Straight answers about hiring AI worker teams.

A grab is a point in a business where work is picked up, waits, or changes hands. Every process has a handful, and they are where the time goes. GRABS finds them, measures what they cost, and places AI workers at them. That is the Grab Method: find the grabs, read the card, manage the term.

The one-page job spec every GRABS hire is proposed on. It states what the worker knows, what it can do, how it behaves, what it is permitted to use, how far it can go before it must ask, and what it needs from the client. Buyers read it the way they would read a candidate, and nothing starts until they have.

A fixed-price, one-week analysis of a single process, run under NDA. The client receives a measured picture of where the work waits and what that costs, the Role Card for the hire that would fix it, and a readiness list with named owners. Everything it produces belongs to the client, whether or not they go on to hire.

Over 40% of unmanaged AI projects fail because nobody owns the outcome, not because the models lack capability. GRABS addresses this directly by assigning every AI worker team a mission, KPIs and a review cadence, so accountability exists from day one.

GRABS supplies managed AI worker teams on fixed-term contracts, structured like interim staffing rather than software licences. Each team comes with a job description, weekly Monday Reports, 30/60/90-day reviews backed by instrumented evidence, and a sixty-second sacking switch for instant termination.

GRABS reviews every AI worker team at 30, 60 and 90 days against its defined KPIs, using instrumented evidence rather than self-reported claims. Weekly Monday Reports keep management informed between reviews, and audit trails document the record throughout.

No. GRABS workers operate exclusively on scoped identities issued for the specific engagement and never hold or use client credentials. There is no shared password to rotate and no standing access to audit away after the contract ends.

No. GRABS enforces complete per-client separation by design, and client knowledge is held in the vault under explicit access rules with compliance logging. Nothing processed for one client is visible to, or reused for, any other client.

The client does, in full. GRABS clients retain complete data ownership throughout and keep portable outcomes at the end of the contract, including playbooks, trained processes and attestation records.

Yes, if the supplier builds for it. GRABS teams generate complete audit trails and compliance logging on every action, sit inside approval queues and escalation routes, and undergo performance reviews at 30, 60 and 90 days backed by instrumented evidence. That is a stronger evidence base than most human roles produce.

Clients retain full data ownership and keep the portable outcomes: attestation records, playbooks and trained processes. The compliance evidence generated during the engagement belongs to the client, not to GRABS, so it remains available for future audits.

GRABS provides weekly Monday Reports summarising work done, approval queues that route defined actions through your designated approvers, and escalation routes for exceptions. If you need to stop an engagement, the sixty-second sacking switch delivers instant termination with code-enforced caps.

Yes. GRABS provides a sixty-second sacking switch that terminates an AI worker team immediately, with no notice period and no exit negotiation. Because GRABS engagements are fixed-term staffing contracts rather than software licences, termination is a client right, not a concession.

The client keeps everything of value. GRABS engagements are portable by design, so playbooks, trained processes and attestation records transfer to the client on exit. The business retains the capability it paid for, independent of any ongoing relationship with GRABS.

GRABS applies code-enforced caps on spend and scope to every AI worker team. These are hard technical limits built into the workers, not policies reviewed after the fact, so a team cannot exceed its budget or drift beyond its agreed brief.

GRABS anchors its pricing to human interim day rates, so the cost is directly comparable to bringing in interim staff for the same work. The difference is that GRABS carries no employment overhead: no employer's National Insurance, pensions, holiday pay or recruitment fees, and engagements are fixed-term with outcome pricing.

Per-seat pricing charges for access rather than results and grows with headcount rather than output. GRABS prices like staffing, not software, so clients pay for a fixed-term engagement and the outcomes it delivers, and the cost never scales with the number of people in the business.

Failed, unmanaged AI projects are the single biggest threat to AI return on investment. GRABS supplies managed AI worker teams with outcome pricing, onboarding in days rather than months, and portable playbooks, trained processes and attestation records on exit, so the spend produces proven results and a lasting asset.

No. Structuring scattered knowledge is the purpose of the vault phase, which GRABS runs as the paid first stage of every engagement. GRABS extracts knowledge from your documents, systems and people and turns it into a governed source of truth.

The vault is the GRABS structured knowledge repository. It holds the business context AI workers need, the access rules that govern who and what may use each item, and compliance logging that records how knowledge is used.

Yes. The vault, along with the playbooks, trained processes and attestation records built on it, is a portable outcome the client owns and keeps. Your knowledge leaves the engagement more organised and more valuable than it arrived.

GRABS onboards managed AI worker teams in days, not months, because every engagement starts from a defined job spec within a seven-stage employment lifecycle. Once the vault knowledge phase is complete, AI workers begin producing output against that spec in the first week of the contract.

GRABS runs governance weekly from the start through Monday Reports, backed by approval queues and escalation routes so humans control what is released. Formal performance reviews at 30, 60 and 90 days measure AI workers against the original job spec.

The seven-stage lifecycle ends with a structured handover, not a switch-off. Clients keep portable outcomes from every GRABS engagement, including playbooks, trained processes and attestation records, so the capability and its evidence remain in the business.

No. GRABS designs its AI worker teams to augment staff, absorbing routine throughput so people move up to review, judgement and client work. Humans remain in command through approval queues and escalation routes on every consequential action.

GRABS builds control in as mechanism: approval queues put actions in front of a named person, escalation routes give edge cases a human destination, and weekly Monday Reports keep managers informed. If trust breaks, the sixty-second sacking switch terminates the team instantly with code-enforced caps.

It stays with you. GRABS captures working knowledge in the vault throughout the engagement, and at handover the client keeps portable outcomes: playbooks, trained processes and attestation records. The capability becomes a permanent asset of the business.

Because most AI is deployed where work is already moving, not where it waits. A process's output is set by its slowest point, so accelerating anything else produces backlog rather than throughput. GRABS starts by measuring where one process actually waits, aims the hire there, and sells it against a single flow number such as debtor days or turnaround time.

At the point where work waits longest, which is rarely the busiest desk. The GRABS Process Diagnostic measures one process from a client's own records in a week, showing where the work waits and what that costs. The first hire is aimed at that point and measured on the number that proves the wait shrank.

Then GRABS says so before selling a worker, because feeding a blocked approval queue only builds backlog faster. The engagement is designed around the approver: the queue is kept deliberately small, escalation routes have named destinations, and the worker's authority is raised at the 30, 60 and 90 day reviews only as the record earns it.

The wait between them all but disappears. Work waits longest where it changes hands between organisations, such as the records an SME owes its accountant, and that handoff is the same grab seen from both ends. When each side runs a GRABS worker, the item passes worker to worker instead of sitting in either firm's queue, which is why each deployment makes the adjacent one more valuable.

From the work itself. A GRABS worker logs every wait, handoff and escalation it works as a side effect of doing the job, in the client's own vault. It measures the work it is given, never the people around it. The picture stays current without another project, and the Monday Report can show where the next wait is, so renewal decisions rest on standing evidence.

Not your content, ever, and not without your agreement. Per-client isolation is absolute: no GRABS worker ever reads across a client boundary. Benchmarks are assembled separately from anonymised timing patterns, only from engagements whose terms allow it, and no client can be identified from them. What clients receive in return is context no survey offers: how their measured waits compare with firms like theirs.