shared platform, pipeline services clean and standardize them, governance controls enforce trusted access, and AI, model-serving, and analytics services deliver caller transparency products and fraud and compliance analytics.

Solution architecture

7 components · 4 layers
  1. Compute
    • Databricks Data + AI Platform Databricks Data + AI Platform unifies engineering, analytics, governance, and AI workloads for caller transparency, spoof mitigation, and AI-powered scam detection.
    • MLflow MLflow tracks experiments, versions, and release workflows for models that support caller transparency, spoof mitigation, and AI-powered scam detection.
    • Amazon EMR Amazon EMR performs large-scale data processing and transformation for caller transparency, spoof mitigation, and AI-powered scam detection.
  2. Storage
    • Delta Lake Delta Lake stores curated call traffic data and scam and spoofing signals so every team works from one trusted data foundation.
  3. Serving
    • Databricks SQL Databricks SQL serves curated dashboards and ad hoc analysis to caller transparency products and fraud and compliance analytics.
    • Agent Bricks Agent Bricks packages domain-specific agents that automate parts of caller transparency, spoof mitigation, and AI-powered scam detection.
  4. Governance
    • Unity Catalog Unity Catalog applies centralized access controls, lineage, and auditability across sensitive datasets.

Architecture clues

  • $12.7M building trust in mobile communications
  • 5x efficiencies and new product innovations
  • Centralized governance, lineage, and access controls are enforced through Unity Catalog.
  • Delta Lake provides the shared storage layer for curated lakehouse datasets.
  • Operational AI workflows are deployed directly beside governed data and analytics assets.

Evidence from the source

Building, managing, and maintaining clusters, notebooks, and production jobs was arduous and expensive. First Orion had to combine EMR and Jupyter notebooks and manually configure Apache Spark™ settings on a case-by-case
From developers to architects to data scientists, we’re saving a massive amount of time now that they can focus on outcomes, collaborate on the same platform, easily access data, and use the tools to help other teams.
Team members can be independent without being siloed because Databricks has straightforward tools. Almost anyone can access and apply the insights and analytics we need to optimize communications.
U.S. mobile subscribers received over 100 billion scam calls during the first half of 2022. First Orion protects mobile customers with branded calling, real-time spoof mitigation and scam prevention. Handling over 350 mi
Transparency Evidence & methodology 100/100 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 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 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
    4 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

    First Orion customer story

    First-party
    https://www.databricks.com/customers/first-orion
    Source type
    Vendor-published customer story
    Published
    Sep 1, 2023
    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 Sep 1, 2023 · 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.

Related

Similar use cases

See all like this
Microsoft Jul 18, 2024 Lionbridge Commercial and Professional Services United States Realizing the need for faster and more agile localization services Founded in 1996, Lionbridge combines the best of human and machine intelligence to support large companies around the world with content creation,… "We already have more than 500 customers using AI to help with content optimization, and we're getting that… Enterprise Knowledge SearchFraud Detection Azure AI Foundry · Azure AI Translator · Azure OpenAI Service Microsoft Jun 14, 2024 House730 Real Estate and Construction Hong Kong SAR The city's property market is highly fragmented with many agents restricted to listings within their community. 2023, House730 enjoyed a 30 percent uptick in users who started their property search online first Enterprise Knowledge SearchFraud Detection Azure AI Foundry · Azure OpenAI Service · Power Platform Databricks Aug 18, 2026 Sabesp Energy Brazil To support this transformation, Sabesp modernized its legacy Oracle Exadata-based data warehouse and adopted Databricks as the foundation for its data and AI strategy. Today, Databricks powers a Data Mesh architecture spanning more than 23 business domains, supports large-scale… Data Lake / Data Warehouse ModernizationFraud Detection AI/BI · Databricks SQL · Genie