The work between wanting AI
and running it.
You cannot buy readiness. You build it. ALLJOY sells judgment, not hours: we audit the data, assign the ownership, build the controls, and lead the program that lands.
Or see the two fixed-fee assessments.
Business context first. Technical filters second.
Most data quality reporting starts with a query and works backwards to a meaning. We start with how the business actually runs — raw materials, bulk, finished goods, internal and external — because different scenarios have different rules and different owners. The filters come after that, and every report returns the same standard answer.
Audit the data. Assign the ownership. Build the controls. Then sign the platform deal.
The honest order is unglamorous, and it works. Every engagement below is one move in it — engage the whole sequence, or the single move your program needs next.
AI & Data Governance Readiness Assessment
Ready for AI to do what? Two weeks on your real data answers it.
A fixed-fee audit of the actual data the AI you want would consume — every critical element, every business rule, every silent failure your people have been absorbing. Not the process around the data. The data. $45,000, two weeks from the day we receive it.
You leave knowing exactly where the ceiling on your AI investment sits, which candidate use cases the data can already carry, and what has to move before the rest.
- Element-level audit of the master data your models will consume
- Named critical-data risks, each with a business owner
- The manual compensations that will not transfer to a model
- A go / no-go read on each candidate AI use case
- A sequenced remediation plan, cheapest gaps first
Turnkey Data Quality Implementation
You cannot buy readiness. We build it — end to end.
The unglamorous work that makes AI worth deploying: ownership that survives reorgs, business rules that exist as testable controls instead of tribal knowledge, and controls that sit at the point of entry so new bad data mostly cannot get in.
Turnkey means ALLJOY runs it — through direct engagement and purpose-built tooling, not a deck handed to your team. The measurement layer runs on JoySoft, deployed today at Parker Hannifin.
- Business owners assigned per data domain — role-based, so they survive a reorg
- Critical business rules codified as testable, enforced controls
- Validation at the point of entry, not after something breaks
- Continuous data quality measurement with thresholds and owners
- A governance body funded to act — not a status meeting
AI Governance & Guardrails
Decide what the model isn't allowed to decide — before it goes live.
Every technology before AI kept a human in the loop to catch what the data got wrong. AI removes that human. So the decisions the model is not allowed to make on its own have to be named — in writing, before the platform conversation, not discovered after a bad call in production.
We define the decision rights, assign ownership for what the model produces, and stand up monitoring against ground truth — so you would actually know when it is wrong, and someone with authority could stop it.
- Written decision rights: what AI may never decide without a human
- Named ownership for model-driven decisions
- Monitoring against ground truth, with thresholds and an owner
- An escalation path with an executive who can — and would — stop the rollout
Migration Data Leadership
Your S/4HANA deadline is also your AI deadline.
SAP is selling S/4 as the AI foundation — which means the migration and the readiness are the same project. The data discipline that lands the migration cleanly is the same discipline that makes AI worth deploying. One body of work. Two funded reasons to do it.
ALLJOY embeds senior data leadership on the program — the methodology established by Tom Kennedy at BackOffice Associates, now Syniti — to take data off the critical path and land the transformation without the heroics. When execution needs to happen at scale, we place senior practitioners through partner firms.
- Embedded senior data leadership on the transformation
- Data removed from the critical path, by design
- Migration data risk assessed, named, and owned
- The same foundation the AI work will require anyway
- Full-scale execution routed to partner firms when the program needs it
Governance operating retainer
Findings need an owner.
An assessment tells you where the data stands and who should own it. The gap is usually ongoing rather than one-time — rules to hold, measures to watch, decisions that need somebody accountable when the program moves on.
That work is offered at an assessment readout, once we both know what the data actually says. It is not sold cold, and it is not the reason we were in the room.
- A named owner for the findings, with the authority to act
- Rules and validation held in place, not re-litigated each cycle
- Continuous measurement against a defined standard
- Scoped at the readout, against your findings
We publish how we're paid.
All three ways.
ALLJOY operates through three commercial structures, each with different economics and each disclosed openly — the two fixed-fee assessments, a governance operating retainer scoped at an assessment readout, and senior practitioner placement through partner firms. We sell judgment, so when implementation at scale is what your program needs, we say so rather than stretching the engagement to cover it.
See the three structures and the execution network →
Take the first
honest look.
Thirty minutes. We'll review your specific exposure and tell you which move your program needs first.
Book the executive briefing