Operational intelligence engineered
The team at Tolbau AI finds the leaks and builds the systems that close them. We diagnose before we build, and we build for production, not for a pilot that quietly dies in month four.
Why now
Adoption is close to universal. Real integration is close to nonexistent. Industry research through 2026 indicates roughly 78% of organizations now use AI in at least one business function, while only about 7% have integrated it deeply into operations, and a majority of enterprise deployments stall before reaching production.
The bottleneck was never model quality. It is the plumbing: systems that were never designed to talk to each other, workflows nobody redesigned, and no one accountable for what happens when it breaks at two in the morning.
AI amplifies whatever system it is dropped into. Drop it into a broken process and you get a faster broken process. That is why this work needs an architect rather than another subscription.
Figures compiled from 2025–2026 industry research on enterprise AI adoption and implementation. Directional, not universal constants.
The method
Most vendors sell you the build and find the problem afterward. We work the other way, because a system built against the wrong leak is an expensive way to stay exactly where you are.
Where work enters, where it stalls, where money exits. We look at the systems and the handoffs, not a questionnaire. You get the leak named in dollars whether or not you hire us to fix it.
You get the design, the boundaries, and a plain list of what we are deliberately not building. Scope creep is how these projects die, so we settle it before anyone writes code.
Logging, escalation paths, rollback planning, failure alerts, and a human in the loop wherever a human belongs. It ships when it can survive a bad day, not when the demo looks good.
The product family
Each one closes a specific hole. They are sold separately, they run on the same engineering core, and every one of them can be demonstrated live rather than described in a deck.
One deterministic engine reads every call the same way and writes a scored record: what was said, where the deal died, and what it cost. Same call in, same answer out, with every finding quoted and timestamped. Prohibited-phrase alerts fire the moment a call ends rather than in next month's review.
Answers the phone and the text thread on one brain with one memory of the same person. Qualifies against criteria you set, answers questions from a defined knowledge base, and books straight into the calendar. It hands off to a human rather than guessing, and it does not negotiate price.
Watches for leads that have gone dormant and drafts a follow-up matched to where each one actually stopped. A lead that ghosted after a quote gets a different message than one who never answered the first call. Drafts are queued for review. You decide what goes out. CRM-agnostic by design.
Monitors open work against the SLA windows you define and alerts before a breach instead of after the client notices. Elapsed time is arithmetic, never inference. The language model is used only at defined judgment points, and every alert traces back to the rule that fired it.
When nothing on the menu is the answer. We map the operation, find the leak, and build the system for it — integrations across tools that do not talk, internal workflow that outgrew the spreadsheet, and the connective work people are currently doing by hand.
For work where the data cannot leave the building. Systems designed to run inside infrastructure you control, on storage and models you own, with audit trails that belong to you rather than to a vendor. Scoped against your constraints before anything gets designed.
How we build
Most conversations about AI skip this part until it becomes a problem. It is the first thing we settle, because it changes what can be built at all.
Who built this
Lo Tolliver has spent more than ten years delivering inside enterprise production environments across multiple technical disciplines — infrastructure, migrations, CI/CD, authentication, legacy modernization — the kind of work where an outage has consequences and the vendor's slide deck stops mattering around hour three.
The pattern was the same in every organization: the leak was never the tool. It was the system nobody had designed. Work entered through five doors, stalled somewhere nobody was watching, and by the time anyone noticed, the money was already gone.
A demo that looks cool is not proof that the thing works.Lo Tolliver, Founder
She started Tolbau AI to build what she kept looking for and never found. Today the team builds those systems for other operators and holds them to the same standard: it has to survive production, and it has to survive the technical questions.
Straight answers
A tool assumes your process is already correct and just moves it faster. We look at the process first and name the leak in dollars. If the honest answer is that you do not need us to build anything, you will hear that too.
Case by case. If what you need is already in our arsenal, it moves fast. If it is a custom build, it moves at the speed of your requirements. Which one you are is what the consultation is for.
Priced against what the leak is costing you, not against our hours. Nobody has ever made this decision off a number on a website, so the number comes after the diagnostic, in writing.
Start here
We will tell you if you are right. Fifteen minutes on the phone is usually enough to know whether there is something here worth building.
