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Google Cloud Financial Services Brazil

Nova Gestões

Customer Service Automation

Nova Gestões used Gemini to eliminate manual data entry and boost agent productivity by 30% across 100 million monthly calls.

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30% productivity increase across 1,700 agents
5 million improvement suggestions generated per month
83% agility gain from eliminating manual data entry
Call monitoring scaled from less than 1% to 100%

Reported impact

Business outcome

Call monitoring scaled from less than 1% to 100%; Wrap time reduced from 2 minutes to 10 seconds; 30% productivity increase across 1,700 agents; 83% agility gain from eliminating manual data entry

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Risk Reduction

Solution

Nova Gestões used Gemini to eliminate manual data entry and boost agent productivity by 30% across 100 million monthly calls. When generative AI arrived as a market force, Nova Gestões didn’t chase the hype. They identified real pain points and attacked them one by one. After testing other providers and finding quality results came at costs 10 times higher than acceptable, Google… The first is Matrix AI, a monitoring and intelligence tool built with Gemini platform . Each call ends and within seconds the recording is processed, transcribed, and analyzed. The AI scores the agent's performance, extracts structured data including offers… Key components include Gemini platform coordinates multi-agent workflows, tool calling, and governed automation across the application; Gemini models provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis. Reported outcomes include Call monitoring scaled from less than 1% to 100%; Wrap time.

Solution architecture

2 components · 2 layers
  1. Compute
    • Gemini models Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
  2. Orchestration
    • Gemini platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.

Architecture clues

  • The first is Matrix AI, a monitoring and intelligence tool built with Gemini platform . Each call ends and within seconds the recording is processed, transcribed, and analyzed. The AI scores the agent's performance,…
  • The manual process created problems everywhere. After each call, agents spent two minutes entering data into the CRM, a process riddled with errors and human bias. Quality monitors, working from tiny samples, introduced…
  • The numbers tell a clear story. Nova Gestões went from monitoring less than 1% of interactions to 100%. Productivity increased by 30% and agility by 83%, driven largely by eliminating the two-minute wrap time. Matrix AI…
  • What stood out in Google was the capacity to interpret the entire conversation, not just isolated words. The context, the interaction, the negotiation, and transform all of that into structured data autonomously. That…

Evidence from the source

30% productivity increase across 1,700 agents
5 million improvement suggestions generated per month
83% agility gain from eliminating manual data entry
Call monitoring scaled from less than 1% to 100%
Nova Gestões used Gemini to eliminate manual data entry and boost agent productivity by 30% across 100 million monthly calls.
Wrap time reduced from 2 minutes to 10 seconds
Transparency Evidence & methodology 90/100 reference value · 77% 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
    6 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence77%
  • 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
    6 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 specificity8/10
    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

    Nova Gestões customer story

    First-party
    https://cloud.google.com/customers/nova-gestoes
    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

  • Sitemap last modified Oct 9, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Oct 9, 2026 · Google Cloud · Unknown Legacy extracted date without source-page confirmation.
    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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