AIM is interim management for the AI function. We take responsibility for AI in your operation for a defined period — we map the processes that currently live in files and in people's heads, put them into a system, and run them until your team runs them without us. Diagnostic, plan and implementation are contracted separately, and each one stands on its own.
Most AI programs stall for a concrete reason: the processes they are meant to improve are not written down anywhere. They exist across documents, spreadsheets and the experience of the people running them. That is hard ground to build a system on. AIM structures the operation first. AI comes in after that, and it fits.
The way work actually gets done is distributed across documents, spreadsheets and the memory of the people who do it. Every departure, promotion or new hire turns knowledge transfer into an expensive draw on management time.
Open items circulate through chat, email and standing meetings. Open cases advance with no structured tracking. The evidence that something was executed is scattered, and reconstructing it after the fact costs real hours.
Steps that were skipped or done wrong tend to appear in an audit, a customer complaint or a month-end close — by which point the cost is already incurred. That exposure is almost never quantified.
Each phase is contracted on its own. You can start with the diagnostic, move to the plan when the findings justify it, and implement after that. There is no commitment to all three up front. Each phase produces a deliverable that stands alone.
We document the SOPs you have today, map the processes that matter, identify where AI actually pays and where it does not, and audit the data you can reach. This is not a generic assessment. It is your operation, examined.
We turn the diagnostic into a roadmap you can execute: what gets built first, what comes after, on what stack, budgeted by milestone, with the internal resources required and the metrics that define success. A plan that holds up in front of a board.
We build. Conversational agents, automated workflows, internal apps with AI built in, LLM analysis across your data, executive dashboards. Each month you get a report on what ran, what it saved and what comes next.
Each phase is quoted and signed separately. You can run only the diagnostic and take it to another firm to build. You can combine diagnostic and plan and implement with your own team. The point is that the decision gets made on evidence, instead of committed to in advance.
AIM runs on EOS — our operating system for running a company on evidence. It is not an abstraction. It is a concrete equation: your SOPs go in, the calendar decides when each one is due, and three lanes (human, AI, engine) execute them, leaving an auditable trail.
In EOS every SOP is a contract with five fields: who owns it, what goes in, what it does, what comes out, and how you know it was done right. The calendar decides when it is due. The three lanes decide who executes it.
A single process mixes three lanes of execution: the system handles what repeats, AI prepares the draft, and your team decides what requires judgment. No process starts in the automatic lane. It earns its way there once the rule is stable and the corrections have settled into one.
A guided checklist with evidence and approvals. Measurable and auditable, even though a person still does the work.
AI prepares the draft; your team approves, corrects or discards it. Nothing moves forward without a human sign-off.
Executed in code. The same every day, without variation. The person moves from doing the work to reviewing the result.
We pull the process out of wherever it currently lives — documents, spreadsheets, the person who has always done it. It gets structured into five fields: who, what goes in, what it does, what comes out, how it is validated.
The SOP goes in as an executable contract. It gets an owner, a second who can cover it, the evidence it is expected to produce, and a validation rule. The process is auditable from day one.
EOS schedules it by its own rule — a fixed date, a triggering event, a condition being met. The calendar stops depending on someone remembering.
AI proposes drafts, extractions and classifications. The person decides: approve, correct or discard. Every interaction is recorded.
Every human correction becomes a reviewable rule. In month one you correct twenty details; by month six, two or three. The process improves without being reprogrammed.
Once the rule is stable, the process moves to the automatic lane. The person stops operating and starts supervising: reviewing output, approving exceptions, validating changes.
This is not "AI consulting." It is a team with nine service lines, deployed according to what the diagnostic finds in your operation. Everything produced for your business is yours — the code, the prompts, the documentation, the reports.
We document how the company runs today, where the friction sits, and what should be automated with AI versus what should simply be a better process.
For customer service, B2B sales, internal support, lead qualification. With guardrails, your brand voice, and handoff to a person when the conversation calls for it.
n8n, Make, Zapier, or custom in Python or Node. Quoting, order follow-up, inventory alerts, recurring reports.
Executive dashboards, analyzers, spec-sheet generators, internal tools. Built around your operation.
Across your ERP, CRM, ecommerce, messaging and email. Extraction, classification, and an automatic weekly executive summary.
Tested prompts organized by use case, versioned, with performance metrics. Reusable by your entire internal team.
Working sessions, not lectures. Your people learn to use and modify what we build. By the end, the internal team runs AIM and EOS.
Explicit rules for responsible use, data privacy, the limits of what AI is allowed to decide, and exception protocols. Auditable.
What ran, how many hours it saved, what failed and why, what comes next month. Four to six pages, ready for the board.
Three views of EOS running inside a company. AIM installs it in phase 3. Switch tabs to see the operating dashboard, an agent handling a live customer, and a workflow laid out end to end.
These are the processes where AI automation has the best impact-to-effort ratio in a commercial operation. The figures below are modeled estimates built from a 114-process catalog at a single distributor. They are not results we have delivered to a named client, and they are here to size an opportunity. The range that applies to your operation is established in the diagnostic.
Open To Buy, the weekly purchase budget. EOS combines sales history, current inventory, forecast and seasonality to recalculate it by category and SKU. It alerts the buyer when a call needs to be made. Exceptions are documented.
Prophet plus an LLM over 90 to 365 days of sales and outside factors — calendar, weather, campaigns. More accurate than a manual spreadsheet, and explainable at the SKU level.
Every morning EOS recalculates distribution routes against confirmed orders, vehicle capacity, delivery windows and expected traffic. The driver gets a finished route.
Reads public competitor pricing, historical elasticity and margin targets. Proposes per-SKU adjustments with a stated rationale. Never changes a price without human approval.
EOS processes rep calls and chats. It flags unresolved objections, prices communicated wrong, and opportunities left on the table. Sales management gets the case and the evidence.
Reads each account's payment pattern and adjusts the message, channel and timing of the reminder. Text for some, email for others, a human call for the accounts that warrant one.
From raw supplier catalogs to finished product pages with SEO, keywords and comparisons, in your brand voice. A hundred SKUs processed in hours instead of weeks.
EOS joins sales, margin, inventory, receivables and logistics into a three-page narrative report ready for the management meeting. With findings, not just tables.
We ran EOS against a 114-process catalog from a single full-line distributor: finance, tax, payroll, inventory, warehouse, collections, sales. This is how they split across the three lanes. It is a starting estimate, not a commitment.
Processes that consume hours of expensive people today and can run on their own with evidence. None of them need AI — they need the ERP to be readable.
Reconciliations with classified variances, reports with alert bands. None of these automate in one step; all of them improve month over month as history accumulates.
Meetings, calibration, credit decisions, negotiation, physical receiving. A third of the operation can't be automated, and shouldn't be. AIM organizes these; it does not replace them.
A product that only handles what fully automates handles roughly one process in six. AIM governs all three lanes: the whole system, including the parts that stay human.
This is the standard rhythm when all three phases run together. If you contract only the diagnostic or only the plan, the schedule adjusts but the rigor does not.
Session with leadership. We agree on the three to five processes that go into the diagnostic. Access setup across ERP, CRM, messaging and ecommerce. NDA signed. Opening session with the operating teams.
One-on-one interviews with function leads. We map the flows as they actually run. We audit the data sources. We separate quick wins from structural friction. You get a 20- to 30-page executive report.
Findings become an executable roadmap. Prioritized by impact against effort. Proposed technical architecture. Budget by milestone. Success metrics. Risk analysis. Board presentation if the decision calls for one.
We pick the highest impact for the lowest risk. Solution design, prototype, iteration, deployment. By the end of the sprint something is running inside your operation with before-and-after numbers attached.
What was built. What ran. What failed and why. How much time it saved. What comes next month. Session with the board or management committee. Decision on whether Sprint 2 proceeds.
AIM does not fit every company. We would rather say so before a sales conversation than during one. The first list is when an implementation has a high probability of working. The second is when something else would serve you better.
Tools that promise everything usually deliver the easy third. AIM does one thing: it makes your operation run. These are the four limits we hold to, and the ones other firms tend to sell past.
Nothing on the list is made up. Every item comes from a process you own, with an owner and expected evidence. Ad-hoc work stays in your chat, where it belongs.
SAP, Odoo or whatever you run stays the system of record. EOS organizes the human operation around it. It reads the ERP through a local replica — it never writes to it.
We do not automate someone else's user interface. We hand your people the data already prepared: less brittle, and auditable.
The AI proposes; your people validate. Anything that must come out identical every time is done in code, not by a model.
AIM has a defined and bounded scope: making the operation run, with evidence, with an owner, and on a calendar. It doesn't go beyond that.
KOJ Consulting works in analytics, business intelligence, applied AI and systems design. We work with mid-market and larger companies, and engagements run remotely. Our working hours overlap the full U.S. business day, across all four time zones.
AIM is our interim management practice for the AI function: how we get operating AI into companies that need a result in months, without the company having to hire and sustain an internal AI team first. It is delivered on EOS, our proprietary system.
Six short questions to tell whether AIM is a fit. If it does, we send scoping and a quote for the diagnostic within five business days.
Your information is in. You'll hear back by email within one business day with next steps. The diagnostic doesn't commit you to anything past it.
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