AI analytics and decision support takes over the recurring analysis work
This service covers predictive analytics, data insights and forecasting, automated reporting, and business intelligence. Beagle builds custom AI models around your data and connects their output to your dashboards, so a prediction sits next to the numbers it relates to.
A predictive model learns patterns from historical records and estimates what is likely to happen next. A risk score ranks items such as accounts, orders or applications by how closely they resemble past problem cases. Anomaly detection compares new data with the normal pattern and flags what does not fit.
The work it takes over is repetitive: pulling data from several systems, rebuilding the same report, scanning rows for outliers. People keep the decision. Decision support means the system puts the evidence on the dashboard your team already uses.
Where forecasting and anomaly detection fit in everyday operations
These models fit wherever a team makes the same judgment call repeatedly from existing data. Common examples follow.
- Demand forecasting: read past sales or order history, project the coming period, and show the forecast beside actuals on the dashboard.
- Cash flow forecasting: combine open invoices and payment history from the accounting system to estimate when money is likely to arrive.
- Risk scoring: score new accounts, orders or applications against past cases and route the high scores to a person for review.
- Anomaly detection on transactions: compare each new expense, payment or reading with its normal range and alert the person responsible when one falls outside it.
- Automated reporting: assemble the weekly or monthly report from the CRM, helpdesk and accounting system, and deliver it on schedule.
How Beagle builds it: from discovery call to monitored system
It starts with a free 15-minute discovery call. We map your current operations and identify the automation opportunities with the most potential. You leave with a prioritized list of AI use cases. No pitch.
Solution design takes 1 to 2 weeks. We write a modular implementation plan and define data flows, integration points, KPIs and success criteria before code is written. For an AI analytics project, the data flows and integration points describe which data sources feed each model and which dashboard shows the output. You sign off at every stage.
Build and deploy takes 2 to 6 weeks, in iterative sprints. Each workflow goes through QA before production, and Beagle handles infrastructure, security configuration and staff onboarding. The last step, optimize and evolve, is ongoing.
What you own afterward: an open, self-hosted stack and your data
Beagle builds on an open, self-hosted stack: n8n for workflows, open-source AI models, and Supabase for data. You keep full data ownership, with no vendor lock-in and no black boxes. If required, the system can be deployed inside your own cloud environment.
The architecture is modular. Adding new integrations, such as another data source, or more automations later does not require starting over.
How it is measured: KPIs agreed in design, monitored after launch
KPIs and success criteria are defined during solution design. For a forecasting model, that might be how closely forecasts track actuals. For anomaly detection, it might be how many alerts turn out to need action. The measures that apply are agreed with you for each project.
After launch, Beagle monitors each workflow against those KPIs and iterates based on real usage data. Because KPIs and success criteria are defined per project, this page quotes no targets.
How to start: a 15-minute call or a 2-minute assessment
Book the free 15-minute discovery call, or take the free AI readiness assessment: 5 questions, about 2 minutes, no sign-up, with an instant score and diagnostics.
The free AI Implementation Guide is personalized and emailed to you. It covers where you are, three quick wins for the next 30 days, a 90-day roadmap, a recommended stack and estimated impact.
Questions buyers ask
Do we need in-house data scientists or AI engineers?
No. Beagle acts as your AI team, covering strategy, build, deployment and ongoing support. We involve your IT team for access and permissions, but you do not need in-house AI experts.
Where does our data live?
On an open, self-hosted stack, with Supabase for data and n8n for workflows. You keep full data ownership, and the system can be deployed inside your own cloud environment if required.
How long until it is live?
Solution design takes 1 to 2 weeks, and build and deploy takes 2 to 6 weeks. Monitoring and iteration against the agreed KPIs continue after launch.
Can it work with the dashboards and tools we already use?
Model output is integrated into your dashboards. Integration points with your CRM, accounting system, helpdesk or other tools are defined during solution design, before code is written. The workflows that move data between those tools run on n8n.