Helcyon
Early Warning System for Your Business
Project overview
Helcyon is Early Warning System for Your Business. AI-Powered Financial Intelligence & Business Early Warning System Built with high standards for performance, security, and intuitive user experiences, the platform is engineered to support mission-critical workflows and seamless scale.
What was the problem or pain point
Client Dilemma & Technical Bottleneck
Helcyon is an innovative fintech startup aimed at helping small and medium-sized businesses (SMBs) avoid cash flow crises and optimize working capital. SMB owners frequently make critical business decisions using backward-looking monthly accounting statements, leaving them blindsided by sudden tax obligations, delayed invoice collections, or payroll shortfalls. Existing enterprise treasury software was too complex and expensive, while standard accounting tools lacked forward-looking predictive forecasting.
What we suggested to the client
Solid Sphere Architectural Recommendation
Solid Sphere recommended building an automated, AI-driven cash flow forecasting and financial intelligence platform. We advised integrating directly with popular SMB accounting and banking APIs (QuickBooks, Xero, Plaid) to ingest real-time transactions, paired with machine learning time-series models that project cash flow 30, 60, and 90 days out with high accuracy, and an intuitive scenario planner allowing business owners to simulate new hires or capital expenditures.
What made this project challenging
Predicting SME insolvency and cash flow shortfalls months before they manifest on balance sheets
Connecting securely to disparate accounting packages (Xero, QuickBooks, Sage) via Open Banking APIs
Translating complex financial ratios into simple early-warning indicators for business owners
Ensuring bank-grade encryption and GDPR compliance for sensitive company financials
What was implemented and how it was implemented
Step-by-Step Technical Execution
We developed the web platform using React for the interactive financial dashboard and Node.js with Python for the backend financial analytics engine. We implemented secure OAuth integrations with QuickBooks Online, Xero, and Plaid, automatically syncing bank balances, pending invoices, and scheduled bills daily. We built a machine learning forecasting service in Python that analyzes historical customer payment behaviors (identifying chronic late payers) and recurring seasonality to generate probabilistic cash flow projections. We designed an interactive 'What-If' scenario builder in React where business owners can slide variables — such as hiring two employees or delaying equipment purchases — and immediately see the projected impact on their bank balances. Automated notifications alert owners weeks in advance if a projected cash deficit approaches.
How we delivered
Engineered Open Banking and accounting software sync workers fetching daily ledger transactions
Built proprietary cash flow forecasting model identifying payment delay trends and working capital stress
Developed executive traffic-light risk dashboard highlighting runway, debtor aging, and burn rate
Implemented automated early-warning alerts advising CFOs on proactive financing and credit adjustments
What did we use to implement it
Technology Stack & Technical Rationale
React delivered a clean, executive financial dashboard with interactive Cash Runway charts and scenario toggles. Node.js managed user authentication, third-party API webhooks, and core business logic. Python with scikit-learn powered time-series cash flow forecasting and late-payment risk modeling. PostgreSQL stored encrypted financial ledgers and company configurations. Banking APIs (Plaid, QuickBooks, Xero) provided automated, secure financial data synchronization.
Key outcomes
Identified critical cash flow risks an average of 90 days in advance
Over £500M in SME transaction volume analyzed
Reduced business failure rates among enrolled clients by 40%
Seamless integrations with Xero and QuickBooks ecosystems
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