Meaningful volume
The workflow happens often enough for every saved minute to compound.
Silicon Valley
AI Agent Expertise,
Now in Miami
Prove your impact with a visible win in weeks.
Deliver a result that strengthens your mandate.
Lead the next chapter of operations with AI agents.
The real opportunity
You do NOT need another
AI transformation program
Most companies either aim too small with isolated AI tasks or too large with transformation programs that risk the operating model. The real value lies in the middle: handoffs, queues, context gathering, routine decisions, system updates, and follow-up
That middle layer is where most integrators struggle. They approach it from the product and service layer, wrapping tools around failure modes they cannot see. But those failures start lower: in how an agent observes, decides, recovers, and carries error into every layer above it. After 30+ years in software and 15 years in AI, I spent the last two years building five reinforcement-learning agent engines from the ground up, so I have watched those shortcomings form in the machinery, not in a slide.
That is why I work with Miami COOs on one expensive workflow at a time. You get operating leverage you can own, not another program papering over the real problem.
Common Approach
- Generic “AI consultant”
- Prompt-pack / training-only offers
- Broad AI agency for everyone
- Flashy AI demos and presentations
- Meetings only consulting
Our Approach
- Workflow-specific AI operator
- Guided implementation
- Deep technical, ground-up build
- Technical deep dives
- Hands-on AI operations guidance
Trusted by
Some of the companies that purchased AI services.
Current stateWork moves person to person
RequestResearchDecideUpdateFollow up
Multiple systems. Repeated context switching. Work waits at every handoff.
Focused AI stateAn agent handles the routine flow
Agent
ContextToolsActionsControls
Human judgment at defined control points
One accountable flow. Automated routine decisions. People handle exceptions and risk.
A practical diagnostic
Four signals that a workflow may be ready for agents
Judgment is involved
People interpret documents, context, exceptions, or intent before acting.
Work crosses systems
The outcome requires gathering context and taking action in multiple tools.
Value is measurable
Cost, cycle time, capacity, revenue, or quality can be baselined and tracked.
Quick economic test
Annual opportunity=workflow volume×cost per workflow×AI-addressable share×conservative improvement
If the result is not material, fix a more valuable workflow. AI is not the answer to every process.
See how agentic workflows are designedWhere agents create value
The work between tasks is the opportunity.
Agents earn their keep on decisions, handoffs, documents, customer response, back-office work, sales follow-up, and knowledge work. Start with the workflow that already has volume, judgment, and a measurable cost.
01Executive agents02Agentic workflows03Operations agents04Service agents05Finance agents06Sales agents07Research agents
Explore the AI Agents sectionDecisions
Routine choices sit in inboxes while people gather context from CRM, email, spreadsheets, and documents.
Handoffs
Work waits between teams because nobody owns the full outcome. Status, context, and next action get lost.
Document interpretation
People read contracts, invoices, applications, and packets, then re-enter the same facts into systems.
Customer response
Service teams reconstruct history across tickets, policies, and systems before they can answer.
Back-office work
Finance and shared services spend hours reconciling, coding, chasing exceptions, and updating records.
Sales follow-up
Leads and accounts stall because research, prioritization, and next-step outreach depend on seller time.
Knowledge work
Analysts and operators re-research the same questions instead of acting on a prepared recommendation.
Three credible paths
How far should you go?
Most Miami COOs should start with a contained win inside the work they already have. Go further only when the economics, the risk of mistakes, and the organization's ability to operate what it builds justify it.
01
Improve the work you already have
Use AI inside existing roles and workflows to remove specific bottlenecks and increase individual capacity.
Best when
The workflow is fundamentally sound and a few steps create most of the friction.
Tradeoff
Faster adoption and lower disruption, with primarily incremental gains.
02
Redesign the workflow around AI
Question every handoff, queue, and duplicate step, then rebuild the process around what AI can now do.
Best when
The process grew over time and coordination costs more than the work itself.
Tradeoff
Material improvement in cycle time, cost, quality, and operating capacity.
03
Put an agent on a high-value outcome
Give an agent responsibility for one valuable result across systems, with human authority, controls, and escalation designed in.
Best when
The workflow is high-value, variable, multi-step, and strategically differentiating.
Tradeoff
The largest change in operating economics, with higher engineering and governance demands.
Industries
The operating problem is the same. The workflow is not.
Founder-led and PE-backed companies in Miami already have expensive packets, exceptions, and follow-up. Start with the industry you are in, then name the one workflow that should change first.
01 Capital
Packets, exceptions, and control points where money moves.BankingCredit, KYC, and the incomplete file.Private EquityThe hold-period workflow, not a firm chatbot.InsuranceClose the file. Do not decorate the letter.
02 Built world
Deals, starts, and requests that wait on a complete packet.Real EstateLease and closing files, not a property bot.HomebuildingSelections, change orders, and chase.Property ManagementA queue of incomplete requests.
03 Consumer
Orders, guests, and exceptions that grow with volume.RetailThe exception queue, not the merchandising slide.Wholesale DistributionClean the order before you add pickers.Travel & HospitalityClose the guest case across systems.
04 Knowledge
Experts, accounts, and obligations buried in reconstruction.Technology & SaaSOnboarding and support packets, not a platform story.Professional ServicesJudgment stays. The packet should not be rebuilt.Media & EntertainmentRights, schedules, and the chase behind the show.Tools & assessments
Make the next decision with evidence.
Use the same questions that should guide an AI investment: where the value is, what it will cost, whether you are ready, and how it should be built.
Discover
Explore all eight AI tools and calculatorsAI Readiness Assessment
Score strategy, data, technology, people, processes, adoption, and governance.
Open tool PrioritizeAI Use-Case Prioritizer
Compare opportunities by value, feasibility, risk, data readiness, and time to value.
Open tool EvaluateAI ROI Calculator
Estimate annual benefit, investment, payback period, and three-year value.
Open tool DecideBuild vs. Buy Calculator
Choose build, buy, or hybrid based on differentiation, cost, risk, and speed.
Open toolBuilt in Miami
Silicon Valley experience, applied to Miami's business reality.
Miami does not need to become Silicon Valley. What that work actually taught is narrower: a demo lives at the product layer, and the failure usually lives in the engine — the objective, the observations, and the world the system thinks it is in. You can use that lesson without importing a Valley program.
Why this perspective is different
Built systems, not just presentations.
Adnan Boz has been shipping software since 1991 and working in AI since 2011. At Yahoo he worked on AI-powered personalization and recommendation enginesfor Homepage, Sports, and Finance — systems that reached more than a billion users. At eBay he worked on AI platform, experimentation platform, and personalization platforms. At NVIDIA he worked on AI platform products for autonomous-vehicle software development.
He trained thousands of operators through AI Product Institute and Stanford Continuing Studies. At SaasChing AI in Miami he builds production agents — so the conversation can move from the economics of one workflow to architecture, evaluation, and operations without becoming a program.
A useful next step
Bring one workflow. Get guided into production.
We guide the implementation, go deep on the technical path, and stay hands-on through operations — a visible win a COO can take back without launching a program.
Discuss an AI opportunity