Workflow automation
Nexus Workflow Automation
Design event-driven and long-running workflows that combine systems, rules, code, AI, infrastructure and human decisions in one observable execution.
A published workflow
Draft and published revisions are separate, so a workflow can be improved while the live version keeps running.
- integration actions
- 1,480+integration actions
- event sources
- 46event sources
- runtime language families
- 8runtime language families
- capable execution
- Air-gappedcapable execution
Why it matters
What changes when the whole process is automated.
Automating a task saves minutes. Automating the process, including the parts that usually fall out of it, changes how the operation runs.
Automate beyond isolated tasks
A single automated task rarely removes the work. Nexus automates the sequence: the retrieval, the checks, the interpretation, the decision and the write-back.
Keep exceptions inside the process
Unusual cases are routed, enriched and reviewed within the same workflow instead of dropping into an inbox where progress becomes invisible.
Reduce handoffs between platforms
Integration, logic, AI and approval run in one execution, so there is no orchestration between an integration tool, a script host and a ticket queue.
Preserve accountability
Approvals, decisions and reasons are recorded with the run, which keeps a named person responsible for consequential outcomes.
Reuse shared logic
Modules, functions, forms and connector actions let one team's proven work become another team's building block.
Operate in restricted environments
The same workflows run on-premises, in sovereign cloud and in fully air-gapped networks, with no dependency on external services.
Design surface
Build the process on a graph, not in a script.
Workflows are assembled from a node palette onto a canvas, with each node configured in its own panel and connected through explicit inputs and outputs.
Node palette
Triggers
- Webhook
- Schedule
- Event bus
Actions
- Connector
- HTTP
- Database
Logic
- Condition
- Rules + Code
- Merge
People and AI
- Approval
- Form
- AI node
- 01Webhook triggerTrigger
- 02Connector actionIntegration
- 03Rules + CodeLogic
- 04AI classificationSovereign AI
- 05Human approvalPeople
- 06System write-backAction
Configuration
- Node
- Rules + Code
- Runtime
- Selected per task
- Inputs
- From previous nodes
- Secrets
- Vault reference
- Output
- Structured, typed
- On error
- Route to exception path
Capabilities
What the workflow engine provides.
These are the building blocks available when a process is designed. Anything not listed here should be confirmed with the team rather than assumed.
Visual DAG workflows
Steps and dependencies are modeled explicitly as a directed graph.
Conditions, branches and merges
Route runs on results and bring paths back together deliberately.
Parallel steps
Independent work runs alongside itself where the process allows it.
Event-driven and scheduled
Start from an event as it happens, or on a defined schedule.
Modules and sub-workflows
Reusable graphs exposed to a parent workflow as one node.
Forms
Trigger a workflow or collect data partway through the process.
Functions
Publish capabilities that can be called on demand.
Human approvals
Pause for validation, correction, rejection or escalation.
Test, publish, revise
A draft revision is prepared and tested before it goes live.
Execution history
Review previous runs with per-node logs and results.
Workspace-scoped organization
Workflows, credentials and access are separated by workspace.
Triggers
Events connect external systems to workflows.
Across application, platform and infrastructure sources, Nexus supports 46 trigger sources. The examples below are representative.
Webhook
External systems notify Nexus as soon as something changes.
Schedule and cron
Recurring execution for periodic and batch-style work.
Event bus and message queues
Enterprise messaging infrastructure starts workflow runs.
API invocation
Applications call a workflow directly as part of their own logic.
Storage and data events
New files and record changes begin processing automatically.
Infrastructure and platform events
Operational signals start response workflows.
Operations
Designed for real operating conditions.
Processes fail, systems time out and inputs arrive in unexpected shapes. A workflow platform is judged on what happens then.
Failures are visible
When a run stops, the status shows where it stopped and which node was responsible, rather than reporting a single opaque failure for the whole process.
Per-node output is retained
The input and result of each node are available for review, which is usually enough to explain an outcome without reproducing the run from scratch.
Duration and history
Execution history records previous runs and how long they took, so operational behavior can be observed over time rather than reconstructed from anecdotes.
Rerun after resolution
Once the underlying issue is fixed, a run can be executed again rather than recreated by hand.
Draft separated from live revision
Changes are prepared and tested in a draft revision, and the published version continues to serve production traffic until the new revision is released.
Reuse
Reusable by design.
Shared components keep large automation estates consistent and reduce the cost of the next process.
Modules
A complete internal graph exposed to a parent workflow as one node.
Shared forms
One form definition used by several processes for input and mid-process data.
Functions
Capabilities published for other workflows and systems to call.
Connector actions
Configured integration steps applied consistently across teams.
Human control
People stay in the process where it matters.
Approval is a workflow node, not a separate tool. That is what keeps the decision, the reason and the resulting action in the same record.
Approval after rules or AI
A reviewer can be inserted after a deterministic result, after a model output, or both, depending on the value and sensitivity of the case.
Reason capture
Decisions are recorded with the reviewer and their reason, which builds a defensible history of how cases are actually handled.
Routing based on the decision
Approve, reject, correct, request changes or escalate. Each outcome can follow its own branch through the remainder of the workflow.
Examples
Where teams apply it.
These are illustrative process patterns across business, IT and security work, not claims about specific organizations or outcomes.
Business
Invoice and document approval
Extract values from an incoming document, validate against the purchase order, route exceptions for review and post the approved result to the ERP system.
Business
Supplier onboarding
Collect details through a form, run checks against internal and external sources, gather the required approvals and create the vendor record.
Business
Reconciliation and exception handling
Compare records across systems on a schedule, resolve differences with deterministic rules and escalate only the cases that genuinely need a person.
IT
Environment provisioning after approval
Take a request through entitlement checks and approval, then run the Kubernetes or Terraform operations and return the details to the requester.
Security
Alert enrichment and incident response
Enrich an alert with context from surrounding systems, apply deterministic triage rules and execute containment steps once approved.
AI
Controlled AI-assisted case processing
Use a self-hosted model to classify or summarize a case, present the result to a reviewer and apply the confirmed decision to the operational system.
Comparison
Why Nexus instead of task automation alone.
Task automation tools are useful and often sit alongside Nexus. The difference shows up once a process needs more than a series of application steps.
The full process, not a fragment
Retrieval, validation, interpretation, approval and write-back run as one execution, so no part of the process depends on someone noticing a queue.
Custom logic without a separate service
Organization-specific rules run as code inside the workflow, which avoids standing up a microservice with its own deployment and support burden for bounded logic.
Infrastructure in scope
Provisioning and platform operations are workflow steps, so the request, the approval and the change live in the same record.
Private AI rather than an external service
Interpretation runs on models you host, keeping documents, prompts and outputs inside your environment.
Governance as part of execution
Workspace isolation, vault-backed secrets, role-based access and execution history apply to every run rather than to a subset of steps.
Architecture session
Show us the process, including the hard parts.
The interesting part of an automation program is rarely the happy path. Bring the exceptions, the legacy interface and the approval nobody wants to own, and we will design against those first.