01
Map
Document the current inputs, hand-offs, systems, decisions, exceptions and outputs.
Services
Maverick Labs starts with the work already happening inside the team. The first task is to understand the process, the friction and the decisions that should remain with people.
Entry pathway
The AI Workflow Audit is the standard starting point. It creates a bounded first scope before implementation is discussed.
AI Workflow Audit
The audit focuses on one recurring process. It does not assume every step should be automated or that a new platform is required.
01
Document the current inputs, hand-offs, systems, decisions, exceptions and outputs.
02
Compare opportunities against likely value, implementation effort, source quality and operational risk.
03
Set the first outcome, boundaries, approval points, acceptance checks and information requirements.
Audit output
The result is a current-state view, a prioritised opportunity list and a recommended first workflow with its assumptions and human review points made explicit. Implementation remains a separate decision.
Service pathways
The format depends on the process. It may be an automated hand-off, a structured register, a reporting view, an approval screen or a focused internal assistant.
01
Structure decisions, actions, owners, risks, due dates and draft follow-ups, with review before anything is sent.
Typical outputs: registers and drafts
02
Extract and validate information, then create structured records, reports or approval-ready outputs.
Typical outputs: records and reports
03
Combine recurring inputs, apply clear rules and produce consistent status reporting and exception views.
Typical outputs: dashboards and briefings
04
A focused assistant that answers from your agreed documents, shows the source behind each answer and says so when the sources don't support one.
Typical outputs: bounded assistant
05
Connect existing forms, documents, spreadsheets and systems into an approval-gated workflow.
Typical outputs: integrated workflow
06
Add a practical surface where people need to review, correct, approve or monitor the workflow.
Typical outputs: screen or workbench
07
Train the people who will run the workflow, document how it works and hand it over, so the team can operate and change it without depending on us.
Typical outputs: training, runbook, handover
08
For information that must stay in-house, set up workflows on locally hosted models with agreed permissions, so sensitive material isn't sent to an outside AI service.
Typical outputs: scoped private deployment
09
An independent, evidence-first review that checks whether a system, workflow or set of claims holds up against what can actually be verified, and returns labelled findings with the open items made explicit.
View Reality AuditDelivery principles
The work should be understandable and operable by the team using it. Assumptions, review points and exceptions stay visible.
Information requirements and privacy constraints are agreed before business material is introduced.
Automation prepares and structures work. It does not quietly absorb decisions that require accountable human judgement.
The workflow, its inputs and its exception path should be clear enough for the operating team to understand.
The aim is a team that can run and change the workflow itself. Read our approach.
Start with the process
A useful first note explains what comes in, what should come out and where the work currently slows down.