We Are the First Full-Stack AI Trade Finance Company
Trade finance is ready for reinvention. Legacy processes rely on paper, manual checks, and siloed systems—leaving more than 130 million SMEs locked out of funding. We are laying new rails for real-time, AI-driven trade execution
where onboarding, risk scoring, and capital deployment clear in hours, not weeks.
1 What “Full-Stack AI Trade Finance” Means in Practice
| Stack Layer |
What We Have Built |
| Client Onboarding |
AI-assisted KYB with OCR + LLMs; instant sanctions and PEP screening. |
| Underwriting |
Neural models trained on 3 000+ historical deals and 20 million datapoints. |
| Deal Structuring |
Smart templates for DLCs, SBLCs, forfaiting, payables, receivables. |
| Capital Matching |
API-linked marketplace of private-credit funds, banks, and DFIs. |
| Execution & SWIFT |
Direct bank rails, optional tokenisation, integrated payments. |
| Monitoring |
IoT shipment pings + invoice status feed risk dashboards in real time. |
2 Market Timing: The USD 5 Trillion Window
- Trade-finance gap: USD 2.5 trn in 2022—growing annually. (ADB/WTO)
- Bank retrenchment: 60 % of rejections in emerging markets. (ICC)
- Private-credit AUM: USD 1.6 trn in 2024—seeking short-duration yield. (Preqin)
- Historical defaults: < 0.2 %; self-liquidating, asset-backed. (ITFA)
3 Traction to Date (Q2 2025)
| Metric |
Value |
| Funded trade volume |
USD 87 million |
| Active clients |
120 + across West Africa, UAE, Türkiye, SE Asia |
| Deal cycle time |
Cut from 22 days to < 72 hours |
| Active bank issuers |
16—including Citi, HSBC, CCB, Mashreq, Standard Chartered |
| Investor appetite |
Primary notes 3× oversubscribed (9–12 % net yield) |
4 How the 72-Hour Flow Works
- Client uploads trade documents.
- AI model scores counterparties, route, and pricing risk.
- Structured offer auto-routes to investor pool.
- Capital deploys via DLC, SBLC, or direct pay.
- Shipment and repayment tracked by API integrations.
5 Why We Win
| Market Pain |
Our Answer |
| Banks demand hard collateral |
Confirmed POs and invoices serve as soft collateral. |
| Opaque markets cloud risk pricing |
Models ingest customs, shipping, credit-bureau, and portfolio data. |
| Deals crawl through manual checks |
AI shrinks onboarding + underwriting from weeks to hours. |
6 Revenue Model
- Origination — 1–3 % of funded volume
- Servicing — 0.5–1.5 % annualised
- Investor spread — carry on warehoused positions
- Premium SaaS tools for trade intermediaries
7 Leadership & Technical Team
The founder appoints a qualified technical core
that codes product and data pipelines with extensive AI assistance. Key hard-skill domains:
- Python & TypeScript micro-services, gRPC, and GraphQL APIs
- LLM fine-tuning (OpenAI & open-weight models), vector search, prompt engineering
- Computer-vision OCR for shipping docs and Swift MT messages
- Swift ISO 20022 integrations, blockchain token-standards (ERC-1400, Hyperledger Fabric)
- Data-engineering stacks (Snowflake, Spark, dbt) for risk ingestion
- DevOps with Terraform, Kubernetes, CI/CD coded via AI pair-programming
Strategic partnerships power the back-end: custodial banks for instrument issuance, logistics APIs for live shipment data, and RegTech providers for automated compliance. Even outbound marketing runs on a rules-based, AI-driven engine—delivering evergreen lead generation in a sector where demand never sleeps.
See the Platform in Action
Explore how AI compresses trade-finance cycle times to hours and transforms short-tenor paper into investable digital assets. Walk through our full architecture, live metrics, and roadmap.
How the Platform Works