Update welcome.md

docs/get-started/welcome.md

@@ -1,27 +1,47 @@
 ---
 title: Welcome
-description: Welcome to the Quix Developer documentation. This documentation includes guides, tutorials, and API references for using Quix Cloud, Quix Streams, and Quix Bring Your Own Cluster (BYOC).
+description: Welcome to the Quix documentation. Quix lets you consolidate sensor data, configurations, and test metadata from your test rigs and simulations in a single platform. Process data in real-time or replay historical runs to accelerate R&D.
 ---
 
 # Welcome
 
-<p>Quix is a telemetry analytics platform that enables you to consolidate high frequency sensor data in a centralized cloud data store, for use cases like real-time monitoring and analytics, predictive maintenance, digital twins, and more. Quix provides the ability to connect, transform and process data in batch or real-time architectures and between legacy and modern systems in any language using easily customisable connectors.</p>
+Quix is a data platform for consolidating measurement data, configuration metadata, and test parameters from test rigs, simulations, and sensors. The platform handles high-frequency telemetry data in real-time and provides the ability to replay historical runs for analysis and debugging.
 
-## Workflow summary
+This documentation includes guides, tutorials, and API references for Quix Cloud, Quix Streams (the open-source Python library), and Bring Your Own Cluster (BYOC) deployment options.
 
-Your Quix workflow:
+## Quix Features
 
-1. Develop your applications locally in Python with Quix Streams, the Quix CLI, and your IDE of choice.
-2. Test and debug your pipeline locally with the Quix CLI and Docker.
-3. Deploy to Quix Cloud for scalability and observability.
+**Data consolidation**: Connect sensors, data acquisition systems, MATLAB/Simulink outputs, and legacy instruments through pre-built connectors or custom Python code. All data streams to a centralized data store. 
+
+* [Learn about data integration →](../develop/integrate-data/overview.md)
+
+**Configuration and measurement linkage**: Store test configurations alongside sensor measurements. Query by test parameters to find specific runs, or trace measurement anomalies back to their exact test setup.
+
+* [Learn about dynamic configuration →](../quix-cloud/managed-services/dynamic-configuration.md)
+
+**Real-time processing and historical replay**: Process live telemetry as it arrives, then replay historical data later to investigate issues or validate changes without re-running physical tests. 
+
+* [Learn about replay →](../quix-cloud/managed-services/replay.md)
+
+**Python-based pipeline development**: Use Quix Streams to build data processing pipelines in Python. Develop and test locally, then deploy to managed infrastructure without requiring Kafka or DevOps expertise.
+
+* [Get started with Quix Streams →](../quix-streams/quickstart.md)
+
+## Typical Workflow
+
+1. **Develop locally**: Build Python data processing pipelines with Quix Streams, your IDE, and the Quix CLI. Test with Docker before deployment.
+
+2. **Debug with replay**: Replay historical test runs locally to reproduce issues or validate fixes.
+
+3. **Deploy to production**: Push pipelines to Quix Cloud for managed infrastructure, monitoring, and data persistence. Alternatively, use BYOC to run on your own Kafka cluster.
 
 <div class="grid cards" markdown>
 
-- __Get started!__
+- __Get started__
 
     ---
 
-    Start building your stream processing pipeline locally on the command line with Quix Streams.
+    Install Quix Streams and build your first data processing pipeline.
 
     [Install Quix Streams :octicons-arrow-right-24:](../quix-streams/quickstart.md)