Aburto AI
Your AI-powered business decision partner
A Growth Architect that learns your business before telling you what to do.
Aburto AI continuously builds an understanding of your financials, customers, operations, priorities and decisions — then helps identify what may be limiting growth, profitability or business strength.
Not another dashboard. Not generic business advice. A decision partner built to understand the business behind the question.
- Financials
- Customers
- Marketing
- Operations
- Pricing
- Capacity
- Cash
- Decisions
- Financials
- Customers
- Marketing
- Operations
- Pricing
- Capacity
- Cash
- Decisions
The problem
Business owners rarely suffer from a shortage of information.
They suffer from a shortage of clarity. The pieces exist — they just live in different systems, and none of them is responsible for the question that actually matters.
- Your accounting systemknows the transactions.
- Your CRMknows the customers.
- Your marketing platformsknow the leads.
- Your teamknows what is happening operationally.
- Youknow the business better than anyone.
But those pieces rarely come together to answer what actually matters most right now.
The difference
Most AI starts when you ask a question. Aburto AI starts by understanding the business.
The distinction is not how good the answer sounds. It is what the system knew before you asked.
General-purpose AI
- You ask a question.
- You supply the context.
- It responds.
- The conversation ends.
Aburto AI
- Builds persistent business context.
- Connects the signals that matter.
- Remembers previous decisions.
- Watches what changes.
- Flags what deserves attention.
- Measures what happened.
- Updates its understanding.
The goal isn’t to know more about business in general. It’s to understand your business well enough to help you think more clearly about what comes next.
How it thinks
A reasoning protocol, not a prompt.
Ten stages. The system does not stop at a recommendation — measuring what happened and learning from it is what separates a decision partner from an answer generator.
- 01Understand the business
Build a structured picture of how the company makes money.
- 02Watch the signals
Financials, customers, operations, pricing, capacity, cash.
- 03Notice what changed
Classified, not arrowed. Up is not good and down is not bad.
- 04Investigate
Rule in, rule out, and say what cannot yet be separated.
- 05Name the priority
What deserves attention, ranked by consequence.
- 06Develop options
Alternatives before the recommendation, each with preconditions.
- 07Apply the practicality filter
Capital, owner hours, reversibility, time to learn.
- 08Recommend
With evidence, confidence and what would change it.
- 09ApproveHuman
The owner decides. Nothing acts without this.
- 10Measure and learnHuman
Expected against observed — then back to the business memory.
- L0Observe
- L1Analyze
- L2Flag
- L3Recommend
- L4Decide / act
Levels 0 to 3 are what the system does on its own. Level 4 is narrow, explicitly authorized, and belongs to you. Aburto AI does not make unrestricted strategic decisions, and it is not designed to.
Six intelligence layers
Not one model producing one answer.
Six layers, each answering a different question and each reading the ones beneath it. The last one writes back — which is why the system gets better at your business over time rather than simply accumulating more of it.
- 01Financial Intelligence
What are the numbers telling us?
Revenue, margin, cost structure, cash, and the evidence class of each.
Depends onThe connectors and what the owner has confirmed
- 02Business Model Intelligence
How does this business create economic value?
Where money is actually made, by service line and customer type.
Depends on01
- 03Company Intelligence
What is true about this specific company?
Constraints, capacity, people, commitments, history.
Depends on01, 02
- 04Decision Intelligence
What decision deserves attention?
The open questions, ranked, with what would answer them.
Depends on01–03
- 05Action Intelligence
What should happen next?
The next practical move, and what it should produce.
Depends on04
- 06Outcome Intelligence
What did the business teach us?
Expected against observed, and what changed as a result.
Depends on05 — and writes back to 01–05
The principle
The best business advice starts by understanding the business.
Aburto AI isn’t designed to produce an answer as quickly as possible. It is designed to determine whether there is enough evidence to give you a useful one.
Which means it has to be willing to say we don’t know yet — and to say what would change that. A system that always has an answer is a system that will eventually invent one.
What it helps you answer
Nine questions, not nine features.
Every one of these is answered by a real screen, and the screen is named. A feature list would be easier to write and impossible to check.
- 01How is the business really performing?
Five executive indicators selected against your goal, each with a reading.
Business at a glance - 02What changed?
Classified rather than arrowed, because up is not good and down is not bad.
Today - 03Why?
Ruled in, ruled out, and what still cannot be separated.
My Business - 04What deserves attention?
Three things, ranked by consequence, urgency, confidence and goal relevance.
Today - 05What is holding us back?
The constraint, named — and the evidence that would confirm it.
Plan - 06What opportunities are realistic?
Each with evidence, expected value, effort and a next test. No generic opportunity lists.
My Business · growth - 07What decision matters most?
Options with preconditions, run through the practicality filter.
Decision Brief - 08What should we do next?
Three actions with an owner, a duration and what each should produce.
What I would do next - 09What happened after the decision?
Expected, observed, variance, and what it changed.
Decisions · outcome review
The methodology behind Aburto AI
It is not a model with a business vocabulary. It is a way of working, made continuous.
Every screen in this product is a step of a method that already existed. The order is the argument: understand the business before diagnosing it, diagnose before recommending, develop the options before choosing one, prefer the reversible move, and measure what actually happened.
- Understand first
Build a structured picture of how the company actually makes money before offering a single opinion about it.
- Diagnose carefully
Separate what the evidence rules in from what it rules out, and say plainly what it cannot yet separate.
- Evaluate options
Develop the alternatives before the recommendation, and state what would have to be true for each one.
- Act practically
Prefer the cheap, reversible, fast-learning move over the impressive one. Most businesses do not need a bigger idea.
- Measure what happens
Write the expectation down at decision time, then come back and check it. This is the step almost everyone skips.
Tayde does not personally review each recommendation. Aburto AI applies the methodology; it is not a channel to him, and the product says so rather than implying otherwise.
The product
What it actually looks like.
Six real states from the business-owner experience. These frames are rendered from the product’s own components and the product’s own demo business — not redrawn for marketing — so this page cannot promise a screen that does not exist. The business shown is Meridian Field Services, a fictional 19-person HVAC service company. Every figure is illustrative.
Day 88 · Meridian Field Services
Your business is growing, but profit isn't keeping pace.
Three things that matter
- 01Profit is falling while revenue grows
Operating profit is down 17.8% across four periods while revenue rose 15%.
- 02The margin decline is labour, and only labour
Labour rose 530bp; materials improved 160bp; overhead is flat.
- 03One decision is waiting on evidence you don't have
The hiring question cannot be answered until utilisation is measured.
Business at a glance
- Revenue+15%4 periods
Growing, and it is not the problem.
- Gross margin38.1%−370bp
Where the money is going.
- Operating profit8.5%−340bp
Almost all of the decline arrives through gross margin.
- Cash41 days−6 days
Receivables, by a decision you made.
- Capacity6 days+2 days
Quoted-to-scheduled interval, rising every window.
What I would do next
- 01Export ninety days of dispatch records20 min
- 02Request price schedules for the two remaining supply categories10 min
- 03Confirm the Day 52 payment terms with your two largest accounts20 min
The synthesis comes first, in writing. One sentence at the top of the screen saying what is going on, before any number appears. A dashboard shows the numbers and asks the owner to work out what they mean; this has already done it. That single choice is most of the difference between the two products.
Decision brief · raised by you on Day 81
The decisionShould we hire a twelfth technician?
Not yet.
- My read
- Demand looks strong enough to justify investigating capacity, but the evidence does not yet show that headcount is the constraint. The backlog is real; what is causing it is not established.
- Why
- Three explanations for the scheduling backlog are still live — capacity, dispatch sequencing, and your own approval time on quotes above $15,000. Two of them are free to fix. Hiring commits about $95,000 a year of fixed labour to a business whose problem is already labour as a share of revenue.
- What I would do first
- Measure technician utilisation for two weeks.
- What it will take
- Cost$0
- Your time~30 minutes
- Team timeDispatcher, 20 minutes
- Time to learn2 weeks
- ReversibilityHigh
- RiskTwo weeks pass before any hire
- If the evidence says yes
- Build the hiring economics: maximum sustainable compensation against the profitable backlog, and whether a twelfth technician or overflow subcontracting reaches breakeven faster.
- If the evidence says no
- Investigate scheduling sequencing and your approval path before adding payroll. Both are free and one of them is a calendar change.
- When we review
- Day 108 — after two weeks of operating evidence.
- Confidence
- MODERATEInferred from financial and CRM data
A recommendation that says “not yet”, and shows what it would take to say yes. Eleven blocks, no chart, and both branches written before the owner commits thirty minutes. The product’s most valuable answer is often that the evidence does not support a decision this expensive — and it has to be able to say so in a format that still looks like advice.
- 01Export ninety days of dispatch records
- Why
- To separate a scheduling problem from a headcount constraint
- Who
- Your dispatcher
- Effort
- 20 minutes
- When
- This week
- Produces
- Billed hours against available hours, by service line
- Then
- I reassess the hiring recommendation
- 02Request price schedules for the two remaining supply categories
- Why
- The last unblocked margin action on the board
- Who
- You
- Effort
- 10 minutes
- When
- Monday
- 03Confirm the Day 52 payment terms with your two largest accounts
- Why
- About $165,000 is in receivables because of a decision you made deliberately
- Who
- You
- Effort
- 20 minutes
- When
- Within two weeks
Total owner time · 50 minutes
Three actions that fit in fifty minutes, each with what it should produce. An action here is not a task — it names the evidence it exists to generate and what happens once it lands. No board, no assignee dropdown, no percentage complete.
Gross margin has fallen 370 basis points across four periods while revenue grew 15%. Materials improved 160bp; labour rose 530bp. Overhead is roughly flat as a share of revenue, so almost all of the operating-profit decline arrives through gross margin.
Inferred from four trailing periodsMaterials −160bp · Overhead −30bp · Labour +530bp
- Not demandRevenue per employee improved from $409,000 to $446,000.
- Not sales productivityLeads are up 31% and conversion up 3.3 points.
- Not materialsThe supplier renegotiation delivered 70bp and is still delivering.
Whether the backlog is profitable. Labour is coded to payroll periods rather than to jobs, so revenue by service line is visible and cost by service line is not.
Insufficient evidenceThe reading comes before the chart, and the limit comes after it. The product says what the numbers mean, what that rules out, and — in the same type size — the one thing it cannot see and why. A number without a reading is a dashboard; a reading without a stated limit is a guess.
Operating profit above 11% without opening a third location.
- 01Resolve the labour-efficiency question
The margin decline is labour; what kind of labour problem is not established.
- 02Decide the capacity question on evidence
Hiring, sequencing and pricing imply different spending.
- 03Recover the working capital the Day 52 terms are holding
About $165,000, by a decision that may no longer be intentional.
- Hire a twelfth technicianBLOCKED · utilisation not measured
- Increase marketing spendBLOCKED · capacity assumption unverified
- Renegotiate the two supply categoriesREADY
Technician utilisation. Everything above waits on it, and two weeks of dispatch records would close it.
One goal, three priorities, three decisions and one unknown. Two of the three decisions are blocked, and the plan says what is blocking them rather than showing them as pending. A plan whose items cannot be blocked is a task list.
Should we hire a twelfth technician?
I’m looking at the same decision you are. I can explain my recommendation, challenge the assumptions, compare another option or help you work through the next step.
Why are you recommending this?
- My read
- Three explanations for the scheduling backlog are still live, and they imply opposite actions. Hiring is the only one of them that costs $95,000 a year before we know which is true.
- Why
- Labour rose 220bp to 36.1% of revenue while materials fell 70bp, so the margin decline is labour and only labour. But a labour problem can be too few people, badly sequenced people, or work priced before the rate moved — and those need different money spent on them.
- Next move
- The dispatch export. Two weeks, thirty minutes of your time, and it separates all three.
The owner never has to explain what they are looking at. The panel opens already naming the decision, and the answer keeps the same shape as the brief beside it — my read, why, next move, with its evidence intact. Being conversational is not permission to be careless.
Proactive intelligence
You shouldn’t have to ask whether anything is wrong.
A strategist who only speaks when spoken to is a reference book. Aburto AI is built to notice — and to be specific about what it noticed and how confident it is.
- Change detectedSomething moved that usually doesn’t.
- Pattern emergingTwo or more signals moving together.
- Assumption may have changedSomething a past decision relied on.
- Decision review dueEnough time has passed to measure it.
- Expected result not materializingThe recommendation isn’t working.
- Missing informationAn upcoming decision needs evidence you don’t have.
Three months ago the business increased marketing spend based on available operating capacity. Lead volume increased, but the scheduling backlog increased with it. The original assumption that capacity could absorb additional demand may no longer be true.
Demo business · illustrative data. No real company is represented.
Trust & control
Your business. Your data. Your decisions.
Aburto AI can analyze, identify, flag and recommend. In narrowly governed workflows, and only with your explicit authorization, it can act. It does not make silent strategic decisions, and the architecture is built so that it cannot.
- Business isolation
Your company’s data is scoped to your company at the database level, not by a filter someone remembered to write.
- Visible provenance
Every material claim can show its source, its date and whether it was measured, inferred or estimated.
- Human approval
Recommendations become actions when you approve them. Not before.
- Visible assumptions
What the system is assuming is shown alongside what it concluded.
- Confidence, honestly
High, moderate, low, or insufficient evidence. No invented percentages.
- Correctable memory
Everything the system believes about your business can be corrected by you.
- Auditable decisions
What was decided, when, on what evidence, and what happened next.
- No silent autonomy
Model-proposed rules are inert until a human ratifies them.
Bilingual intelligence
One business. Two languages. The same intelligence.
The presentation language changes. The understanding does not — there is one company profile, one financial context, one decision history, one business memory.
Briefings, priorities, recommendations and decision records.
- Company profile
- Financial context
- Priorities
- Decisions
- Outcomes
- Unknowns
Los mismos informes, prioridades y decisiones — no un perfil aparte.
Switching language does not create a second business profile, a second decision history or a second set of priorities. Spanish is not a translation layer bolted on at the end.
Aburto AI
Know what matters. Understand why. Decide what comes next.
Aburto AI is being built to help business owners understand what matters, make better decisions, and learn from what happens next. It is informed by the Business Growth Architect methodology — the same way of working, made continuous.
Stay informed as Aburto AI develops.
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Aburto AI is in development · early access is not yet open to the public