The Audit Your AI
Spending Never Gets.
The Decision Governance Review is Jochanni Labs' fixed-scope diagnostic. It maps every AI pilot against the requirement it claims to satisfy and issues a verdict on each one: keep, downsize, kill, or replace.
The first recommended cut pays for the engagement.
The First Line Of Any AI Budget Is The Question Most Consultancies Refuse To Ask.
Where fractional CAIO firms sell strategy and Big Four practices sell maturity roadmaps, the Decision Governance Review issues a fixed-scope diagnostic whose only job is to re-classify the workflow, backed by evidence, not opinion.
Each pilot is traced from the line-item cost it draws down to the business outcome it is meant to support. Most fail the line of sight on the first pass.
For every in-flight model, the Review names a logically viable cheaper mechanism, rules, RPA, classical ML, for your engineering team to validate.
The Review is fixed-scope. The first recommended cut is the ROI, and the Decision Registry is software-readable so the savings travel into the next budget cycle.
Jochanni Labs investigates each workflow against six governing questions. Your named executive sponsor signs the verdict, and DAL-X enforces it where the spend actually happens.
Six Questions, Answered Before A Verdict Is Issued.
A verdict issued without answering all six is a preliminary read. It is labeled as such, not filed as a finding.
Jochanni Labs generates the investigation. Your team validates the evidence. Your named executive sponsor signs the verdict. DAL-X enforces it where in place.
A Short List Of Possible Outcomes. A Row For Each One.
The Review does not grade AI maturity. It classifies each workflow. There are only four verdicts, and the rules are published up front.
The pilot maps to a real business requirement that no simpler mechanism can meet. The reasoning is auditable, the model is monitored, and the spend is earned.
The workflow is real, but the machine-learning overhead is wasted on it. We swap the LLM for rules, a small gradient model, or a tighter retrieval scope.
The pilot is the wrong shape for the requirement. We re-author the requirement so a deterministic or RPA pipeline can carry the workload.
The workflow is busy work: duplicative, low-value, or a measurement artifact. We recommend decommissioning it before the next budget cycle.
Regulated Mid-Market Firms, Ordered By Where The Spend Is Leaking Most.
Built for environments where a wrong model call is a finding: internal audit, regulator letter, or board question.
Where capital-markets scope drift and stale reasoning rates drive model budgets higher than they should be.
Where payor rules, appeals and queue triage are measured in cents-per-claim and most LLM deployments quietly over-spend.
Where document review, drafting and privilege triage beg for a lower-cost alternative, and most AI vendors are content to sell you a model.
Where vision QA, demand sensing and routing pilots get funded before anyone has measured their value against rule-based control.
Administered by Jochanni Labs. Built by a capital markets product owner who has personally caught AI-generated scope drift in payments work.
Four Weeks. One Signed Record Per Workflow.
The price does not move if the answer is "kill half of your portfolio." A single engagement covers up to ten core workflows, additional workflows are reviewed in a subsequent engagement, purchased in blocks of ten.
Pipeline Census
A line-by-line map of up to ten core in-flight AI pilots against the business outcome each claims to support. Cost-per-call, model tier, evidence of acceptance.
Investigation
Each workflow is run through the six governing questions. For each pilot, we name a logically viable lower-cost alternative for your engineering team to validate.
Decision Registry
A structured, exportable registry, one row per workflow, one verdict per row, each with its exact reason and supporting evidence.
Decision Defense Files
A signed file for each workflow. Your team generates the tracking references, Jira or Linear keys, for approved actions, which we log in the final Registry before delivery.
A Signed Verdict Is A Record. The DAL-X Hook Makes It Enforced.
Where DAL-X is already in place, an approved verdict loads directly into the runtime layer as a signed governance manifest. The sponsor's signature becomes the enforced policy, not only a record of intent. Where it isn't, the Decision Registry and each Decision Defense File hand off in a structured format your own engineering team implements directly.
Administered By Jochanni Labs.
The Decision Governance Review emerged from the same operational discipline behind DAL-X: real interaction with enterprise workflows, AI systems, and the gap between what a pilot was funded to do and what it actually does.
Direct Answers.
No Marketing.
01Does a verdict get issued from uploaded data alone?+
No. The six-question investigation produces a preliminary read. A validated verdict requires your team confirming the evidence, business requirement, and operational dependencies, then your named executive sponsor signing it, before it's issued.
02What happens after a verdict is issued?+
The Decision Registry and each Decision Defense File are delivered as a structured, exportable format. Where DAL-X is already in place, the approved verdict is enforced inside the actual pipeline, a cost cap, a routing rule, or a decommission hook, so it isn't left to informal follow-through.
03How many workflows does one engagement cover?+
Up to ten core workflows. A larger portfolio is reviewed across multiple engagements, purchased in blocks of ten, so each Review stays fixed-scope and delivers inside four weeks.
04How do you know the savings actually happened?+
Sixty days after delivery, we hold a thirty-minute checkpoint with your named sponsor to confirm the Registry's approved actions were carried out. Your team reports the outcome directly, this is a confirmation, not an independent audit of your billing.
05Is this under NDA?+
Yes. All engagements with Jochanni Labs are conducted under mutual NDA by default.
Send A One-Paragraph Note.
We'll Be Back In A Business Day.
Most engagements start with the company, the size of the AI spend, and the top three internal audiences it answers to. We'll scope the Review from there.
Reviews Are Limited By Quarter