Ship AI before the committee finishes the spec.
We build the systems, sit at the leadership table, and train your people to run them. Working software that moves the P&L, live while everyone else is still scheduling the kickoff.
Not sure where to start? Take the 3-minute AI readiness checkBuild · Consult · Train | Miami, FL and remote across the US
Trusted by teams in
- Legal
- Real Estate
- Logistics
- Healthcare
- Financial Services
- Enterprise tech
- 20 yrs
- Revenue influenced
- $10M+
- Platforms shipped
- 3
- People trained
- Hundreds
Google SRE, BMW cloud and ML, Fashion Nova data science
Through AI strategy work
Claresto, iExcel, ClearPitch AI
Free AI programs for Miami residents and youth
Sound familiar
The licenses are paid for. The work still runs on spreadsheets.
Buying AI was the easy part. These are the four places it usually stalls.
The pilot demoed well in March.
It is still a pilot. Nobody owns getting it to production, so nobody does.
Everyone has a seat. No workflow changed.
The licenses renew every year. The spreadsheets and the copy-paste are still there.
Legal asked for an audit trail.
There is no log of what the system did or who approved it, so the project stops at review.
The vendor roadmap became the strategy.
Priorities get set by whatever the platform ships next, not by where your money leaks.
None of these are model problems. They are ownership, money, and governance problems. That is what we fix first.
What we do
Three ways in. One standard of work.
Most firms sell you strategy or code. We do both, then hand your team the keys.
01 / Build
Build
Custom AI software: agents, workflows, automations, voice AI. We ship production systems that run inside your stack, on your data, under your controls.
- Agents and multi-step workflows
- Voice and document automation
- Evals, logging, and rollback
02 / Consult
Consult
Fractional Chief of AI. Strategy, roadmap, architecture, governance, and board-ready reporting from an operator who has run systems at scale.
- 90-day embedded engagements
- Architecture and vendor review
- Governance and board reporting
03 / Train
Train
Executive briefings, team workshops, hands-on enablement, and keynotes. Your people leave able to use the systems, not just talk about them.
- Executive and board briefings
- Role-specific team workshops
- Keynotes and live sessions
Out of band
None of this was in the manual.
A few real moves from the last year. They say more about how we will attack your problem than any capabilities deck.
- 01
Our agents sleep while the overnight meter runs and wake at 5 AM. Same output, smaller bill.
Cost - 02
OpenAI's CEO asked the internet what AI should solve. We pulled the replies, sorted them by category, and read the market straight off the chart.
Research - 03
Retired a paid scraping vendor. An open-source scraper paired with a coding agent now pulls the ad-library data we used to rent.
Tooling - 04
Chained a music model to a stem separator that was never built to talk to it. Together they do something neither tool ships on its own.
Media - 05
When one model would not follow instructions, we had a different model write its instructions.
Models - 06
Switched model providers the week one stopped earning its seat. Loyal to results, not logos.
Vendors
By department
Every department has work a machine should be doing.
Common starting points. The assessment and the first two weeks rank them against your actual volumes and costs.
Sales
- Lead qualification by voice and chat
- CRM updates that happen without reminders
- Proposals drafted from call notes
Marketing
- Ad operations monitoring and alerts
- Creative and copy variants at volume
- Market and competitor research on a schedule
Operations
- Document intake and extraction
- Scheduling, routing, and handoffs
- Reports that assemble themselves
Support
- Voice agents that answer every call
- Triage and routing with human review
- Answers grounded in your own docs
Finance
- Invoice and receipt processing
- Reconciliation exceptions surfaced early
- Board and ops reporting drafts
How we work
A 90-day cadence, not an open-ended retainer.
Four phases. Clear exits. You know what you are getting and when, before we start.
- 01Weeks 1 to 2
Assess
We map the workflows, the data, and the money. You get a ranked list of where AI actually pays and where it does not.
You get
- Workflow and cost map
- Ranked opportunity list
- What not to build, and why
- 02Weeks 3 to 4
Architect
System design, model selection, integration plan, guardrails, and a cost model your CFO can read without a translator.
You get
- System design and model choice
- Integration and guardrail plan
- Cost model for finance
- 03Weeks 5 to 10
Build
We ship working software in your environment. Evals, logging, and human review are in the first release, not the backlog.
You get
- Working release in your stack
- Evals, logging, review queue
- Weekly demo of shipped work
- 04Weeks 11 to 13
Enable
Runbooks, training, and handover. Your team operates it. We stay on a cadence, not a leash.
You get
- Runbooks and handover docs
- Team training on the live system
- Next 90-day recommendation
Every 90 days we re-scope.You either renew because the work earned it, or you walk with a system your team already runs.
Talk through your first 90 daysWho you are hiring
Twenty years of enterprise tech, pointed at your operation.
AI Success Partners was founded by Micah Berkley, a Brown University computer scientist who spent two decades building and running systems at scale before AI became a line item on every board agenda. Site reliability at Google. Cloud architecture and machine learning at BMW of North America. Big-data marketing science at Fashion Nova.
He has architected and shipped production platforms including Claresto, iExcel, and ClearPitch AI, influenced more than $10M in revenue through AI strategy, and trained hundreds of Miami residents and young people through free programs. Builders outrank talkers.
Off the clock he holds a U.S. Coast Guard 200-ton Master Captain license. He got it for fun.
Google
Site Reliability Engineering
BMW of North America
Cloud architecture and ML
Fashion Nova
Big-data marketing science
Brown University
Computer Science
Miami Herald
Front page feature, 2023
Adobe
AI Change Maker, 2024
Additional press: National Law Review, Florida Herald. Speaking: GPTuesday, DeepStation, Miami Dade College.
Why teams pick us
Receipts over theory.
Four commitments we make on every engagement, written down before the contract is signed.
Production-grade
Demos are easy. We build for uptime, latency, cost, and the bad day. If it cannot survive a Monday, it does not ship.
Governance built in
Access controls, audit trails, evals, and human review from day one. Secure your stack before you scale it.
Your team owns it
No black boxes and no hostage code. You get the repo, the runbooks, and the people who can run it without us.
Model-agnostic
We run whichever model wins on your evals this quarter, and we design so switching next quarter costs a config change, not a rewrite.
Security and control
Your data stays where your auditors expect it.
Procurement, legal, and IT get their answers before the build starts, not after the demo.
Runs in your environment
Your cloud, your accounts, your keys. The system lives where your auditors already look.
Access and audit
Role-based access, plus a record of what the system did, when, and on whose behalf.
Evals before scale
Each release is tested against cases you approve before it reaches more users.
Human review where it counts
Approval steps on the decisions you choose. Not everywhere, and never nowhere.
Model-agnostic, in practice. What we ship with.
- Anthropic Claude
- OpenAI
- Google Gemini
- Open-weight models
- Replicate
- Voice AI platforms
- Google Cloud
- Cloudflare
- Your CRM
- Your ERP
- Your data warehouse
Free AI readiness assessment
Eight questions. Three minutes. An honest read.
Find out whether you should start with training, strategy, or a production build, plus the first three moves. Scored in your browser. Nothing is sent.
Insights
Notes from the build.
What we are learning shipping AI inside real companies.
Consult
The Fractional Chief of AI: what a 90-day embed actually looks like
Not a workshop. Not a slide deck. An embedded operator who sits in your leadership meetings, makes architecture calls, and leaves your team running something real after 90 days.
ReadBuild
Build vs buy for AI agents: the decision framework
Most build-vs-buy debates about AI agents skip the question that actually decides it: is this workflow your differentiation, or your overhead. Here is the framework we use.
ReadStrategy
Why most enterprise AI pilots never ship
Pilots are built to impress a room. Production is built to survive a Monday. Most teams design for the first one and wonder why the second one never comes.
ReadQuestions
The things buyers ask first.
Straight answers. If yours is not here, ask it on the call.
Most stalled projects share the same causes: no owner, no connection to a number that matters, and no path through legal review. Our first two weeks exist to fix those three things before any code gets written. If we cannot tie the work to money, we will say so.
Less than people expect. We need a sponsor with decision rights, one person who knows the workflow cold, and access to the systems involved. Everyone else meets the system when it is ready to use, during enablement.
Assessment findings land in the first two weeks. Working software is typically in your environment inside a quarter. We scope so there is a usable release before the engagement ends, not after it.
An embedded senior operator inside your leadership team on a 90-day cadence. Strategy, architecture, vendor calls, governance, and board reporting, without adding a permanent executive line to payroll.
Yes. Most engagements start with software you already pay for. We are model-agnostic and cloud-agnostic, and we will tell you when the answer is to use what you have rather than buy something new.
You do. Code lands in your repositories, systems run in your environment, and your data stays under your controls. Handover documentation is part of the deliverable, not an upsell.
Mid-market through enterprise. Typical buyers are the CEO, COO, CTO, CIO, VP of Operations, or the head of innovation. The common thread is a real workflow with real money attached.
Yes. Executive briefings, workshops, and keynotes stand on their own. Many clients start there and move into Consult or Build once the leadership team is aligned.
Next step
So. What are you building?
Bring the workflow that costs you the most. One call, and you leave knowing what ships first, what it costs, and what we would skip.