AI workflows driven by
internal knowledge.
A playbook defines the precise steps your assistant executes alongside the governance boundaries it cannot cross. Team members capture their subject-matter expertise in plain language, enabling the assistant to carry out routine operations with complete autonomy tailored to your needs.
Playbooks
Your way of doing the work, written down — steps an agent follows, rules it cannot break.
Look up the order, check it is inside the returns window, refund it and tell the customer.
Collect the documents, check them against the list, open the record and hand it to purchasing.
Read last week's tickets, group what they are really about, write the Friday summary.
The playbook shelf in the app. The line under each one answers the only question worth asking: how much has it run, and how much of that went the way it was written.
In conversation
Via AI assistant or a plain instruction. Transform your workflows.
The same job, “refund this order and tell the customer”, done two ways. The difference is not how clever the agent is. It is whether you want it to follow certain instructions every single time.
Asking
It works it out each time
“Refund order 4417 and let the customer know.”
- A different order every time
- Every tool it has, at every moment
- Sends when it decides it is ready
- Your rules are a sentence it might recall
Fine while you are watching. Less fine at 3am.
Following a playbook
It follows what you wrote
- 1
Find the order
look up order· Stripe - 2
Check the returns window
check policy· Notion - 3
Refund it
issue refund· Stripe asks you first
Never put card details in a reply
checked on the action itself, before it happens
Autonomous background processing
Start a complex playbook and close your screen. Tasks complete in strict sequence across your defined schedule, routing results straight to the team channels you already use.
Mandatory approval checkpoints
Flag sensitive actions to require explicit human authorisation. Unattended operations wait securely until approved, which rules out unauthorised actions and guesswork.
Enforced system guardrails
Controls execute directly on system calls before they are fulfilled. Governance stays immutable, operating entirely independently of language model behaviour.
The steps
Knowledge-driven workflows.
Playbooks capture how work gets done, combining team expertise with AI capabilities to execute context-aware operations.
- Plain text instructions
- Skip visual builders, complex diagrams and IT tickets. Define conditional logic naturally by putting the condition at the start of the sentence.
- Granular tool scope
- Restrict integration access strictly to the steps that need it. If an early step only reads data, the agent never holds the access that would let it move money.
- Explicit approval checkpoints
- Pause workflows at the steps you designate as critical. Overnight background runs wait securely for human confirmation rather than making unauthorised choices.
- Deterministic exception handling
- Codify edge cases explicitly, so execution halts immediately with clear diagnostic feedback instead of being improvised in the moment.
Refund a customer
What this playbook does
- 1
Find the order and note what the customer paid
look up order· Stripe - 2
Check it is inside the returns window
30 days from delivery, not from the order date. A gift order runs from the day the recipient got it.
If the item was marked damaged on arrival, hand it to the claims desk — the run stops here
check policy· Notion - 3
Refund the amount they paid
issue refund· Stripe asks you first - 4
Tell the customer what happened
reply to customer· Zendesk
Refund a customer
The rules it follows
Never refund more than the customer paid
checked on the action itself, before it happens · watches step 3
Never put card details in a reply
checked on the action itself, before it happens · watches step 4
Refunds over €200 need a person
the process stops and a person approves · watches step 3
Refund order 4417
The refund was for €900. Stripe says the order was €240.
The action was not taken. This rule is checked outside the assistant, on the action itself, so it cannot be talked past.
The rules
Immutable policy guardrails.
Policy enforcement takes place within the console, evaluated directly against the underlying execution layer rather than inside agent prompts. Enterprise administrative rules and local playbook policies both apply, so a denial from either authority stops the execution instantly.
- Action-level evaluation
- Security policies validate every operation before it executes. Nothing unauthorised is granted access, and only precisely screened data is let through.
- Flexible approval workflows
- Configure policy evaluations to trigger an automated system approval or to require an explicit manual sign-off, based on the risk involved.
- Dynamic scope protection
- Policy rules evaluate the surrounding context dynamically, so new workflows stay covered automatically without extra manual setup.
- Hierarchical enforcement
- Playbooks may apply stricter local conditions, but they can never override or loosen the baseline enterprise controls set in the console.
TBAC engine
Dynamic execution control.
Access permissions are enforced dynamically at runtime, protecting sensitive systems and keeping you in complete operational control.
- Just-in-time tool provisioningIntegration access is restricted strictly to what an individual step requires, keeping unnecessary capabilities entirely hidden from the assistant.
- Comprehensive parameter screeningThe tool, the incoming arguments, the external connection and where the data is headed are all weighed in a single integrated evaluation.
- Inherited enterprise governanceOrganisation-wide defaults establish the core boundaries that departmental policies build upon, so the most conservative restriction always governs execution.
Policy check
The rule
Customer data does not leave the company. Payments above €10,000 wait for a person.
Three calls, one rule
- create_invoice€4,200, for an existing customerAllowed
- transfer_payment€24,000, above the team's thresholdNeeds approval
- send_emailCustomer list attached, to an external addressBlocked
The same check runs before every call and afterwards stands as a step in the decision chain.
The run
AI that follows your lead and learns from your team.
An action is not a black box you read about afterwards. The steps tick off visibly and a skipped step is shown. If an action has to stop, the system holds it until someone approves it, and records that.
- Transparency
- Above the message box you see the playbook, the step and how far along it is. That goes away when the action ends.
- Actions cannot simply be skipped
- “Didn't apply: the item was not marked damaged” stays on the record, so you can see why this case came out the way it did.
- Every fact names its source
- Looked up in Stripe, provided by you, or the agent's own words. The verbatim line it was lifted from sits underneath it.
- Only real facts can be a yardstick
- A rule may measure against something looked up in a real system, never against a number the agent wrote itself. A rule that trusts the thing it is checking is not a rule.
Refund order 4417
- Find the order and note what the customer paid
- Check it is inside the returns window
- Hand it to the claims deskdidn't apply — the item was not marked damaged on arrival
- Refund the amount they paid
- Tell the customer what happened
- order totalStripe · looked up
- 240.00
- delivered onStripe · looked up
- 14 July 2026
- customeryou provided this
- Renate Böhm, order 4417
- why they askedthe agent's own words
- The size ran small and she has already reordered.
“Order total: €240.00”
“Delivered 14 Jul 2026”
Publish and share
Internal processes which improve based on your needs.
A draft stays private until you publish it. Only the latest published version is ever active, and every release carries a note saying what changed.
Refund a customer
The record
24runs
- finished
- 19
- stopped
- 3
- blocked
- 1
- running
- 1
Releases
- v4
Refunds over €200 now ask a person
2 Aug · Mara K.
- v3
Added the claims-desk stop for damaged items
17 Jul · Mara K.
- v2
The reply moved to Zendesk
3 Jul · Mara K.
Runs on its own
Every weekday, 8am
The overnight refund queue
Next Mon, 08:00
- Drafts are private
- Nobody else has access. Once you publish, colleagues read exactly what the assistant carries out.
- Every release keeps its note
- The note is written from what changed between versions. You keep it, edit it, or write your own.
- The status is fact
- How often the playbook ran, was checked or was stopped: everyone with access to it gets the same figures.
- Unattended does not mean uncontrolled
- Start a playbook on a schedule and it is attributed to you and checked. Exactly as if you had started it by hand.
Transform a playbook and convince yourself.
Bring a use case you would like to hand over in future. We will show you how it works.