Houston · Forward Deployed AI Engineering
AI, set up right,
inside your business.
Autom8 Studio builds working AI tools for companies and trains the teams that use them. Not courses, not slide decks — deployed software. We've done it inside the IT organization of a Fortune 5 energy major, and we run our own studio on the same systems.
95%
of enterprise AI pilots show no profit-and-loss impact, per MIT's 2025 study — after $30–40B spent.
64%
of Copilot licenses sit idle. Buying software isn't the same as getting your team to use it.
2×
Vendor-led deployments succeed twice as often as internal builds. The problem isn't the models. It's deployment.
How it works
Three steps, each with a fixed price and a fixed scope. Start small, see results, then decide.
Step 1
AI Readiness Audit
Fixed fee · 2 weeks
We walk your actual workflows with your team and find where AI pays for itself — and where it doesn't.
- Written roadmap with a build order
- Cost and time estimate per opportunity
- Data, security, and vendor review
- Yours to keep, no obligation past it
Step 2
Pilot Build
Fixed scope · 30 days
One working tool solving one real problem, deployed to your team. This is where most AI consultants hand you a deck; we hand you software.
- Deployed, working tool — not a demo
- Security and access control built in
- Documentation your IT will accept
- Team training included
Step 3
Enablement Retainer
Monthly · cancel anytime
We keep your tools running, train new people, and ship the next automation on the roadmap each month.
- Maintenance and model updates
- Ongoing team training
- A steady build queue from your roadmap
- Direct line to the builder
The forward deployed model
The industry calls this forward deployed engineering: an engineer embedded in your business, building on your real data and workflows until the system runs in production. It's the model OpenAI and Microsoft now sell to the Fortune 500 at eight-figure prices — we do the same work, sized for Houston companies.
Embedded doesn't mean permanent. Every engagement has written success criteria, a knowledge-transfer plan, and an exit. We stay until it runs, train your team to own it, and leave you independent — not renting an engineer forever.
Pilot to production, one workflow at a time. Time-to-value is measured in weeks, not quarters.
What "set up right" means
Most companies that try AI get a chatbot subscription and a policy memo. Six months later nobody uses either. Setting AI up right means picking the few places in your operation where it actually pays, building tools your team uses without thinking about it, and keeping your data where it belongs — under your control.
We handle the parts the hype skips: data governance and PII handling, access control, human review steps where mistakes are expensive, private deployment in your own tenant when the data is sensitive, and documentation that passes your IT department's vendor review. If your team is already pasting company data into free chatbots — that's called shadow AI, and it's more common than you think — we'll help you write the acceptable-use policy that ends it. Every build ships with training for the people who'll run it, because adoption is the metric that matters, not licenses.
If a workflow shouldn't use AI, we'll tell you that too. The audit is honest or it's worthless.
Built and running today
Working systems, not case-study vapor.
AI writing coach — Fortune 5 energy major
A brand-compliance writing evaluator used by the IT communications team of a Fortune 5 energy company. Scores drafts against the corporate style guide before they ship.
Enterprise intranet — same organization
An internal communications site built and maintained inside the same Fortune 5 IT organization, on their standards and their review process.
CaseGrader — automated legal intake
An automated case-evaluation tool for a Houston personal-injury firm. Qualifies leads before staff spends a minute on them.
The studio behind this practice
SLFEMP Studio runs on systems we built: a client portal with AI-assisted estimates, automated invoicing and delivery, and a local AI production pipeline. We sell what we use.
Who you're working with
Autom8 Studio is the AI implementation practice of SLFEMP, run by Michael "Frost" Moore — 13 years inside the IT organization of a Fortune 5 energy company, where he builds and ships internal tools, including the AI systems above. Enterprise standards are the default here, not an upgrade.
You work directly with the person who builds your tools. No account managers, no handoffs, no offshore build team.
Start with the audit.
Two weeks, fixed fee, a written roadmap you keep either way. If AI doesn't pay in your operation, the audit says so.