Hard-mode fintech & crypto products

Problem

A team needed a multi-chain trading platform supporting advanced orders and multi-chain wallets with ability to add new networks without downtime.

Solution

Built modular architecture with separate services for order book, execution routing, portfolio analytics, wallet management and risk with CEX/DEX integrations.

Problem

Fintech company needed unified UX combining multi-currency accounts, IBANs, cards and crypto wallet instead of multiple disjointed services.

Solution

Built core banking engine with accounts, ledger, FX flows, card issuance integrations and integrated crypto wallet in a single mobile app.

Problem

Crypto service needed robust way for users to move money between fiat and crypto using many payment providers with optimized routing.

Solution

Built orchestration layer with intelligent routing engine choosing providers based on user country, limits, and historical performance.

Problem

Bank and crypto exchange needed unified AML/CTF monitoring across BTC, ETH, TRON with transaction monitoring and address-level risk scoring.

Solution

Real-time on-chain data ingestion, transaction graph construction, wallet risk scoring using ML, and anomaly detection.

Problem

Financial service provider losing users to slow manual KYC checks taking hours or days.

Solution

AI onboarding with OCR on documents, FaceID + liveness detection, spoofing detection, and KYC provider integrations.

Problem

Crypto platform wanted to launch copy trading with ML-enhanced signals instead of purely manual strategies for smoother equity curves.

Solution

Built ensemble of LSTM models, token-specific behavior models, sentiment analysis and risk management layer with exposure limits.

Problem

Lender wanted to reduce default rates and operational costs without lowering approval rates significantly.

Solution

AI credit scoring with XGBoost/CatBoost, AutoML feature engineering, and SHAP explainability integrated into underwriting.

Problem

Investment platform needed dynamic AI-driven strategies adapting to macro regimes instead of static model portfolios.

Solution

Deep RL for portfolio optimization, GRU/LSTM for macro signals, and LLM layer explaining decisions in plain language.