Trigger & handoffs
Map the trigger, required data, system handoffs and final action.
Awakast · AI engineering
AI workflow automation development
For product and operations teams handling repetitive work across several systems, we connect those systems in one workflow, use AI where inputs need interpretation and require human approval for consequential actions.
Scope one workflowDefine the scope
Separate rules from judgement
Rules & judgement
Keep steps governed by clear rules deterministic; use AI for the interpretation that needs evaluation. Agree which proposed actions require approval.
Approval & exceptions
A useful scope explains who acts when the model or an integration cannot complete the task.
What you can commission
Start with one process and an agreed end state. We can scope the design, integrations, AI steps, review controls and handover together; additional processes and ongoing support need their own agreement.
A process definition
Document the trigger, input format, system of record and completed outcome, along with approval rules, permitted actions and who handles exceptions. This gives the delivery team and your operators a shared description of what the automation may do.
An executable integration
The build can include API connectors, deterministic checks, AI interpretation and a queue for human approval. Track each task through the agreed steps, including a confirmed write to the destination system rather than just a generated draft.
An acceptance and handover pack
Agree the process tests, action log, operating instructions and monitoring included in the handover before we start. Agree which configuration your team can change, how to pause execution and what post-launch support covers before release.
A concrete starting point
A supplier invoice that does not match its purchase order
1
Hypothetical workflow: compare an invoice with its purchase order and delivery record, then flag mismatched line items or totals.
2
One AI step explains the discrepancy; a second agent checks that explanation against those source records.
3
If records are missing or conflict, route the case to an operator with the evidence and a proposed resolution.
4
A person approves any accounting change.
5
If the integration times out, check the accounting record before retrying to avoid posting the invoice twice.
Scope & acceptance
Accept the whole process, not a single model output
- Test invoices with matching records, mismatched totals, missing delivery confirmations and a timed-out write.
- Agree how each case should be handled before delivery, and check the destination before retrying so a completed write is not repeated.
- Compare processing time and review quality with the current baseline.
How we approach the work
Map the current work
Walk through a real task with the people who perform it. Identify delays, repeated interpretation and manual handoffs. Record today’s completion time and review effort so later evaluation has a useful baseline.
Choose the simplest architecture
Use rules for validation and routing when they are enough. Introduce AI for unstructured interpretation. A single controlled process may be sufficient; multi-agent architecture is an option when tasks need distinct tools, permissions or independently testable specialist outputs.
Assign bounded agent roles
A possible design separates extraction, classification and result checking, with an orchestrator managing the handoffs. These are proposed operational roles, not extra autonomous authority. Each agent needs defined inputs, outputs, tool access and a stopping condition.
Build, evaluate and release in stages
First test the process on representative inputs without consequential writes. Review proposed actions with the owner, then enable only the agreed actions and user groups. Expand the scope after the complete process meets acceptance criteria.
Controls, evaluation & ownership
Approval before consequential action
Specify which actions can run automatically and which require a person to approve the exact proposed change. The destination system’s permissions still apply. Uncertain classifications or incomplete inputs should enter a review queue, not bypass the gate.
Failures, retries and duplicate actions
Agree handling for unavailable APIs, timeouts and partial completion. Scope retry limits, duplicate-write prevention and a visible exception queue. Before retrying a failed handoff, establish whether the earlier action already succeeded.
Acceptance across the whole task
Test ordinary cases, ambiguous inputs, rejected approvals and failed integrations. Inspect both the AI output and the final system state. Compare completed-task time and review effort with the baseline; model fluency or the number of agents is not a business result.
An accountable operator
Your process owner decides policy and exceptions; the agreed technical owner manages credentials, monitoring and incidents. Define who can pause the process, correct a record and approve changes to a prompt, tool or model. Set logging and retention to your data constraints.
Before we start
Bring a process brief
Share a current process map, sample inputs, destination systems, available access and the reviewer responsible for exceptions.
The scoped build can include orchestration, human review, traceability, monitoring and handover.
If the same result can be achieved with a rules-based integration, start there; if feasibility is unclear, commission discovery before automation.
When to choose another path
- A rules-based connector or feature in your existing software completes the task adequately: use that before adding agents.
- No accessible systems, no owner for exceptions or no permission to automate the final action: settle those dependencies before a build.
- An open-ended autonomous worker with unrestricted access and no review or measurable end state is not a workable delivery brief.
Questions before you commission
Do we need a multi-agent system?
Only if the task warrants it. Separate agents can help isolate specialist work, but they add coordination, latency and evaluation work. Compare them with one agent or a rules-based process against the same acceptance criteria.
Can the automation use our existing systems?
That depends on their APIs, permissions and operational limits. Bring the source and destination systems to the first conversation. We scope connectors around supported access, rather than assuming every screen can safely be automated.
Will people still need to review results?
Agree review by action and risk. A low-impact routing step may be automated after evaluation; a sensitive change can remain approval-only. The review queue and manual fallback are part of the process, not temporary workarounds.
What happens after launch?
Agree the operational owner, incident path and support scope before release. Source data, APIs and models can change. The handover should explain how to retest the process, pause it and recover incomplete tasks.
Can you estimate savings before building?
Begin with observed task volume, completion time and review effort in your current process. Include integration and operating costs in the comparison. A pilot can test the assumptions; savings still need to be demonstrated in operation.
See a multi-agent architecture in a legal workflow
Our VAIOT legal multi-agent case describes supervisor-led specialist agents, legal RAG and escalation to human review. It is a concrete example of coordinated tasks and controls, not a template every business process needs.
Explore integrations and controlled AI workflows
Use our engineering cases to discuss system handoffs, proposed actions and human approval in your process.
Bring one repeated task
Send an example input and the destination system. We will discuss the build, approval rules and who handles exceptions.