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Google Cloud Public Sector New York

Suffolk County

Customer Service Automation · Real-time Analytics

Suffolk County's departments faced seasonal call surges on outdated telephony infrastructure, with more than 600 calls per day, 30-minute waits, and over 70% of calls abandoned during peak property-tax periods.

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30% reduction in incoming call volumes during the high-stress property tax season
874 incoming calls within its first two weeks
Delivers secure, 24/7 multilingual assistance to 1.5 million residents across Suffolk County
average caller wait times topped 30 minutes

Reported impact

Business outcome

Suffolk County reduced waits and backlogs, resolved large portions of inbound traffic automatically, and established a repeatable public-sector model for AI-assisted resident services.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement

Solution

Working with Google Public Sector and UVS InfoTech, Suffolk County deployed the Civic Oriented Response Assistant (CORA) as an AI-powered first line of constituent service. CORA is built on Google Cloud Contact Center AI and integrated with the county's existing RingCentral telephony environment so callers can receive multilingual support around the clock without requiring a live agent for every request. Gemini platform extends the assistant's intelligence, while Google Cloud Storage and BigQuery support the knowledge and telemetry layers behind the service. Interaction data is streamed into BigQuery dashboards so the IT team can monitor resolution trends and tune workflows continuously. The system automates high-volume, repetitive calls during tax season, routes more complex issues to county staff only when needed, and gives employees more room to focus on deep constituent support rather than backlog triage.

Data flow

Resident calls enter through RingCentral and are answered by CORA on Contact Center AI. Gemini platform helps resolve or route requests, while call telemetry streams into BigQuery dashboards and related assistant content is stored in Google Cloud Storage for ongoing optimization.

Solution architecture

4 components · 3 layers
  1. Compute
    • Gemini platform Adds generative AI reasoning that helps CORA understand and resolve more complex resident questions.
  2. Storage
    • Google Cloud Storage Stores content and assets used by the virtual assistant environment.
  3. Serving
    • Contact Center AI (CCAI) Runs CORA as the county's conversational front door for multilingual voice interactions and automated workflow handling.
    • BigQuery Captures interaction telemetry for central dashboards used to monitor trends and optimize service performance.

Architecture clues

  • CORA is integrated with the county's existing RingCentral telephony system
  • The assistant is designed as an agentic virtual assistant for multiple county processes
  • The deployment was built with Google Public Sector and UVS InfoTech
  • interaction telemetry is streamed directly into BigQuery for dashboards

Evidence from the source

CORA handled 874 incoming calls within its first two weeks, directly resolving 36% of all inbound traffic.
Powered by Google Cloud Contact Center AI (CCAI) Platform and integrated seamlessly with the county’s existing RingCentral telephony system, CORA acts as an intelligent conversational first point of contact.
Streams interaction telemetry directly into BigQuery, powering a central dashboard
With limited agents, average caller wait times topped 30 minutes, and more than 70% of inbound calls were abandoned.
the system immediately drove a 30% reduction in incoming call volumes during the high-stress property tax season
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
    6 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. Google Cloud

    Suffolk County customer story

    First-party
    https://cloud.google.com/customers/suffolk-county-new-york
    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

  • First archived Jul 16, 2026 · 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 Oct 8, 2026 · Google Cloud · 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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