AI & Intelligent Systemson the data your business already trusts.
AI on structured data, GenAI/RAG, agentic AI & intelligent automation — deployed directly inside your Azure tenant with full audit trails and citations on every output.
Real Intelligence requires accurate foundations.
Most AI vendors point you at a chatbot and say 'upload your documents'. We deploy AI directly on your governed ERP and finance data with full audit trails and source citations. The CFO can trust the answer because the AI shows exactly where it came from.
Sound familiar?
- Variance analysis consumes days of manual effort every month-end
- Fraud and anomalies are discovered weeks after they occur
- ERP data is locked behind static reports — not conversational
- Reconciliations require a full team and still contain errors
- Documents and contracts cannot be searched with intelligence
- AI initiatives stall because the underlying data is not trusted
What is included
- AI readiness and data quality assessment
- Governed data foundation on Microsoft Fabric
- AI model build — forecasting, anomaly detection, classification
- Enterprise RAG knowledge base and retrieval pipeline
- Private AI assistant deployed within your Azure tenant
- Agentic workflow automation and orchestration
- Executive AI insights dashboard
- Full audit trail on every AI decision and output
- Continuous model monitoring and retraining
- Stakeholder training and operational handover
The full AI & Intelligent Systems suite
Each capability is deployable standalone or as part of a fully integrated AI estate built on your governed data foundation.
AI on ERP & Finance Systems [cite: 46]
AI over Dynamics 365, SAP & NetSuite — forecasting and financial intelligence. [cite: 46]
- AI-powered financial forecasting on GL, AP, AR, and cashflow [cite: 46]
- Automated variance analysis with ML-driven explanation [cite: 46]
- Revenue recognition anomaly detection and exception flagging [cite: 46]
- Working capital optimisation using predictive cashflow modelling [cite: 46]
- Explainable AI outputs aligned to CFO and auditor requirements [cite: 46]
AI Financial Reconciliation [cite: 47]
Automated matching, exception flagging, and month-end acceleration. [cite: 47]
- Bank statement to ledger reconciliation using ML matching [cite: 47]
- Intercompany reconciliation automation across group entities [cite: 47]
- Exception queue — unmatched items surfaced with context for review [cite: 47]
- Pattern learning from historical matches to improve accuracy [cite: 47]
- Audit trail for every automated match and exception decision [cite: 47]
Enterprise RAG Implementation [cite: 48]
AI over documents, SharePoint & SQL using Azure AI Search. [cite: 48]
- RAG architecture design — chunking, embedding, and retrieval pipeline [cite: 48]
- Azure AI Search with vector, keyword, and hybrid search configuration [cite: 48]
- Document ingestion from PDF, Word, SharePoint, and Blob Storage [cite: 48]
- Grounding and citation — every AI answer linked to source document [cite: 48]
- Evaluation framework — retrieval precision and hallucination rate [cite: 48]
Private Enterprise AI Assistant [cite: 49]
Internal ChatGPT on your own data — secure, governed & compliant. [cite: 49]
- Azure OpenAI private deployment within your tenant [cite: 49]
- Multi-source knowledge base — SharePoint, SQL, and document libraries [cite: 49]
- Role-based access ensuring users only see authorised data [cite: 49]
- Teams and web app chat interface deployment [cite: 49]
- Content filtering, prompt injection protection, and responsible AI controls [cite: 49]
AI Anomaly Detection [cite: 50]
Fraud, outlier, and exception detection on transactional and operational data. [cite: 50]
- Statistical and ML anomaly detection on financial transactions [cite: 50]
- Fraud detection in procurement, expenses, and payments [cite: 50]
- Inventory and supply chain anomaly alerting [cite: 50]
- Real-time alerting via Teams, email, and Power BI [cite: 50]
- False positive reduction via supervised feedback loops [cite: 50]
Agentic AI & Automation [cite: 51]
AI agents for finance, workflow orchestration, and decision automation. [cite: 51]
- Finance and approval workflow AI agents [cite: 51]
- AI operational copilot — natural language to SQL over ERP data [cite: 51]
- Document AI with OCR, extraction, and classification automation [cite: 51]
- Agentic process orchestration — scheduling, routing, and escalation [cite: 51]
- Agentic AI for construction: BOQ tracking and cost variance AI [cite: 51]
Distribution Group — AI Financial Intelligence
A distribution group running 3 ERPs on AUD $300M revenue deployed AI across Dynamics 365 and finance data. The CFO now asks "why did margins drop in QLD last week?" in natural language and receives cited answers — traced to source records — in seconds.
Who this is for
Industries Served [cite: 11]
Target Buyers
Delivery Timeline
Per AI capability — standalone or as a combined programme
Deployment Model
AI runs entirely inside your Azure tenant — your data never leaves your environment.
Ready to put AI on your governed enterprise data?
Book a 30-minute conversation. We will look at your current data setup, identify the right AI entry point, and outline what an engagement would look like — at no cost and no commitment.
Book a 30-minute conversation→