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Overview

AskSenseOps is SenseOps' conversational AI product that enables business users and developers to interact with enterprise data using natural language.

It provides a unified conversational interface across BI applications, databases, and enterprise documents. Users can ask questions, explore insights, and retrieve answers grounded in live query results or cited documents.

AskSenseOps does not include an AI model of its own. It runs on a server where the data sources are available and acts as a bridge between those sources and the language models selected by the organisation. This allows organisations to choose their preferred models and manage their usage.

Ways to Use AskSenseOps

AskSenseOps can be used in three ways. They all connect to the same AskSenseOps server, so you can start with one and add the others later.

Variant What it is Best for Set up with
Web The AskSenseOps portal in a browser, with chat, saved dashboards and administration settings. Business users and developers who want a dedicated place to chat with their data, and administrators who manage models, sources and users. Web Server Installation
Extension An AskSenseOps extension that runs inside your Qlik Sense apps. Users who want to ask questions without leaving Qlik Sense. Extension Installation
MCP connector AskSenseOps added as a connector to an LLM tool users already work in, such as Microsoft 365 Copilot, Claude or any other MCP-compatible client. Teams that want their existing AI assistant to answer from governed enterprise data. MCP Integration Setup

In Microsoft 365 Copilot, users can ask questions, add charts to Qlik apps and build dashboards. To see how the pieces connect, see Architecture.

Supported Sources

Connect the sources you need and select the datasets users can ask about.

Source Configuration
Qlik Sense Enterprise QlikSense Enterprise Configuration
Qlik Cloud Qlik Cloud Configuration
Power BI Power BI Configuration
Databases Database Configuration
Enterprise documents Document Source Configuration

Supported Models

AskSenseOps works with the language models that fit your organization's policy, including cloud, local, offline and self-hosted options. Configuration guides are available for:

  • Azure OpenAI and OpenAI
  • Anthropic (Claude)
  • Google Gemini and GCP Vertex AI
  • AWS Bedrock
  • Mistral AI, Cohere, Groq, Together AI and Fireworks AI
  • Ollama, vLLM and Hugging Face (TGI) for local and self-hosted models
  • GitHub Models
  • Any custom OpenAI-compatible model

You can configure several models and switch between them for different use cases.

Key Features

1. Conversational Data Access

  • Ask questions about enterprise data using natural language.
  • Retrieve information from connected BI platforms, databases, and enterprise documents.
  • Get answers grounded in live query results or cited documents.
  • Explore data using Lite and Deep conversation modes.

2. AI Model Configuration

  • Configure models from multiple cloud and self-hosted providers.
  • Use different models for different use cases.
  • Monitor LLM usage through built-in usage counters.

3. Dashboards and Workflows

  • Create and save dashboards from conversations.
  • Share dashboards with other users.
  • Refresh dashboards and schedule email delivery.
  • Configure scheduled or rule-based workflows.
  • Trigger notifications and supported actions through configured integrations.

4. Security and Administration

  • Respect existing user permissions when accessing connected data.
  • Support Qlik streams, spaces, Section Access, and row-level security.
  • Manage users, roles, connections, and model configurations.
  • Configure metadata and business terminology for connected data.

5. External AI Client Integration

  • Connect AskSenseOps to compatible MCP clients, including Microsoft 365 Copilot, Claude, and ChatGPT.
  • Access connected enterprise data and supported AskSenseOps tools through external AI clients.

Getting Started

  1. Review the Prerequisites.
  2. Install the web server, then add the extension or MCP connector if you need them.
  3. Connect your sources and models using the configuration guides.
  4. Start asking questions in Chat or build a Dashboard.

For common questions, see FAQ & Troubleshooting.