Google Cloud Software / SaaS Australia

Decidr

Real-time Analytics

Decidr needed to turn scattered documents, spreadsheets, invoices, and operational records into deterministic business intelligence in hours rather than months while avoiding custom infrastructure work.

Reported impact

Business outcome

Decidr shortened time-to-intelligence, processed more cross-system data in real time, and cut infrastructure-management effort for customers using its decisioning platform.

  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

Decidr uses Google Cloud to address this challenge: Decidr needed to turn scattered documents, spreadsheets, invoices, and operational records into deterministic business intelligence in hours rather than months while avoiding custom infrastructure work. Google Workspace provides the Drive, Docs, and Sheets data sources that feed Decidr’s ingestion and translation pipelines, serving as the ingest layer. Gemini Pro reasons across long-context supplier records, invoices, and usage data to create structured intelligence and deterministic models, serving as the compute layer. Gemini 3 Flash supports high-speed real-time processing across cross-system data workloads, serving as the compute layer. Identity and Access Management delivers fully managed access control and reduces operational overhead for the platform, serving as the governance layer.

Data flow

Data from Drive, Docs, Sheets, supplier records, invoices, and usage systems is ingested into the Decidr schema through Google Workspace connectors, Gemini models structure and reason across the content, and deterministic models return real-time operational recommendations.

Solution architecture

4 components · 3 layers
  1. Ingest
    • Google Workspace provides the Drive, Docs, and Sheets data sources that feed Decidr’s ingestion and translation pipelines
  2. Compute
    • Gemini Pro reasons across long-context supplier records, invoices, and usage data to create structured intelligence and deterministic models
    • Gemini 3 Flash supports high-speed real-time processing across cross-system data workloads
  3. Governance
    • Identity and Access Management delivers fully managed access control and reduces operational overhead for the platform

Architecture clues

  • Infrastructure management overhead dropped by 45% by relying on managed Google services
  • The eBev purchasing model reasons over historical behavior, supplier terms, and consumption patterns
  • The platform includes deterministic purchasing models that preserve transparency and auditability

Evidence from the source

Processes 10× more cross-system data in real time with Gemini across Google Workspace.
Reduces data integration time by up to 65% through automated ingestion and translation pipelines from Drive Docs Sheets, and Gemini into the Decidr schema.
We selected Gemini Pro for its advanced reasoning capabilities and long-context handling.
Transparency Evidence & methodology 71/100 reference value · 77% confidence · 3 sources

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 value71/100
  • 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 specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    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 traceability25/25
    12 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency9/10
    3 source references 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

    Decidr customer story

    First-party
    https://cloud.google.com/customers/decidrai
    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
  2. Decidr

    Decidr homepage

    First-party
    https://www.decidr.ai/

    The homepage JSON-LD lists addressCountry "AU", addressLocality "Sydney", and streetAddress "Suite 1, Level 20/347 Kent St," supporting Australia as the headquarters country.

    Source type
    Official company website
    Supports
    • Region
  3. LinkedIn

    Decidr | LinkedIn

    Independent secondary
    https://www.linkedin.com/company/decidr-ai/

    The Organization JSON-LD lists addressLocality 'Sydney', and addressCountry 'AU', and numberOfEmployees value 52.

    Source type
    Structured company profile
    Supports
    • Company size
    • Region

Date evidence

  • First archived Mar 17, 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 Feb 18, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.