END-TO-END GLOBAL AI INFRASTRUCTURE

Business predictive engines. Deploy via REST API in minutes.

GI2.Tech provides the analytical layer for your organization. Achieve massive scalability in risk prevention, alternative credit scoring, and process automation without refactoring your core architecture.

Talk to Engineering API Documentation
SOC 2 Type II Compliant PCI-DSS Environment Deployed on AWS us-east-1 / eu-west-1
+12.5M
API Calls / Day
99.99%
Global SLA
< 40ms
Network P95 Latency

Trusted by Enteprises:

NeoBank (NDA)* GlobalRetail LLC

Modular API Ecosystem

Integrate a single engine or assemble the entire suite natively. Designed under strictly compliant REST standards.

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Docs →
FraudShield Core™

/v2/transactions/analyze

Statistical ML heuristics to evaluate digital identity and reduce financial chargebacks reliably.

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Docs →
CrediScore Engine™

/v1/scoring/evaluate

Alternative credit scoring algorithm designed to underwrite sub-prime users without increasing your NPL metrics.

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Docs →
RevMax Platform™

/v1/pricing/predict

Stochastic price elasticity models to dynamically optimize margins for massive Enterprise E-commerce datasets.

AutoFlow AI™

/v1/rpa/webhook

On-premise OR Cloud RPA orchestrators. Safely replace manual ERP bottlenecks maintaining 100% data concordance.

Built for Engineers. Verified by Finance.

Scalability is a solved mathematical problem. Deploy our infrastructure using our strict SDKs and modern OAuth2 authentication.

  • ✓ Comprehensive Open API 3.0 Documentation
  • ✓ Ultra-low latency programmable Webhooks
  • ✓ Isolated Sandbox Environment for secure testing
Read Integration Guide
POST /api/v2/transactions/analyze 
const payload = await fetch('https://api.gi2.tech/v2/transactions/analyze', {
  method: 'POST',
  headers: { 'Authorization': `Bearer ${GI2_API_KEY}` },
  body: JSON.stringify({ amount: 1250.00, currency: 'USD' })
});
if (payload.risk_level > 85) await FraudShield.block();

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*Our enterprise clients operate under strict NDAs. Direct references are shared exclusively during private due diligence processes.