AI Chatbot for Data Analysis
Ask business questions in plain language and receive KPI answers, charts, explanations, and suggested follow-up questions.
AI Analytics Services
We design analytics platforms, predictive models, dashboards, and governed data pipelines that help leaders see what is happening, why it is happening, and what to do next.
Analytics and decision intelligence stack
Power BI
BI
Tableau
Dashboards
Snowflake
Warehouse
Databricks
Lakehouse
Microsoft Fabric
Data Platform
Python
Analytics
TensorFlow
Predictive AI
AWS
Cloud
Azure
Cloud
Google Cloud
Cloud
Data Factory
Pipelines
Kafka
Streaming
Patient flow, clinical operations, diagnostics analytics, and resource planning.
Risk signals, portfolio visibility, fraud patterns, and cash-flow intelligence.
Quality analytics, OEE, predictive maintenance, and plant performance dashboards.
AI Analytics Agent
We build AI analytics chatbots that connect to Power BI, MCP tools, governed datasets, and enterprise sources so users can ask questions, get visual answers, and move from analysis to action. Copilot works like a charm when the semantic layer, tools, and guardrails are designed properly.
Ask business questions in plain language and receive KPI answers, charts, explanations, and suggested follow-up questions.
Connect the chatbot to trusted Power BI datasets, measures, reports, and governed business definitions.
Use MCP-style connectors to securely query warehouses, databases, files, APIs, and BI systems through controlled tools.
Use Claude to interpret questions, select the right tools, compare metrics, summarize patterns, and explain drivers.
Design guided topics, actions, approval paths, handoffs, and Teams-ready conversational analytics workflows.
Deliver a familiar Copilot interface where business users can ask, refine, visualize, and act on data.
Generate variance explanations, anomaly alerts, executive summaries, and recommended next questions automatically.
Respect Power BI permissions, row-level security, audit logs, source boundaries, and sensitive data rules.
Natural Language Analytics
Ask
questions in natural language instead of building every report manually
MCP
controlled tools for querying trusted analytics sources
PBI
Power BI datasets and semantic models become conversational
Copilot
familiar interface for insight, charts, and business action
How It Works
The user asks a question. The agent understands intent, routes the request through approved MCP tools, queries Power BI or source systems, reasons with Claude, and returns an answer with context, chart suggestions, and follow-up prompts.
A user asks: "Why did West region margin drop last month?" in Copilot, Teams, or a web chatbot.
The agent selects approved MCP tools, Power BI datasets, SQL sources, and business definitions.
Claude compares measures, checks context, identifies drivers, and prepares a grounded explanation.
The user receives a clear answer with charts, filters, citations, and suggested next questions.
Show revenue variance by product and explain the top three drivers.
Claude selects the Power BI semantic model, applies filters, and compares measures.
Copilot returns a chart, explanation, and next steps for sales, finance, or operations.
Use Cases
Patient flow, clinical operations, diagnostics analytics, and resource planning.
Risk signals, portfolio visibility, fraud patterns, and cash-flow intelligence.
Quality analytics, OEE, predictive maintenance, and plant performance dashboards.
Demand forecasting, pricing intelligence, customer behavior, and SKU performance.
Learning analytics, cohort performance, research reporting, and institutional insights.
Inventory movement, supplier performance, delivery efficiency, and exception alerts.
Example Questions
The analytics chatbot becomes a trusted teammate: it can explain KPIs, compare segments, summarize reports, and recommend the next question without exposing data outside approved access paths.
Delivery Flow
We keep the process practical: define trusted questions, connect approved data tools, design Copilot conversations, validate answer quality, then launch into daily workflows.
Step 1
Map the real questions teams ask, the KPIs they trust, the Power BI datasets they use, and the decisions they need to make.
Step 2
Connect Power BI semantic models, SQL sources, files, APIs, and MCP tools with permissions, descriptions, and safe query boundaries.
Step 3
Design prompts, tool routing, Copilot Studio topics, answer formats, chart generation, and follow-up question behavior.
Step 4
Test answer accuracy, measure definitions, row-level security, source citations, hallucination controls, and escalation rules.
Step 5
Deploy into Copilot, Teams, portals, or BI workflows, then monitor usage, unresolved questions, feedback, and insight quality.
Power BI
Semantic BI
Claude
Reasoning
Copilot Studio
Agent Builder
Microsoft Copilot
User Interface
MCP
Tool Access
Microsoft Fabric
Data Platform
SQL
Query Layer
Snowflake
Warehouse
Databricks
Lakehouse
SharePoint
Documents
Teams
Channel
Excel
Business Data
The chatbot must respect the same controls as your reports: row-level security, approved measures, audit logs, source boundaries, and permission-aware answers.
Ask Your Data
Let AIMatica design the MCP-powered analytics agent that lets your team ask questions, get trusted answers, and act faster from the tools they already use.
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