STRATEGIC FINANCE
ADVISORY SERVICES THAT
MOVE THE NEEDLE.
From raising your institutional round to navigating a complex acquisition -
we are in the room with you, from strategy through execution
FINENGINE
AI-NATIVE ENTERPRISE PERFORMANCE MANAGEMENT SYSTEM
Every AI finance tool can generate output. FinENGINE generates output a CFO trusts.
The difference is context.
FinENGINE is built around a structured intelligence layer - your metric definitions, your initiative owners, your variance patterns, your commentary - embedded directly alongside your financial data.
That context is embedded in every feature. Every workflow. Every output.
The result reads like a senior finance leader who has been at your company for years.
Not because the AI is smarter. Because it knows your business.
That is FinENGINE.
TREASURY
AGENTIC TREASURY MANAGEMENT SYSTEM
Most treasury tools make you do the work. Ours acts more like a strategic companion.
The Finance Pro's Treasury Management System is a full stack AI-native agentic platform - liquidity, Fx, reconciliation, working capital and more.
AI doesn't sit on top of this platform. It's built into it — assisting with transaction matching, exception classification, statement ingestion, and financial reporting so your team spends less time processing and more time driving strategy.
Institutional-grade treasury intelligence. Built for the ambition of the modern CFO.
Smarter treasury. Fewer hours. Zero compromises.
PREDICTLY
ML-POWERED REVENUE PREDICTION
Revenue prediction is one of the most high-value applications of machine learning (ML) in Finance. Yet, traditional methods are relied upon.
Traditional financial forecasting — spreadsheet-based linear extrapolations or simple regression struggle with fundamental challenges:
Non-linearity: Revenue drivers rarely move in straight lines. Seasonal spikes, competitive disruptions, and macro shocks create patterns that classical models miss.
High dimensionality: Modern companies generate hundreds of signals (pipeline data, product usage, macro indicators, web traffic) that a human analyst cannot synthesize efficiently.
Latency: Spreadsheet models are updated on monthly or quarterly cycles. ML models can run continuously on live data, producing rolling forecasts.
Machine learning addresses these gaps by learning complex, non-linear patterns from historical data and generalizing them to future periods — all at scale and speed that finance teams cannot replicate manually.
PREDICTLY
powered by Lasso Regression
PREDICTLY
powered by Random Forest
PREDICTLY
powered by Long Short Term Memory
HOW WE WORK
OUR DEPLOYMENT PROCESS
A structured approach that gets you live faster — without the chaos of a typical software implementation.
01
Discovery
Assess your current stack, data quality, and reporting needs.
02
Design
Architecture, data, model, and platform selection.
03
BUILD
Configuration, model build, and integration with your systems.
04
TEST
UAT, data validation, and reconciliation against source systems.
05
DEPLOY
Go-live, team training, and full documentation handoff.
06
SUPPORT
Ongoing monitoring, recalibration, and model updates.