Stonebranch Feature
Workflow Automation and Orchestration
Powered by AI
Build intelligent, event-driven workflows that leverage AI to automate actions, streamline orchestration, and unify systems across on-premises and cloud environments—all through an essential control plane for AI orchestration that ensures visibility, governance, and control at scale.
One AI-Powered Platform
to Build Workflows for any IT Process
The Stonebranch Universal Automation Center (UAC) is a service orchestration and automation platform (SOAP). Within UAC, workflow automation enables end users to visually orchestrate automated jobs or tasks across the enterprise.
- Centrally manage workflows from a single AI-powered platform
- Orchestrate workflows that span your entire hybrid environment
- Embed AI steps to support autonomous tasks
- Integrate with any application or infrastructure
Orchestrate Every Automated Workflow
Build Workflows without Limits
- Visual workflow builder
- Drag-and-drop user experience
- Embed AI-powered tasks in workflows
- Low-code/no-code workflow creation
- Web-based access from anywhere
- Role-based security for self-service
- Easily add integrations to any application or infrastructure
- Use Event-based triggers to run workflows in real-time
Design Powerful Workflows for any IT Use Case
Workload Automation
Orchestrate cross-platform jobs and processes from a single centralized solution.
Cloud Automation
Extend and run automated workflows in public cloud and multi-cloud environments.
DevOps
Unite IT Ops and developers with jobs-as-code and CI/CD toolchain automation.
Data Pipeline
Coordinate your end-to-end data pipeline - from data collection to loading to distributing analytics.
IT Service Management
Open tickets and resolve issues back and forth between your ITSM solution and any other application.
Managed File Transfer
Automate enterprise MFT internally, between partners, and between on-prem and the cloud.
AI Workflow Automation
Put AI Inside Your Workflows — Keep Humans in Control
Embed AI tasks directly into workflows, moving from rigid, rule-based automation to adaptive, intelligent systems that can handle unstructured data and make decisions with minimal human intervention.
Essential Control Plane for AI Orchestration
- Interpret, summarize, and route work with AI
- Enforce approvals, RBAC, and confidence gates with UAC
- Build hybrid deterministic and probabilistic workflows
- Integrate enterprise-grade LLMs through AWS, Azure, and Google Cloud
Integration Hub
Explore Over 150 Integrations
Connect with any platform or application — from the Mainframe to the cloud
- Integrate UAC with any platform or application
- Connect AI services like Claude, ChatGPT, Gemini, and more
- Drag and drop integrations directly into your workflow
AI Use Cases
Practical Ways to Use AI in Workflows
Put AI to work across your workflows—automating decisions, reducing friction, and accelerating outcomes.
Alert and Log Summarization
Embed LLM steps into incident workflows to automatically summarize logs and output clear, concise explanations.
Human-in-the-Loop
Combine AI insights with human judgment to validate and control decisions in real time.
Unstructured Data Parsing
Process emails, invoices, and chat messages to extract and structure data that can be used in downstream workflows.
Code Generation & Execution
Dynamically generate and run code to offload token-heavy LLM tasks to deterministic automation.
AI Task Governance & Guardrails
Three Layers. One Trusted Execution Model.
Every AI task invocation flows through three distinct control layers - each with a
specific governance role that cannot be overridden by the layer beneath it.
Defines what the LLM is allowed to do, how it should respond, and what constraints it must respect. Think of it as the standing instructions for every invocation.
- Can be authored inline as a text field directly on the task definition.
- Can be sourced from the UAC System Prompt Library, where system prompts are permission-protected and cannot be modified by standard users.
- In extension LLM tasks, the system prompt lives inside the extension definition itself, capturing all context and instructions at the point of authorship.
Carries the actual payload for each execution — variables, file content, structured text, or any combination. This is the dynamic, per-run data the model works with.
- Accepts workflow variables, file references, or free-form text.
- Scoped to the executing user's permissions – what they can see in the workflow is what they can pass to the model.
- Does not override system level constraints defined in the system prompt.
Tell the LLM how to structure the response. The model fills a defined template rather than composing freely. Outputs are machine-readable and workflow-ready.
- Eliminates ambiguous or free-form responses that downstream automation can't reliably parse.
- Keeps outputs machine-readable and workflow-ready without post-processing.
- Specify and validate required fields, data types, and structure: { jobName, failureTime, errorCode, suggestedAction }.
Additional Core Pillars of Universal Automation Center:
Learn more about Stonebranch’s service orchestration and automation platform (SOAP) capabilities by exploring UAC’s core pillars.
Self-Service Automation
Empower end users, developers, and business users with citizen automator capabilities.
Infrastructure Service Automation
Manage both on-prem, and cloud-based computer, network, and storage resources.
Manage Data Pipelines
Automate file transfers and orchestrate the ingestion and processing of multiple data streams.
Analytics and Observability
Enable advanced reporting and predictive capabilities in support of improving SLAs.
Event-Driven Automation
Use event-based triggers to create modern workflows that execute in real-time.