We don't throw solutions on top of your business. We build them from within.
Kept is our evaluation, and real value comes from real context. Before we propose a single solution, we go inside the business, map every workflow, and find exactly where it is quietly losing money. Other firms hope for a return after they build. We know it is there first.
Most AI investments don't pay off, because they are built without context.
The market is flooded with tools promising productivity gains. The numbers tell a different story.
AI use cases that break even within a year
Six in a hundred break even. The rest take years, or never do.
Source: Deloitte Generative AI Survey, 2025
2-4 yrs
The average enterprise payback period on AI.
Source: Deloitte Generative AI Survey, 2025
4.5 hrs
Spent each week correcting work AI got wrong.
Source: Zapier and Centiment Survey, 2025
The cause is always the same. The solution was designed before anyone understood the work it was meant to fix.
- Built on what someone thinks will help.
- Built without knowing where, when, and how the problem happens.
- The team has to adapt to the solution.
- Hopes for a return after launch.
- Built on what we have watched slow the work down.
- Built with full context of where, when, and how the problem happens.
- The solution fits the workday as it already runs.
- Knows the return before the build starts.
A solution is only as good as the context it is built on.
To build something that fits, we need context at three levels. Most firms only ever get the first, from the founder's pitch.
The business
How it makes money, what success looks like, and where strategy meets execution.
The workflow
How work actually flows, where it breaks down, and where it sits idle between steps.
The employee
What each person actually does day to day, what frustrates them, and what they wish was automated.
Every evaluation opens with one question: are we saving you money, or making you more?
The two are different engagements. They measure different things and lead to different recommendations. We ask rather than assume, and many engagements blend both.
For lowering operating cost, freeing up capacity, and automating manual work. We map your operational architecture, the workflows and the manual tasks.
What we measure
For growing faster, lifting conversion, and scaling a funnel that already works. We map your revenue pipeline, the funnel and the customer journey.
What we measure
Before we recommend anything, we baseline your business on the seven metrics that actually predict scaling.
Most agencies talk about impact without measuring it. We measure first. Every leak we surface and every solution we propose is scored against its measured impact on the metrics that drive your business. Recommendations are only made once the baseline is established.
Money In
Your revenue engine.
Revenue, growth rate, new customers per month, CAC, NRR.
Money Out
Your cost engine.
Operating cost, cost per transaction, variable vs fixed split.
Money Kept
Profitability.
Gross margin, operating margin, EBITDA.
Efficiency
Output per input.
Revenue per employee, Labor Efficiency Ratio, Process Cycle Efficiency.
Speed
Time-based flow.
Sales cycle, time to revenue, order fulfillment, cash conversion.
Quality
Defects and retention.
Error rate, rework rate, First Pass Yield, churn, NPS.
CapacityConstraint
The scaling constraint.
Throughput, utilization, headcount growth vs revenue growth ratio.
The capacity metric is the one that caps your scale. Per Goldratt's Theory of Constraints, any improvement that does not help the bottleneck is wasted. We identify your specific constraint metric and prioritize against it.
~$215K
Median revenue per employee in the mid-market US.
> 2.0
Healthy Labor Efficiency Ratio.
< 20%
Where most organizations sit on Process Cycle Efficiency before optimization.
When we tell you a solution has $89,000 of annual impact, you can trace that number back through this tree to the exact metric it moves.
Every evaluation runs on CORE 1.
CORE 1 is our simulation engine. It learns how your business actually runs, tests every move against your real numbers, and surfaces only the few that pay. The depth of analysis a top firm needs months for, run on your data in days. You do not have to understand the engine. You just get the answer it proves.
Built on your real workflow data, not benchmarks. CORE 1 is the first model in a line we sharpen with every company we work with.
What CORE 1 hands back
A structured read of your business, not a deck of opinions.
CORE 1 divides your business into its real parts and works each one on its own. It identifies the moves worth making, scores every one of them across the categories that decide whether a fix is worth it, and ranks what is left by what it returns. You get the few that pay, sorted and explained, with the reasoning attached.
Every move scored across
Validated methodology
One method. Same as McKinsey, BCG, and Bain. Run by CORE 1, in days, not months.
We did not invent operational evaluation. We codified what the top consulting firms refined over decades, then built CORE 1 to run it: a simulation engine that does the analysis those firms need months for, in days.
We didn't invent the process. We made it faster.
30-60%
Operations cost reduction via RPA and cognitive automation.
Source: McKinsey Quarterly, 2026
1,200
Historical transformations that validate the OEI methodology.
Source: McKinsey & Company, 2024
Not every problem is worth solving. We tell you which ones are not.
Once every leak is on the table, we score each one. Some are bleeding real money. Some cost less to live with than to fix. If a problem cannot return more than it costs to solve, it goes on the keep-your-money list, and we tell you to leave it alone.
What we recommend, each item carrying its expected return, payback period, and a sensitivity range. The problems worth solving, ranked.
What we found that is not worth fixing, and why. For example, a weekly reconciliation one person handles in a few hours. Automating it would cost more than it would ever save, so the verdict is to keep your money and leave the task as it is.
What we surfaced that does not materially touch any core metric. Real inefficiencies, just not ones worth your attention. Background noise. Example: weekly Slack notification noise surfaced from employee interviews. Costs maybe an hour a month across the team. Ignore. This list exists so you can trust the build list, because we have proven we will tell you when something is not worth doing.
383%
Return over three years from process-mining-based automation, with a six-month average payback.
Source: Forrester Total Economic Impact study (Celonis), 2025
Other firms recommend everything they can build. We put the things we tell you not to build in writing, on two separate lists. No other consulting firm does that.
The same diagnostic from a McKinsey, BCG, or Bain team is a six-figure to seven-figure engagement. We run the identical process with AI, and price it to the size of your business.
The evaluation does not just answer. It preserves how your business runs.
Everything CORE 1 captures, how the work actually gets done, who does what, and where the value moves, becomes yours to keep. If an owner steps back or a key person leaves, that knowledge does not walk out the door with them. You hold it, structured and usable, long after the evaluation ends.
See what a Kept evaluation would find in your business.
It starts with a short, confidential assessment. We size the evaluation to your business, then CORE 1 does the rest.