Google Cloud Software / SaaS United Kingdom

Parsewise

Document Processing · Risk Management · Security and Compliance

For risk specialists in the financial services and insurance industries, reading can feel like a full-time job. Whether assessing an insurance claim or approving a loan, these subject matter experts must search through hundreds of pages of scanned forms, multi-tab spreadsheets, and legal text to find specific details.

29% lower error rate than best-performing LLM on grounded-reasoning benchmark
8x faster portfolio review time with Gemini
Parsewise uses Gemini to streamline complex risk analysis, accelerating review times 8x and delivering benchmark-leading accuracy.

Reported impact

Business outcome

8x faster portfolio review time with Gemini; 29% lower error rate than best-performing LLM on grounded-reasoning benchmark; Handles unpredictable traffic surges with Gemini Enterprise Agent Platform; Parsewise uses Gemini to streamline complex risk analysis, accelerating review times 8x and delivering benchmark-leading accuracy..

  • Compliance
  • Cost Reduction
  • Productivity Improvement
  • Risk Reduction

Solution

To build trust in its output, Parsewise uses the models' spatial understanding to pinpoint exactly where specific data such as a relevant number appears, highlighting the location on the original scanned page. With one click, human analysts can trace each result back to its source, making it easier to resolve inconsistencies across documents and greatly reducing the risk of hallucinations. Parsewise also needs to ensure its customers can trust the platform’s data security and regulatory compliance. By selecting regional data residency settings within the Gemini Enterprise Agent Platform, Parsewise restricts data processing to the European Union, ensuring it meets strict GDPR and SOC 2 requirements for its financial clients. “Gemini Flash stands out against previous third-party models we tested because it actively asks for more information when context is missing,” says Nikola Bozhinov, head of engineering at Parsewise.

Data flow

processed with Gemini 3.0 Flash, orchestrated via Gemini Enterprise Agent Platform, and surfaced through Gemini Enterprise, Gemini 3.5 Flash, Gemini Flash, Gemini

Solution architecture

6 components · 3 layers
  1. Compute
    • Gemini 3.0 Flash Extracts and reasons over complex unstructured content at high speed.
  2. Serving
    • Gemini Enterprise Provides a secure enterprise environment for teams to use Gemini with governed data access.
    • Gemini 3.5 Flash Handles conversational reasoning across large document sets and user questions.
    • Gemini Flash Handles high-volume generative AI tasks with lower latency and lower serving cost.
    • Gemini Powers natural-language reasoning, summarization, generation, or assistance inside the workflow.
  3. Orchestration
    • Gemini Enterprise Agent Platform Provides governed enterprise access to Gemini models, agents, and regional controls.

Architecture clues

  • # Meet the startup transforming financial risk assessment with 8x faster case reviews with Gemini
  • 8x faster portfolio review time with Gemini
  • Handles unpredictable traffic surges with Gemini Enterprise Agent Platform
  • Parsewise integrates Gemini models directly into its data processing pipelines and conversational workspace, Navi. This setup helps analysts safely upload, extract, and question their files in a logical sequence.
  • Parsewise uses Gemini to streamline complex risk analysis, accelerating review times 8x and delivering benchmark-leading accuracy.
  • Processing unstructured documents and reasoning across files with Gemini models

Evidence from the source

29% lower error rate than best-performing LLM on grounded-reasoning benchmark
8x faster portfolio review time with Gemini
Handles unpredictable traffic surges with Gemini Enterprise Agent Platform
Parsewise uses Gemini to streamline complex risk analysis, accelerating review times 8x and delivering benchmark-leading accuracy.
Streamlining risk analysis for regulated industries
Transparency Evidence & methodology 95/100 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 value95/100
  • 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 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

    Parsewise customer story

    First-party
    https://cloud.google.com/customers/parsewise
    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 Sep 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 Sep 15, 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.