Design, compose, simulate and validate agentic processes with your existing AI stack. Align business and IT around a tested process before committing to development.
Works with what you already run. Your agents, tools and data stay where they are.
An AI use case starts with business requirements. IT builds the application, technical testing follows, and only then do business users judge the result. That is where missing steps, misunderstood requirements and unexpected agent behaviour tend to surface. Each gap can trigger another cycle of clarification, development, integration and testing.
The impact is more than delay: every additional cycle consumes scarce business, engineering, architecture and testing capacity, often after much of the expensive technical work has already been completed. For example, a missing approval step or incorrectly routed exception discovered during acceptance testing can require changes to the workflow, agent instructions, integrations, test scenarios and governance evidence. The problem is not that the issue cannot be fixed. The problem is when it is discovered.
Explore how the process behaves while changes are still design decisions. Design the process, simulate realistic scenarios, test exceptions and let business users review the expected behaviour before significant engineering effort is committed. Development then starts from a process that has already been challenged by the business, with clearer requirements, understood exceptions and concrete acceptance criteria.
Validate the process before committing expensive engineering capacity. Technical, security, integration and final acceptance testing still complete the path to production; the difference is that fundamental process issues can be discovered before they become expensive implementation changes.
Orqentra Studio is the design and validation layer for agentic business processes.
It sits above the AI capabilities your organisation already owns: agents, tools, data and knowledge services, and the runtime that executes them. Studio complements your development and runtime platforms rather than replacing them.
01Design
Map business steps, agent responsibilities, data needs, decision points and human approvals.
The example throughout: a stock replenishment process. A test persona, Jordan, asks which products need to be reordered.
02Compose
Bring in the agents, tools and data services your organisation already runs, and map what each step sends and returns.
03Simulate
Explore realistic scenarios with synthetic personas, controlled data and approved capabilities. Follow a request from intent to outcome, including the routes you did not expect.
04Validate
Review outcomes against business requirements, resolve gaps and agree on the intended behaviour.
Agree on how the process should behave before developers build it.
Rehearse against a mix of synthetic responses and real capabilities, reached through connections your platform team configures once. Anything you are not ready to execute stays synthetic.
Routes through the integration layer to your inventory database, read only.
Routes to a synthetic fixture inside the Studio. No real system is called.
Routes to a synthetic fixture inside the Studio. No real system is called.
Illustrative process with synthetic data. Business teams refine and test designs without waiting for an application to be rebuilt each iteration.
Make permissions part of the process. Limit agents to approved capabilities, bring in human approval for write actions, and test against controlled data before anything reaches a real system.
Human approval required
The Create reorder step wants to write to the Purchasing API. The write stops at the permission boundary until a person approves it.
Orqentra Studio composes what you already own. It is where process intent becomes visible, testable and validated.
The benefits the approach is intended to produce. What you gain depends on your processes and your teams.
Resolve differences between business expectations and process behaviour before implementation.
Identify missing steps and exceptions while the process is still inexpensive to change.
Focus business, engineering, architecture and testing resources on a process that has already been validated.
Carry concrete scenarios and expected outcomes into development and testing.
Inside the Studio
From a first sketch to a design your builders can rely on, without touching a live system. Every example comes from one process: a customer who wants to change their mortgage.
Connect the agents, tools and data you already run. Import only what a process may use; your own people approve it, and Live needs approvals.
Examplecapabilities.bank.example/mcp → discover → approve lookup_mortgage (read)
Map business steps, agents, data sources and human approvals on one canvas.
ExampleChange requested → Clarify customer request → Assess eligibility → Advisor approval → Apply approved change
Run the whole process end to end on synthetic data and follow every step: what it received, what it returned, where it waits for a person.
ExampleAssess eligibility (synthetic) → Advisor approval waits → Approve & continue → Change confirmed
Validate checks the design and, where the fix is clear, offers it as a button.
Example“Mortgage policy is not reachable from Start.” → Reverse that arrow
Write down what a conversation agent must ask, collect, hand over and never do. It travels into the specification.
Example“Ask for the mortgage number first. Never promise a rate.”
A model answers as the agent would, following its brief and your principles, on made-up data only.
Example“I want to fix my rate for ten years.” → “Could you give me your mortgage number?”
Play the customer yourself. In voice mode it feels like a call: speak, pause, hear the answer.
ExampleTest in English or Dutch, with answers read aloud in the agent’s voice
Save a good conversation and replay it after every change, to see whether the answers got better or worse.
ExampleChange the brief, run again, compare the same four customer lines
Check each conversation against your organisation’s principles. AI suggests verdicts with quotes; people decide.
ExampleAI disclosure: not met, “the agent did not say it is an AI assistant”
Switch steps to Live to call your real backend through the approved capabilities, within your policies. Every write waits for a person to approve that exact call.
Examplelookup_mortgage (Live, read) → update_mortgage_rate waits for the mortgage advisor → Approve & continue
Hand the builders the agreed design: a specification with the steps, agent briefs, approvals and agreed behaviour, plus the process as JSON or YAML.
Examplemortgage-service-change-design-spec.md and the process in YAML, ready for your delivery team
Orqentra Studio brings business and IT together around an agentic process that can be designed, simulated and validated against realistic scenarios and the capabilities you already run. We are working with a small number of design partners who bring real use cases and want to shape what this becomes.
Tell us about the process you would bring.