AI & Data Analytics
Turn the data already sitting in your ERP, CRM, and operational systems into forecasts, dashboards, and applied AI features people actually use.
From scattered data to decisions
Most organizations don't have a data shortage — they have a data-access problem. Data lives across the ERP, the CRM, spreadsheets, and a handful of point systems, and nobody trusts a number without checking three places first.
We build the data pipelines, models, and dashboards that turn that mess into something a finance lead or operations manager can act on the same day, and layer applied AI — forecasting, anomaly detection, document extraction, copilots — on top once the foundation is solid.
- Data pipeline design pulling from ERP, CRM, and operational systems
- BI dashboards in Power BI or a custom analytics front end
- Forecasting and anomaly detection models for demand, inventory, or finance
- Applied generative AI: document extraction, copilots, and internal chat assistants
What's included
Data Pipeline & Warehouse
Consolidate ERP, CRM, and operational data into a single, query-ready warehouse.
BI Dashboards
Executive and operational dashboards that answer real questions, not vanity metrics.
Forecasting Models
Demand, inventory, and cash-flow forecasting models trained on your own historical data.
Document AI
Extraction models that turn invoices, purchase orders, and forms into structured data.
Copilots & Assistants
Internal AI assistants grounded in your own documentation and data, not generic web knowledge.
Governance & Access Control
Row-level security and audit logging so analytics respects who should see what.
Why build analytics with DADynamics
We've built the ERP and integration layers this data comes from, so the analytics we build on top understands the source systems, not just the export files.
- Pipelines built against your actual ERP/CRM schema, not a generic connector
- Dashboards designed with the people who'll use them daily, not just IT
- Models validated against a holdout period before anyone relies on them
- Clear documentation on what a model does and doesn't account for
How we get there
A structured path from discovery to a supported go-live.
- 01
Audit
Map where the data lives today and where the gaps and trust issues are.
- 02
Pipeline
Build the ingestion and transformation layer feeding a central warehouse.
- 03
Model & Visualize
Build dashboards, forecasting models, or applied AI features in iterations.
- 04
Adopt
Train teams, gather feedback, and refine before wider rollout.
Where this fits
Executive Dashboard Consolidation
Replacing a dozen manually maintained spreadsheets with one governed, always-current dashboard.
Demand Forecasting
Retail and distribution businesses reducing stockouts and overstock with a trained forecasting model.
Invoice & Document Automation
Finance teams cutting manual data entry with document extraction feeding directly into the ERP.