Outcomes we can stand behind.

SplitChey needed a production-ready expense tracking and bill splitting platform that could handle real-time group finances, multi-currency support, and seamless settlement flows. The MVP needed to launch fast with a clean, intuitive UI that made splitting bills feel effortless — not like doing accounting homework.

We built SplitChey as a full-stack Next.js application with real-time balance tracking, intelligent debt simplification, and group management. The platform supports flexible split types (equal, percentage, shares, itemized), multi-currency conversion, and automated settlement optimization that minimizes the number of transfers needed to clear all debts. Receipt scanning and expense categorization were added via AI integration.

TestFlow set out to eliminate the most time-consuming part of the development pipeline: writing and maintaining test cases. Existing testing tools required manual script writing, disconnected CI/CD pipelines, and no centralized visibility into test execution. Teams were shipping code with low confidence and expensive post-deployment bugs.

We built TestFlow as a repository-aware AI testing automation platform that connects directly to GitHub repos, analyzes codebases, and generates comprehensive test cases using Google Gemini. The platform auto-generates Playwright scripts, executes browser tests in Browserless cloud environments, and provides live execution tracking with detailed logs, screenshots, and trace artifacts — all from a single dashboard.

Aura Logistics operated three warehouses across the region with entirely manual processes. A four-person team spent 60% of their labor hours on physical inventory counts, cycle tracking, and order picking workflows that hadn't changed in a decade. The fulfillment cycle averaged 12 hours per order, and stockout rates hovered around 15% — burning margin and eroding customer trust.

We deployed a self-hosted JH Engine cluster with custom workflow nodes built specifically for Aura's warehouse topology. Real-time inventory synchronization now runs across all three facilities via WebSocket-fed dashboards. A custom ML demand forecasting model — trained on 18 months of historical order data — predicts stock depletion 72 hours in advance. Exception routing automatically escalates anomalies to the operations lead.

A cross-border payments startup needed a SOC 2 compliant mobile application — iOS and Android — within 90 days to hit their Series B fundraising timeline. Their legacy PHP backend suffered from 800ms p95 latency, had zero compliance framework, and relied on manual KYC verification that took 48 hours per user. No design system existed; every screen was bespoke.

We shipped a React Native application with a hardened Node.js backend, designed for sub-200ms p95 latency from day one. The architecture enforced SOC 2 alignment with encrypted data handling, audit logging, and automated KYC via document verification APIs. A shared design system — built in parallel with the app — gave their team a component library that scaled into Series B product iteration.

GlobalMart processed 50,000 daily orders through a Shopify storefront, but fraud detection was entirely manual — a three-person review team manually flagging suspicious transactions. The chargeback rate sat at 8%, costing the business millions annually. First-response time for customer inquiries averaged 4 hours, and the team had no automated routing or escalation paths.

We built a JH Engine order automation pipeline with AI-powered fraud scoring at the edge. Every incoming order is evaluated by a GPT-4o-backed model trained on historical chargeback patterns — scoring risk in under 200ms before payment settlement. Automated routing sends flagged orders to a review queue while clearing low-risk transactions instantly. Real-time Slack notifications keep the ops team in the loop without manual monitoring.