The final technical webinar of the Agentforce League 2026 brought together industry context and platform innovation in a powerful way. The session focused on how Manufacturing Cloud and Data Cloud (now branded as Data 360) work together to deliver a unified, intelligent, and actionable view of manufacturing data. Through concepts, features, and live demos, the speakers showcased how structured and unstructured data can be transformed into real business value.
Manufacturing Cloud: From Build-and-Sell to Lifecycle Relationships
The session began with a high-level overview of Manufacturing Cloud, positioning it as more than just a sales tool. Modern manufacturers no longer stop at producing and selling products – they manage the entire customer and asset lifecycle. This includes contracts, delivery commitments, warranties, service, maintenance, and long-term customer value.
Key capabilities highlighted included:
- Sales Agreements
- Track long-term commitments such as planned vs. actual quantities shipped
- Support monthly and yearly forecasting
- Enable renewals and compliance checks through automation and agents
- Asset Lifecycle Management
- Maintain a 360° view of customer-owned assets
- Track milestones, warranties, service history, and asset hierarchies
- Monitor asset health using telemetry data
- Service & Field Operations
- Work orders and service appointments for installations and repairs
- Alerts and milestones tied directly to asset records
- Integration with Field Service concepts for technician visits
Manufacturing Cloud was presented as a layered solution built on core Salesforce objects, extended with industry-specific data models, processes, and templates.
Data Cloud (Data 360)
The core of the session focused on Data Cloud, now referred to as Data 360, and its role in unifying data across systems. Data 360 enables manufacturers to bring together information from CRM systems, ERP platforms, IoT devices, documents, and external sources into a single, governed data layer.
At a high level, the data processing flow includes:
- Data Ingestion
- Connectors for Salesforce CRM, APIs, cloud storage, and enterprise systems
- Ingestion API for streaming telemetry and event-based data
- Harmonization & Unification
- Map raw data into standard or custom Data Model Objects (DMOs)
- Resolve duplicates and unify records where required
- Activation
- Use processed data in flows, analytics, Agentforce, and automations
- Trigger actions based on calculated insights
What’s New in Data Cloud
A major highlight of the session was how Data Cloud now supports both structured and unstructured data, significantly expanding its capabilities.
New and Enhanced Features Covered
- Ingestion API
- Stream real-time telemetry data from machines and devices
- Designed for high-volume, asynchronous data ingestion
- Intelligent Context
- Automatically enrich prompts with relevant structured and unstructured data
- Reduce manual prompt engineering by adding context behind the scenes
- Document AI
- Extract structured data from unstructured documents like PDFs
- Convert invoices, warranties, and manuals into usable tables and fields
Demo Highlights: From Asset Data to Proactive Action
The demo showcased a practical manufacturing scenario where asset data, real-time telemetry, and automation came together to solve a common challenge—identifying at-risk customer assets and acting before failures occur. Instead of focusing on isolated features, the walkthrough demonstrated how Manufacturing Cloud, Data Cloud, and Agentforce work together in a seamless flow.
The use case centered on customer-owned equipment that continuously sends telemetry data. This data was used to monitor asset health and automatically trigger alerts when conditions became critical, reducing the need for manual monitoring.
The demo began in Manufacturing Cloud, where assets were already set up with a complete business context. Each asset included warranty details, milestones, alerts, and asset hierarchies, giving service and operations teams a clear 360-degree view of the equipment installed at customer sites.
From there, the focus moved to Data Cloud, where telemetry data from machines was ingested using the Ingestion API. The raw data was mapped to Data Model Objects, making it usable alongside CRM data. Once the data was in place, Calculated Insights were created to continuously evaluate asset conditions and flag assets that entered a critical state.
To ensure insights led to action, Data Cloud–triggered Flows were used. When an asset’s health dropped below a defined threshold, the system automatically created alerts and prepared follow-up actions for service teams—without any manual intervention.
The demo concluded with Agentforce, where users could ask natural-language questions like “Which assets are critical?” and instantly get answers based on live Data Cloud insights.
Key features shown in the demo:
- Manufacturing Cloud asset management
- Data Cloud ingestion using APIs
- Data Model Objects and Calculated Insights
- Automated flows triggered by insights
- Agentforce for conversational access to data
Overall, the demo clearly illustrated how manufacturers can move from reactive support to proactive, data-driven service using Salesforce’s industry and data capabilities.
Resources and Helpful Links
Author: Tejas Jain
