AI Assessment
A fixed-scope diagnosis of where AI creates real value in your operation, quantified in hours and dollars, with a written roadmap you keep. Every engagement starts here.
Production AI systems for companies anywhere, operated by the engineer who built them.
I assess where AI actually creates value in your operation, build the systems that earn their place, and then operate them, so they're still working correctly a year later, after the models they were built on have been replaced twice. The work is remote-first everywhere, including twenty minutes from my own door, because the systems live in your cloud accounts rather than in a conference room.
Paid assessment from $2,500 · Remote-first, United States · Based in Lindale, TX
100%
Remote-first delivery
2 wks
Assessment turnaround
$2,500
Fixed-scope assessment
30 yrs
In technology · 10 in SRE
Nothing I deliver is something you could have received in person.
The output of this work is code running in your cloud accounts, pipelines wired into software you already pay for, dashboards your team opens on a Monday, and a monthly report of what the system did and what it got wrong. None of that arrives in a briefcase. The parts that look like they need a room, the interviews and the process walkthroughs, turn out to need a screen share, because what has to be seen is the ticket queue, the shared inbox, and the spreadsheet somebody has rebuilt three times.
The operating half settles the question outright. Production systems fail on their own schedule, and the response to a 3 a.m. degradation has never involved getting in a car. I've spent a decade doing exactly that for large enterprises, on call, from wherever I was. A vendor who can only help you between nine and five in your city is a vendor who cannot help you when it actually matters.
Distance is not what kills these projects. What kills them is a system nobody is watching, and that fails the same way whether the consultant was in the building or not.
I'm Byron Walker, a Staff Site Reliability Engineer with thirty years in technology and a decade spent keeping large enterprise systems online. That background is the whole argument. Most AI projects don't fail at the demo. They fail at 2 a.m. three months later, when a model update shifts behavior or an upstream schema changes and nothing throws an exception. I build AI systems the way production infrastructure gets built: instrumented, independently verified, and honest about what they got wrong. Then I operate them, because a system nobody maintains is a system quietly going out of date.
The assessment decides which of these matter.
Not a menu to shop from. These are the categories the work falls into, and for most companies, the honest answer is that two of them matter and the rest don't.
Agent Systems
Multiple agents with separated responsibilities: detect, decide, act, and independently verify the work happened. Verification is its own agent, not the actor grading itself.
Document & Data Pipelines
Contracts, claims, invoices, and field reports read, extracted, validated, and written into your systems of record, with confidence thresholds that route exceptions to a human.
Systems Integration
Wired into your ERP, CRM, ticketing, and the internal tool from 2011 that nobody documented and nobody can replace this year.
Custom Software
Purpose-built internal applications and customer-facing products for how your business actually runs, designed and coded, not templated.
Operate & Maintain
The part nobody else stays for: 24/7 monitoring with degradation alerting, model migration against a regression suite, and a monthly report that shows the failures.
Mid-market companies with real operational complexity, wherever they happen to be.
Roughly 50 to 500 employees. Manufacturers and distributors with order-to-cash processes spanning systems that were never designed to talk. Insurance, financial, and professional services firms where a document queue is the whole job. Healthcare administration groups drowning in credentialing paperwork, vendor invoicing, and supply-chain documents, meaning the non-clinical side; patient data stays out of scope by design. Energy and field services companies whose data arrives as photographs of paper.
The common thread isn't industry or geography. It's a process that's expensive, high-volume, currently done by people doing the same thing repeatedly, and important enough that getting it quietly wrong would be a serious problem. That last part is why verification architecture is the center of how I build rather than a feature bolted on at the end.
It's worth being equally clear about who this isn't for. If you want a proof of concept to show a board, a chatbot on your website, or a pilot nobody intends to operate, there are cheaper places to get one. If you need a team of ten starting Monday, this is one engineer and I'll say so. And below about twenty employees the economics don't work at these prices, which is a thing I would rather tell you now than discover together in week three.
Nothing I build fails silently. You get a monthly report of what ran, what escalated, and what it got wrong, with the receipts. The wrong-answer section is in every report, including the clean months.
Everything ships in your accounts, in your name, with documentation and team handoff at delivery. No proprietary runtime, no black-box middleware. If you cancel the retainer, the system keeps running and any competent engineer can pick it up. That's a deliberate design constraint, not an accident, and it matters more at a distance, not less: you should never be locked in to a vendor by anything other than the quality of the work.
See the standard every system I build reports against on the reliability page, a working demonstration of the verification architecture, including a button that injects a silent failure so you can watch it get caught. The incident platform case study covers how agents with real authority get built and verified, and engagement pricing is published in the open.
Remote AI consulting, answered plainly.
Do you work with companies outside Texas?
Yes, and the engagement is identical. Video calls, screen shares, a shared repository, and access to the systems the process touches. East Texas clients get the option of discovery in person because I happen to live there, which is a convenience rather than a different service.
How does a remote assessment actually run?
Two weeks, fixed scope. Interviews with the people who do the work rather than the people who describe it, read-only access to the systems involved, a written map of where the hours go, and a quantified list of what's worth building, with cost and return attached to each item. You keep the report whatever you decide next, including if the finding is that you shouldn't build anything yet.
What time zone do you work in?
Central. Eastern through Pacific is a normal working day from here, and anything under an operations retainer carries written acknowledgment windows that don't depend on where you are. Those windows are in the agreement rather than agreed informally per client, which is the only version of a response time that means anything.
How much does it cost?
The AI assessment is $2,500, fixed scope, two-week turnaround, with a written report that's yours regardless of what happens next. Systems builds start at $18,000 fixed price, quoted after the assessment. Operations retainers start at $3,500/month for a single system, rising with what's under management, month to month. Full detail on the engagements page.
Why isn't there a free consultation?
Because a free consultation is a sales call, and it produces a proposal shaped like whatever the consultant already wanted to sell. A real assessment means interviewing the people who do the work, mapping undocumented systems, and quantifying opportunities against your actual volumes, which is a week of engineering effort. Charging for it means the findings are yours regardless.
How do you handle our data if you're never on site?
The same way it should be handled if I were. Third-party accounts are in your name from day one, access is scoped to what the work requires, and what gets collected, where it lives, and how long it's kept is published on the data handling page rather than described on a call. A data processing agreement goes out with the statement of work instead of waiting for your counsel to ask for one.
Find out what AI is actually worth in your operation.
A fixed-scope assessment, delivered in two weeks, with a written report you keep. You'll know what's worth building, what it costs, and what it returns. You'll also know which items aren't worth doing at all.
Start an Assessment ↗Prefer plain email? byron@walkeraisystems.com