What challenges did Junson Capital face before AI implementation?

Extract structured intelligence from high-variance unstructured investment and administrative documents. Manual processing took 15.5 days per report and monthly reimbursement/invoice matching took about 10 days. Maintain global data residency and privacy compliance while processing sensitive financial documents.

What was the impact of the AI solution?

Report generation time reduced from 15.5 days to 1 day. Monthly reimbursement workflows reduced from 10 days to 1 hour. Achieved 90%+ resource efficiency. A team of two could manage work that previously required 15 people. 100% data residency compliance across key markets.

Source

GCPProductionEvidence: Medium65/100

Junson Capital scales an AI-native data engine with Vertex AI and Document AI (investment reporting + reimbursement automation)

Use case typeIntelligent document processingUpdated Jun 13, 2026

Junson Capital is a global investment management firm spanning real estate, private equity, and public markets across Hong Kong, Singapore, New York, and Palo Alto. The firm built a proprietary AI-native data framework to extract structured intelligence from high-variance, unstructured investment and administrative documents. The solution uses Vertex AI, Document AI, Gemini 2.5 Flash, Gemini 2.5 Pro, and Google Cloud Regions to support data extraction, automation, and regional data residency.

Organization: Junson Capital
Industry: Finance
Location: Hong Kong
Published: June 2026

Reported outcomes

−93.5%

report generation timeTime & speed

−99.6%monthly reimbursement workflow time90%productivity100%quantified impact

Strategic outcomes

New product / capabilityBuilt proprietary AI-native data extraction frameworkSpeed & agilityAutomated reimbursement and invoice matching workflowsRisk & complianceEnabled regional data residency complianceScale & capacityExpanded operational capacity with smaller team

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Report generation time: 93.5% decrease

Google Cloud Customer StoriesJun 3, 2026Customer storyExplicit claimMedium evidence strength

Report generation time reduced from 15.5 days to 1 day.

Correction recorded Jul 26, 2026 · Previously: 15.5 days decrease · Replaced endpoint-only extraction with one source-verified duration transition.

Normalized claim

Monthly reimbursement workflow time: 99.6% decrease

Google Cloud Customer StoriesJun 3, 2026Customer storyExplicit claimMedium evidence strength

Monthly reimbursement workflows reduced from 10 days to 1 hour.

Correction recorded Jul 26, 2026 · Previously: 1 days decrease · Removed a duplicate endpoint after preserving the full duration transition.

Normalized claim

Productivity: 90%

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

Achieved 90%+ resource efficiency.

Correction recorded Jul 26, 2026 · Previously: 10 days decrease · Replaced endpoint-only extraction with one source-verified duration transition.

Normalized claim

Quantified impact: 100%

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

100% data residency compliance across key markets.

Correction recorded Jul 26, 2026 · Previously: 1 hours decrease · Removed a duplicate endpoint after preserving the full duration transition.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Junson Capital
Provider: GCP
Maturity: Production
Linked source: Google Cloud Customer Stories

Deployed Vertex AI and Document AI to extract structured data from complicated documents

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

1Document automation
2Intelligent document processing
3Workflow automation

Extract structured intelligence from high-variance unstructured investment and administrative documents.
Manual processing took 15.5 days per report and monthly reimbursement/invoice matching took about 10 days.
Maintain global data residency and privacy compliance while processing sensitive financial documents.

Deployed Vertex AI and Document AI to extract structured data from complicated documents.
Built a proprietary six-layer recognition framework for vertical industry data extraction.
Used Gemini 2.5 Flash and Gemini 2.5 Pro, with regional hosting planned in Singapore for data residency.
Built a digital employee application to automate internal reimbursement and invoice matching workflows.

Technologies

Vertex AI Document AI Gemini 2.5 Flash Gemini 2.5 Pro Google Cloud Regions

Report generation time reduced from 15.5 days to 1 day.
Monthly reimbursement workflows reduced from 10 days to 1 hour.
Achieved 90%+ resource efficiency.
A team of two could manage work that previously required 15 people.
100% data residency compliance across key markets.

Architecture

A proprietary six-layer recognition framework combines Vertex AI and Document AI for structured extraction from complex documents, with Gemini 2.5 Flash and Gemini 2.5 Pro used in the workflow and planned regional hosting in Singapore via Google Cloud Regions to meet data residency requirements.

Sources & evidence1

Evidence: Medium65/100Evidence strength