Our workClient work is confidential.
Client work is confidential.
The method is not.
We do not publish a client logo wall, and we do not name who we work with — see our case studies page for why. What we can show instead is the method itself, and real anonymised patterns from past engagements, each one linked back to where we first published it.
Key takeaways
What the engagements actually show.
- In one European manufacturer’s order-handling workflow, three of eleven steps genuinely needed a model. The other eight were parsing, lookups, validation and routing.
- Research-heavy consulting work sees a 30–50% acceleration in deliverable turnaround — in the research and first-draft stages, not in the judgement calls.
- The average agency loses 12–18 hours per week, per fee-earner to non-billable admin. That is the workflow mapped first, because nobody budgeted for it.
- A senior automation hire beats a platform licence at a typical 5–10x return, because the specialist finds the three workflows worth automating.
Source for every figure: SUPALABS engagement data, 2024–2026, each one linked to where it was first published in the patterns section below.
The findings, in one table
Where the work actually goes.
| What was measured | Finding | Where it applies |
|---|---|---|
| Steps that genuinely need a model | 3 of 11 | Manufacturer order handling |
| Deliverable turnaround | 30–50% faster | Research-heavy consulting |
| Non-billable admin lost | 12–18 hrs/week | Per fee-earner, agencies |
| Senior hire vs platform licence | 5–10x return | Mid-market automation buys |
Each row is expanded, with its original source, in the patterns section below.
What every engagement produces
Five artifacts, each one nameable.
You cannot inspect a client we will not name. You can inspect a document. Each engagement produces the same five, regardless of industry.
Exception LedgerEvery real deviation from the documented process, how often it happens, and who absorbs it today.
AI Boundary MapEach step marked as deterministic code, model judgement, or human approval. Most steps are not AI.
Evaluation suiteA golden dataset, per-step pass rates, and a monthly accuracy report. A named line item, never bundled.
Decision logEvery agent action, its inputs, its confidence, and who approved it. A surface a compliance officer can open.
ERP-additive covenantWe build on top of your existing systems. We do not propose replacing them. No migration.
How an engagement runsThe method in full →
Four rungs. You can stop after any of them.
0
Qualification call — free, 30 minutesA straight answer on whether there is anything here worth mapping.
1
Mapping Sprint — five days, embedded with the teamPaid discovery. Produces the Exception Ledger, the AI Boundary Map, and a fixed-price build quote.
2
Build — six weeks to productionScoped from the sprint findings, built on top of your existing systems, human approval at every irreversible step.
3
Run — ongoingMonthly accuracy report against the golden dataset, regression alerts, quarterly re-scoping.
How authority is earned
Three tiers, set per task type, and you set the thresholds.
Every automated task runs at one of three levels of authority. The tier is set per task type rather than per system, so the same workflow can draft one step, wait for approval on another, and act alone on a third. A task moves up only when the evaluation suite shows the pass rate you defined as the threshold, and it moves back down the moment the monthly report shows a regression.
1
DraftedThe system prepares the work and a person finishes it. Every draft carries its evidence: the source documents, the rule or model that produced it, and its confidence. This is where every task starts, and where shadow mode runs before anything is shown to the team at all.Gated by the Exception Ledger — the task is not automated at all until its real deviations are written down.
2
ApprovedThe system prepares the complete action and a named person authorises it before anything consequential moves. The approval, the approver and the inputs go into the decision log.Gated by the evaluation suite — promotion from Drafted needs the per-step pass rate you set, measured against the golden dataset.
3
AutonomousThe system acts and the team audits afterwards, on a sample or on the exceptions. Any irreversible step stays at Approved regardless of accuracy, because a reversible mistake is a cost and an irreversible one is a liability.Gated by the monthly accuracy report — a regression alert sends the task back down a tier until the pass rate recovers.
Nothing is promoted on our say-so. The thresholds are yours, the report that tests them is a named line item, and the decision log shows every action that was taken at every tier.
The full method: five artifacts, three tiers, four rungs →Patterns from real engagements
No client names. Real patterns.
Each of these is drawn from an actual engagement and was published, in this form, on the page linked below — this section compiles them, it does not introduce anything new.
A European manufacturer’s order-handling workflowWe mapped the workflow step by step. Three of eleven steps genuinely needed a model. The other eight were parsing, lookups, validation and routing — work that ordinary software does more cheaply, faster, and with an answer you can reproduce tomorrow.Source: Embedded Operators →
A quote-to-cash process, five handoffs, no ownerSales creates the opportunity, finance checks the credit position, operations confirms it can be delivered, legal reviews non-standard terms, finance invoices. Five handoffs, five owners, and a process that no single one of them is accountable for end to end.Source: AI Does Not Respect Your Org Chart →
Mid-market agency engagementsAcross the agency engagements in our data, the median engagement value is $45K — and the agencies that get the most from it are the ones that had already mapped which of their own workflows were the real bottleneck before the build started.Source: AI Workflow Automation for Agencies →
Research-heavy consulting workIn research-heavy consulting engagements, we typically see a 30–50% acceleration in deliverable turnaround — concentrated almost entirely in the research and first-draft stages, not in the judgement calls a senior consultant still makes.Source: AI Tools for Consultants →
Non-billable admin at agenciesThe average agency in our data loses 12–18 hours per week, per fee-earner, to non-billable admin — timesheets, status updates, scope-change paperwork. That is the workflow we map first, because it is the one nobody budgeted for and everybody absorbs.Source: AI Automation for Agencies →
One senior specialist hire vs. a platform licenseWhen the choice is between a platform license and a single senior automation specialist hire, the hire wins more often than vendors admit — a typical range of 5–10x return, because the specialist finds the three workflows worth automating instead of automating whatever the platform demo covered.Source: Workflow Automation Specialist Hiring Guide →
The one we can show end to end
Not a client. Our own network.
Client engagements stay confidential. The one system we can walk through in full — challenge, build, results — belongs to a partner in our own network, not a client, which is exactly why we are able to show it.
Read the case study →Read this before you book
When you should not buy this.
You can staff a standing practiceIf you are large enough to run your own internal delivery team, hire it. Embedded delivery is how you learn what to hire for, not a permanent substitute for it.
The problem is arithmetic, not judgementIf the rules are knowable and stable, a rules engine or a well-built spreadsheet beats anything we would put in front of you, and costs less to maintain.
No executive owns the outcomeWithout a named owner who can clear an approval boundary, the work stalls at the first one. That is true regardless of who builds it.
Frequently asked
Questions buyers actually ask.
How much of a process actually needs AI?Usually a minority of it. In a European manufacturer’s order-handling workflow that SUPALABS mapped step by step, three of eleven steps genuinely needed a model. The other eight were parsing, lookups, validation and routing — work that ordinary software does more cheaply, faster, and with an answer you can reproduce tomorrow. That ratio is published for each engagement as the AI Boundary Map.
Why does SUPALABS not publish client names or a logo wall?Client work is confidential; the method is not. An embedded operator sits inside a client organisation and sees how the work actually runs, so confidentiality is a condition of the engagement rather than a marketing choice. What can be inspected instead is the method and the five artifacts every engagement produces: the Exception Ledger, the AI Boundary Map, the evaluation suite and monthly accuracy report, the decision log, and the ERP-additive covenant.
What evidence is there that an engagement worked, if the clients are anonymous?Named documents rather than named logos. You cannot inspect a client that will not be named, but you can inspect a document, and every engagement produces the same five regardless of industry. The evaluation suite is the strongest of them: a golden dataset, per-step pass rates and a monthly accuracy report, quoted as a named line item and never bundled, so accuracy is measured after the build rather than asserted before it.
What kind of time savings do these engagements produce?It depends on the work. In research-heavy consulting engagements SUPALABS typically sees a 30–50% acceleration in deliverable turnaround, concentrated almost entirely in the research and first-draft stages rather than in the judgement calls a senior consultant still makes. The average agency in the same data loses 12–18 hours per week, per fee-earner, to non-billable admin such as timesheets, status updates and scope-change paperwork.
Is a platform licence or a senior automation hire the better buy?When the choice is between a platform licence and a single senior automation specialist hire, the hire wins more often than vendors admit — a typical range of 5–10x return. The reason is scoping, not talent: a specialist finds the three workflows worth automating, whereas a platform tends to automate whatever its demo covered.
When should a company not buy an embedded engagement?Three cases. If you are large enough to run your own internal delivery team, hire it — embedded delivery is how you learn what to hire for, not a permanent substitute. If the rules are knowable and stable then the problem is arithmetic rather than judgement, and a rules engine or a well-built spreadsheet beats anything SUPALABS would put in front of you. And if no executive owns the outcome, the work stalls at the first approval boundary regardless of who builds it.
Thirty minutes to find out whether there is anything worth mapping.
The call is free, and we will tell you if the answer is no.