Triggers and connections
We define what starts the flow and which systems provide information, connecting APIs, files or events according to need.
- Workflow map
- Service connections
Keep work flowing.Give your team time.
We design workflows that connect your services, understand the data and take the right next step. Let’s run one together.
Let’s talk about your workflowAI Workflow Studio
Customer experience / Sample workflow
3 parallel services
3 connected outputs
When a zoom control is focused, use the arrow keys to pan the canvas.
Uses sample services and prepared AI outputs. No real connections, model calls or messages are sent.
Different systems. One shared purpose.
AI-Powered Workflow Automation
Turn repeated work into traceable workflows.
We develop automation as a workflow across systems. Triggers, service connections, AI processing and human approval are designed as parts of the same process.
For tasks such as creating records from documents or routing requests, rules handle predictable steps while AI is considered where interpretation is needed.
What we deliver
Every step has an input, a job and a result.
AI and rules
We combine classification, extraction or drafting with business rules, validating outputs before subsequent steps.
- Processing steps
- Validation rules
Approval and tracking
We add approval where needed, making stalled work and recoverable steps visible.
- Approval points
- Processing and error tracking
The work in context
Turn an incoming document into a reviewed record.
In the example, a document is received, information extracted, checked against existing records and sent to the destination after approval. Users can follow how the result was produced.
- An explicit workflow
- Steps proceed using validated outputs from previous steps.
- A point of intervention
- The state of work is clear when approval is needed or a failure occurs.
How we work together
Understand the work and run it with control.
Deliverables and the working plan are defined around the needs of your project.
Analyze the process
We clarify how the work begins, which data it uses, repeated steps and the points that require a decision.
OutputAutomation scopeDesign the workflow
We define which steps use rules, which use AI and which require user approval. Service connections and responsibilities are defined within the same flow.
OutputAutomation and decision flowBuild and validate
We develop the workflow using real scenarios and test errors, missing data and retries alongside successful operations.
OutputValidated automationMonitor and manage
We make the status of running workflows, errors and points requiring intervention visible. Permissions and manual takeover steps are included in the operations plan.
OutputOperations plan
Engineering in the details
Automation should remain understandable when it fails.
Duplicate actions
We account for tasks where retries must not repeat an action.
Human approval
Approval points follow the impact of decisions and actions.
Observability
Step results, reasons for waiting and errors remain traceable within the workflow.
Common questions
Let's start with your questions.
Does every step need AI?
No. Conventional automation may be more suitable for deterministic rules. AI is considered for tasks such as interpreting text or classification.
What happens when a workflow stops?
The failure determines whether to retry, intervene or cancel. Recovery is designed to avoid unnecessarily repeating completed work or creating inconsistent records.
Can we use our existing tools?
We review API, export and access options. Suitable connections can support automation across existing tools without replacing every system.
Let’s look at the work your team repeats.
Share the input, the services involved and the record you want at the end.