Intelligence Engine
Four layers.
One complete picture.
Seneca Aldwyn's architecture connects your fragmented data, computes standardised metrics, synthesises narrative intelligence, and generates forward-looking forecasts — in a single platform.
Data Integration Layer
Connect everything. Miss nothing.
Seneca Aldwyn connects directly to your existing tools — Exact Online, HubSpot, Jira, Stripe, Microsoft Project — and normalises the data into a unified financial model. We correlate engineering hours in Jira with invoices in Exact Online to show exactly which clients are burning your margins.
- Exact Online — live accounting and invoice feeds
- HubSpot CRM — revenue pipeline and deal data
- Stripe — payment and subscription feeds
- Jira — engineering hours and project cost tracking
- Microsoft Project — project timeline and resource cost
- Google Sheets API — custom and legacy data sources
- Custom XAF imports and CSV uploads for any system
- FinBERT-powered automatic transaction categorisation
Financial Analysis Engine
40+ metrics. 63 sector benchmarks.
Once data is unified, the analysis engine computes over 40 standardised financial metrics — from gross margin and working capital to customer acquisition cost and cohort revenue trends. Every metric is benchmarked against industry-specific baselines across 63 classification codes.
- Gross margin, EBITDA, operating leverage ratios
- Working capital and cash conversion cycle
- Revenue segmentation by channel, product, and customer
- Cost structure analysis and variance detection
- Sector-specific benchmarks (63 industry classifications)
- Rolling 12-month trend analysis with anomaly flags
AI Intelligence Engine
Synthesis, narrative, recommendation.
The AI layer has agentic functions — it actively queries your database for context-aware financial answers and surfaces patterns across metrics that don't usually appear in the same conversation. It uses FinBERT for transaction categorisation and sentiment analysis across your business data.
- Agentic AI that actively queries your data, not just chat
- FinBERT-powered transaction categorisation and sentiment
- IsolationForest anomaly detection for spending and invoice gaps
- Cross-metric pattern recognition and correlation analysis
- Natural language synthesis of financial performance
- Conversational follow-up on any insight or metric
Forecasting Engine
Forward-looking. Stress-tested.
Deterministic forecasting mixed with XGBoost machine learning projects your KPIs and calculates your exact cash runway. Stress-test plans across multiple scenarios before you commit — and understand your range of outcomes, not just a single base case.
- XGBoost ML model for KPI and revenue projection
- Deterministic 13-week and 12-month cash flow forecasting
- Multi-scenario modelling (base, optimistic, stress)
- Exact cash runway calculations with burn rate assumptions
- Seasonal adjustment and growth trajectory analysis
- Break-even analysis and scenario comparison
Integrations
Connected by default
Platform Specs
Technical overview
Go Deeper
Read the technical white paper
The full architecture document covers our data model, AI methodology, benchmark construction, and the technical rationale behind every design decision.