Reported impact
Business outcome
New models deployed in 1.5 weeks
- Revenue Growth
- Scalability
- Speed to Market
Google CloudFinancial ServicesRisk ManagementAI and Machine LearningData AnalyticsRevenue GrowthScalabilitySpeed to MarketUndated Google CloudGC#4285f4Financial ServicesArgentinaBold is an Argentine deep-tech startup building the agricultural financing AI infrastructure that turns Earth observations data into credit intelligence for financial institutions across Latin America."With minimal information, we can infer everything we need and finish a credit analysis in 48 hours."Modified · Jul 14, 20264Risk ManagementAgent Platform · Apigee · BigQuery0 2026-07-14 4
Bold
Risk Management
Bold is an Argentine deep-tech startup building the agricultural financing AI infrastructure that turns Earth observations data into credit intelligence for financial institutions across Latin America.
"With minimal information, we can infer everything we need and finish a credit analysis in 48 hours."
Bold built agricultural financing AI infrastructure on Google Cloud, cutting credit analysis from weeks to hours for BBVA Argentina.
Bold's platform now powers $1.2 billion in annual agricultural loans at BBVA Argentina.
Inference time cut from minutes to seconds
Solution
Their platform runs on two internal layers: Daredevil, the Earth-sensing layer that ingests and processes signals, and Thot, the AI agentic layer that turns those signals into actionable economic intelligence. "When you are building something nobody has built before, there is no manual," says Kevin Canova, CTO and co-founder of Bold. "You figure out the architecture, you test it, and then you need infrastructure that does not collapse when the data starts coming in at scale." With Google Cloud in place, Bold built a pipeline that takes raw signals and turns them into credit-ready intelligence in near real time. The process starts with Daredevil ingesting signals from satellites and data streams across millions of hectares. That data flows into BigQuery , which serves two roles simultaneously: a data warehouse that stores and organizes the geospatial information, and a feature store that exposes the right data the moment a request comes in.
Solution architecture
- Compute
- Cloud Run Runs serverless application services and APIs with automatic scaling for bursty workloads.
- Storage
- BigQuery Serves as the governed analytics and storage layer for high-volume operational data, features, and reporting.
- Serving
- Apigee Manages APIs that expose governed services to connected applications and partners.
- Orchestration
- Gemini Enterprise Agent Platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.
- Gemini Enterprise Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
- Agent Platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.
Architecture clues
- Their platform runs on two internal layers: Daredevil, the Earth-sensing layer that ingests and processes signals, and Thot, the AI agentic layer that turns those signals into actionable economic intelligence.
Evidence from the source
"What used to be a slow, manual, fragmented process is now a complete flow," says Juan Pedro Gazzotti, head of agribusiness at BBVA Argentina. "With minimal information, we can infer everything we need and finish a credi
Founded in 2024, the company processes real-time data from climate, soil, radar, laser, and multispectral sensors covering 600 million hectares in Latin America, detecting planting and harvesting dates of crops, rotation
Gemini Enterprise Agent Platform is where Thot does its work, training and deploying the models that power real-time insights. Thot, powered by Gemini , adds a layer of contextual reasoning on top of the signals, interpr
New models deployed in 1.5 weeks
Partner Maplink helped homologate the architecture to ensure it could perform in production from day one. "Latin America has 600 million hectares of agricultural land," Canova says. "We have made 40 million visible so fa
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
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 value82/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth15/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity12/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact25/253 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence75%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance0/10The publication date has no documented provenance.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity6/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://cloud.google.com/customers/boldGoogle CloudFirst-party
Bold 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 Jul 14, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.Open date source
- Unverified extracted date Jul 14, 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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