Shared agentsCase Management
Automation, orchestration, and human decision-making combined, to adapt to unpredictable tasks and decisions over the life of a case.
- Case & Process Management
//Hyperautomation
Smarter end-to-endautomation.
AI, BPM, low-code, RPA and process mining together, automating complex business processes end-to-end.
Discover
Find what to automate
Process and task mining show where work stalls and what to automate first.
Connected
Break down silos
Information and process silos replaced by connected, dynamic workflows.
Optimize
Continuous improvement
Performance metrics and feedback loops refine automation over time.
//Overview
What is hyperautomation?
Hyperautomation is the coordinated use of AI, business process management, low-code, robotic process automation and process mining to automate complex business processes end to end, rather than one task at a time.
DataObserve Flow brings the five elements together (process discovery, integration, orchestration, intelligence and monitoring) on an open, best-of-breed platform with no vendor lock-in, so you choose the technologies and keep the process.
//How hyperautomation works
Five elements ofhyperautomation.
Step 1
Process discovery
Mining finds inefficiencies, bottlenecks, and opportunities.
//Hyperautomation with DataObserve Flow
Choose the technologies, keep the process
Best-of-breed
The right technology for each use case, integrated.
No vendor lock-in
AI, RPA and more via API or connectors.
Process orchestration
Complex end-to-end workflows across systems.
Scalability
Growing workloads without losing performance.
Low-code development
Business users build and change applications.
//Explore more withDataObserve
More from Flow · Case & Process Management
Process Orchestration
Encode and enforce the end-to-end process, so the business can evolve fast at minimal cost, with long-running automations for routine and exception-driven work.
- Case & Process Management
Business Orchestration & Automation (BOAT)
Automation tools too often work in isolation.
- Case & Process Management
Artificial Intelligence
AI runs inside business processes governed by an orchestration layer, which decides when an AI task runs, what data it sees, and where a person reviews the result.
- AI & Intelligent Platforms
//The challenges
What to plan for
Complexity in integration
Many systems take careful planning to connect without disruption.
New technology adoption
Skills, data, and systems need to be ready.
Monitoring and maintenance
Ongoing care keeps the benefits.
//FAQs
Hyperautomation: questions teams ask
What technologies make up hyperautomation?
Typically AI and machine learning, BPM, low-code development, RPA, process mining and integration platforms, orchestrated together.
What is process mining?
Process mining analyses event logs from business systems to show how processes really run, revealing bottlenecks and automation candidates.
Do I need to replace my existing tools?
No. DataObserve Flow orchestrates the tools you already have, such as RPA bots and integration platforms, alongside new ones.
What are the main challenges of hyperautomation?
Connecting many systems without disruption, readying skills and data for new technology, and maintaining automations over time.
