CONNECTED TO 30+ DATA SROUCES
WHY AI AGENTS FOR DATA
Your data team shouldn't spend their time pulling reports
Most organisations have more data than they can reasonably analyse. Dashboards get built, but the real questions — why did revenue dip last Tuesday, which customers are about to churn, where is the bottleneck in this process — still require someone to sit down and dig.
AI data agents change that. Rather than waiting for a human to ask the right question at the right time, a data analytics AI agent monitors your data continuously and proactively. It answers natural language questions against your live data. It flags anomalies the moment they appear. It triggers downstream actions — a notification, a task, an update — without waiting for someone to notice.
We build AI agents for data analysis that connect to your existing data sources and work within your current reporting environment — including Power BI and Microsoft Fabric.
Deliverables
What's included in our AI data agent builds
Discovery & Data Mapping
- Identify the data sources and business questions to target
- Map data pipelines and integration points
- Define agent goals, triggers and output actions
Agent Design & Build
- Custom AI agent development
- Natural language query layer over your data
- Anomaly detection and threshold alerting
- Integration with Power BI, Fabric or existing BI stack
Testing & Validation
- Accuracy and reliability testing across data scenarios
- Prompt and response tuning
- Edge case handling and guardrails
Handoff & Support
- Team training on interacting with the agent
- Documentation and usage guides
- Ongoing support and iteration retainer available
How we work
How we build AI agents for data analysis
Discovery & Scoping
We start by understanding the data questions that matter most to your business. Which decisions are still manual? Where do your analysts spend most of their time? What would change if you had answers in seconds instead of days? We map your current data sources and define what the agent needs to do.
Design & Architecture
We design the agent architecture — the data connections, the query layer, the alerting logic, and the downstream actions. You see the full design before we write a line of code. No surprises, no scope creep.
Build & Integration
We build your data analytics AI agent and connect it to your data sources — whether that’s Power BI, Microsoft Fabric, a SQL database, your CRM, or a combination. We test accuracy across real data scenarios and tune the agent before delivery.
Training & Ongoing Iteration
We walk your team through how to interact with the agent, interpret its outputs, and know when to trust it versus investigate further. Ongoing support and iteration retainers are available for organisations that want to expand agent capability over time.
USE CASES
What AI agent data analysis looks like in practice
These are real scenarios our data analytics AI agents handle for clients:
Revenue anomaly detection
- Finance team notified within minutes of an unusual transaction pattern — not at month end.
Pipeline health monitoring
- Reps alerted to deals going cold before they're lost. No manual pipeline reviews.
Capacity and utilisation alerts
- Operations managers see utilisation gaps in real time, not in last week's report.