AI agent for workflows
Workflows with decisions,not just rules.
The AI agent for workflows runs multi-step processes where classic automation (“if X, then Y”) stops at the first exception. It reads the situation, chooses the next step from those allowed and asks for confirmation when the decision matters.
Fixed automations stop at exactly the cases that take up time
The simple flow is already automated. What stays manual are the variations: a client who sent the wrong document, an order with a special requirement, a request that has to go down a different route. Every exception lands with a person who picks up the case from scratch.
- “If–then” rules become hard to maintain as exceptions multiply
- Unstructured inputs cannot be handled by an automation that expects fixed fields
- Cases stuck halfway have no clear history of the steps already taken
- People do the linking work between systems instead of deciding only where they are needed
Who it is for
- Companies that already have automations (Make, Zapier, Power Automate) and run into many exceptions handled manually
- Teams with long administrative processes: client onboarding, approvals, custom orders
- Processes where the inputs are unstructured (emails, documents, messages) and need interpretation
- Managers who want to know exactly where each case has been and who approved what
What the AI agent for workflows does
- 01
Reads and interprets the input
Understands an email, an incomplete form or a document and extracts what is needed for the next step.
- 02
Chooses the right route
Decides between the defined flow options (standard, additional check, escalation) based on the rules and the context.
- 03
Runs steps across several systems
Uses the approved tools: creates records, updates statuses, generates documents.
- 04
Requests missing information
When a document or a confirmation is missing, prepares the request and resumes the flow after the reply.
- 05
Stops for approval
Before steps with impact (external communications, amounts, contract changes), waits for a person's confirmation.
- 06
Keeps the history of each case
Records every decision and the reason for it, so anyone can resume or audit the case.
How it works
How a case moves through the workflow
The steps marked in yellow are approved by a person.
- Input
- AI
- Action
- Human in the loop
- Result
- 01
Input
New case
A request, an email or a document triggers the flow.
- 02
AI
Analyses and decides
The agent checks what information it has and chooses the route from the allowed options.
- 03
Action
Runs the steps
Updates the systems, generates documents or requests missing data.
- 04
Human in the loop
Approval where it matters
A colleague confirms sensitive steps or takes over cases that fall outside the rules.
- 05
Action
Completes the flow
The agent closes the case in the systems and notifies the parties involved.
- 06
Result
Documented case
The result and the full history of decisions are saved.
What information and tools the workflow agent uses
- The process description: steps, route options, stop conditions and approval points
- Authorised tools in each system, with separate permissions for reading, writing and proposing
- Approved document and message templates
- Business rules: value limits, deadlines, escalation criteria
- The history of previous cases, used for testing
Possible integrations
- CRM (HubSpot, Salesforce, Pipedrive)
- ERP (Odoo, SAP Business One, WinMentor)
- Microsoft 365 / Outlook
- Gmail and Google Workspace
- Make, n8n or Power Automate for steps that are already automated
- E-signature platforms
- Ticketing systems (Jira, Freshdesk)
- The company's internal APIs
- CRM (HubSpot, Salesforce, Pipedrive)
- ERP (Odoo, SAP Business One, WinMentor)
- Microsoft 365 / Outlook
- Gmail and Google Workspace
- Make, n8n or Power Automate for steps that are already automated
- E-signature platforms
- Ticketing systems (Jira, Freshdesk)
- The company's internal APIs
Each integration's compatibility is checked during the analysis phase, for the systems and versions you use.
Control and transparency
What a person validates
- Any external communication sent on behalf of the company, until the templates have been validated
- Steps involving amounts, discounts, contracts or changes to important data
- Cases the agent marks as unclear or outside the defined routes
- Changes to the process, the rules or the agent's permissions
Limits and how we manage them
- The agent chooses only from the defined routes and tools; it does not invent new processes
- It works best on a clearly described process; if the process is still unclear, we document it together first
- For fully predictable flows, fixed automation is simpler, cheaper and easier to maintain
- The agent's decisions can be wrong in rare cases; that is why steps with impact require human approval
- It depends on the availability and the APIs of the connected systems
How we measure the quality of decisions in the flow
We agree the indicators together before launch and track them afterwards. The values depend on the process, the data and the volume.
- Accuracy of the chosen route
- We run historical cases and compare the route chosen by the agent with the decision the team made at the time
- Cases completed without intervention
- We measure from the log how many cases go through end to end and how many need manual takeover, and why
- Rejected approval rate
- We track how many proposals sent for approval are corrected or rejected, and why
- Errors in connected systems
- We monitor failed or cancelled actions and their technical causes
How we implement the workflow agent
- 01
Mapping the process
Together we describe the real steps, variations and exceptions, starting from concrete cases.
- 02
Agent or automation
We decide which steps remain fixed automations and where an agent's judgement makes sense.
- 03
Building and testing on historical cases
We connect the tools, define the approval points and test on cases that have already been resolved.
- 04
Pilot with extended approval
At first we approve more steps manually, then relax control only where the results justify it.
Use cases
The examples below are conceptual scenarios, not delivered implementations.
- Leasing and financing
An incomplete client file
The agent checks the documents received, identifies what is missing, requests it and sends the file to the analyst only when it is complete.
Conceptual example - Made-to-order manufacturing
Orders with special requirements
Standard orders go straight into the ERP, while those with special dimensions or materials are sent for technical review, with a summary of the requirements.
Conceptual example - B2B services
Onboarding a new client
After the contract is signed, the agent creates the account in the systems, prepares the initial documents and schedules the steps, and the account manager approves the welcome message.
Conceptual example
Frequently asked questions
When is simple automation better than an agent?
When the process is fully predictable, with structured data and no frequent exceptions. There, fixed automation is cheaper and easier to control. An agent makes sense when interpretation and decisions are needed along the way.
Can the agent take any step in our systems?
No. It only gets the tools we approve for that process, each with clear permissions. Everything it does is logged and can be audited.
What happens when the agent is not sure which route to choose?
It pauses the case, explains why it cannot decide and sends it to a person with all the context gathered so far. It does not carry on by guessing.
How is the data passing through the flow protected?
The agent accesses only the data needed for each step, using dedicated accounts. We agree on log retention and choose AI providers with clear commitments on data processing.
Can we keep the automations we already have?
Yes. Often the agent takes over only the part that involves decisions, while the simple steps stay in Make, n8n or Power Automate.
How do we get started?
With a single process and concrete cases from the last few months. We describe the real steps and exceptions, decide what remains fixed automation and test the agent on cases already resolved, with more human approvals at the start.
Can’t find the answer? Write to us and we’ll reply directly.
Do you have a process that gets stuck at every exception?
Describe the flow and where your team steps in manually. We will tell you honestly whether you need an agent or whether simple automation is enough.
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