AI That Works. ROI in Weeks.
Engineer-led. We build systems, not slide decks.
Growing companies (50–500 employees) need AI that delivers from day one. We find the highest-ROI opportunities, build the solution, and deploy it.
Recent: 70+ hrs/month recovered, $42K annual savings — read the case study | New: Building AI-ready knowledge systems for an enterprise client
Discover. Build. Scale.
First working systems in 2–4 weeks.
62% of companies are still stuck in AI pilots that never reach production (McKinsey, 2025). We skip the experiment phase entirely — working solutions in weeks, not months. No handoffs, no middlemen. Engineer-led from discovery to production.
It starts with a focused 2-week sprint to identify your highest-value AI opportunities. From there, we build, test, and deploy — prioritizing by ROI so the biggest wins land first.
We don't hand you a PDF and walk away. We build the solutions ourselves. 10+ years of systems architecture means we design AND deliver.
"Start with the highest-ROI opportunity. Build it fast. Then scale what works — because momentum compounds."
"After a decade designing and building complex systems, I wanted to help companies implement AI the right way — fast, practical, and built on foundations that actually hold."
That's why I built TRIAGE — a practical protocol that starts where the work happens, identifies the highest-ROI opportunities, and delivers working solutions in weeks. And because I'm an engineer, not just a consultant, I build the solutions myself. No slide decks. Working systems that your team actually uses.
The TRIAGE Framework
A systematic, 6-step protocol designed to move companies from discovery to measurable results.
Research across 2,500+ AI deployments shows systematic approaches significantly outperform isolated experiments.
Task Assessment
We sit with your team to identify the real bottlenecks — the ones costing the most time and money. Data-driven discovery reveals root causes, not symptoms.
ROI Mapping
We map clear financial outcomes before building anything. If an automation doesn't save measurable hours or dollars, we don't build it. Simple as that.
Integration Planning
After we know what to fix and what it's worth, we design exactly how. Your implementation roadmap accounts for the tools you already use, the constraints you operate under, and the capacity your team actually has. No rip-and-replace. No theoretical blueprints.
Adoption Strategy
Technology fails if humans don't use it. Training and change management are baked in from day one — not bolted on at the end. Your team shaped the solution, so they actually want to use it.
Governance
Every solution ships with guardrails built in: security protocols, compliance requirements, and quality controls. AI runs within proper boundaries from day one — not retrofitted after something breaks.
Evaluation & Optimization
Impact is measured against the KPIs defined in step 2 — no subjective "it feels better." The system iterates and improves, and so does your team's ability to manage it independently. The goal is your independence, not our retainer.
Your AI Implementation Timeline
A clear path from kickoff to measurable results.
Where Most Companies Start
- × Leadership demanding "AI strategy"
- × IT blocked by compliance concerns
- × Teams stuck in manual work
- × Consultants quoting six figures for unknowns
- × 6-12 month timelines, no guarantees
- × No idea where data actually lives
The Production State
- ✓ Quick wins deployed in first 2-4 weeks
- ✓ Operational waste quantified in dollars
- ✓ Processes documented & standardized
- ✓ Foundation for scalable automation
- ✓ Team empowered, not replaced
- ✓ Clear ROI documented from day one
The TRIAGE Timeline
Process mapping, opportunity identification, ROI documentation
First AI solutions deployed, immediate time recovered
Standardization, automation architecture, team training
Model Your AI Savings.
Every hour your team spends on manual processes is an hour AI could give back. Use this model to estimate what implementation could recover for your organization.
Not sure yet? If our sprint doesn't surface clear savings, you get a full refund. See a real example.
Directional estimate. Your discovery sprint will produce verified numbers specific to your organization.
Why companies choose TRIAGE.
Traditional consulting recommends and leaves. We design, build, and stay until the numbers prove it works.
Your Real Options
Every company facing AI adoption has three paths. Here's an honest look at each.
Wait & See
Cost: $0 upfront, compounding waste
- × Operational waste continues unchecked
- × Competitors gain efficiency advantages
- × Team burns out on manual work
- × Eventually forced to act under pressure
Hire an AI Lead
Cost: $150-200K/year + 6-12 month ramp
- ✓ Permanent in-house capability
- × 3-6 month hiring process
- × No framework or methodology on day one
- × Single point of failure if they leave
TRIAGE Framework
Starts with a 2-week Discovery Sprint
- ✓ Quick wins in 2-4 weeks
- ✓ Structured 6-step methodology
- ✓ Ground-truth, frontline-first discovery
- ✓ Your team owns the result
The real cost of waiting isn't the AI you didn't buy — it's the operational waste you keep paying every month. The calculator above shows you the cost. We build the fix.
Ready to implement AI that works?
In two weeks, you'll have verified ROI projections and a clear implementation plan — and we'll have already identified your quickest wins to start building.
Discovery Guarantee: If our Discovery Sprint doesn't surface clear, measurable savings opportunities, we'll refund it. That's how confident we are in the process.
Everything You Need to Know
Most AI consultants sell tools or strategy decks. We do neither. We start by sitting with your actual team members — the people doing the work — to understand where time and money are being wasted. Then we fix the process before touching any technology. Our engagements are scoped and priced for growing companies, not enterprises, and you see quick wins in weeks, not months. If you're considering hiring an AI lead instead, consider this: we deliver a structured methodology and results in the time it takes to fill a role.
That's exactly why we exist. MIT research shows 95% of AI pilots fail — not because the AI is bad, but because the process underneath was never ready. Most implementations skip straight to the technology and wonder why nothing sticks. We work backwards: document what actually happens day-to-day, remove immediate friction with tactical solutions, then standardize processes so automation has a stable foundation to build on.
Discovery phase: 2 weeks to quantify waste and map real bottlenecks.
First quick wins: 2-4 weeks to remove immediate friction and free up capacity.
Full implementation: 8-12 weeks for complete TRIAGE cycle (standardization + automation architecture).
Unlike traditional consulting where you wait 6 months to see value, you see measurable improvements in the first month.
Yes — this is one of the most common scenarios we hear. Pressure without clear strategy leads to expensive mistakes. We help you respond intelligently: first, we quantify your actual operational waste (the calculator above shows you the math). Then we build a phased roadmap with measurable ROI milestones. You'll have concrete numbers to present to leadership within 2 weeks, and demonstrable results within 60 days — not vague promises about "AI transformation."
Absolutely—and you're not alone. Data blindness is one of the most common blockers companies face. That's why Task Assessment (the "T" in TRIAGE) starts with discovery: we sit with your teams to understand actual workflows, identify where data lives (spreadsheets, databases, tribal knowledge), and document the current state. You can't automate what you don't understand. We make the invisible visible first.
Discovery phase: 5-10 hours of interviews with key team members across operations.
Implementation: Weekly check-ins (1 hour) + access to systems/data + one internal champion (10-15% of their time).
Our philosophy: We build with you, not for you. Your team's insights are critical—they know where the real pain points are.
But we do the heavy lifting on design, build, and deployment.
No—waiting for perfect AI agents means losing money today while competitors gain ground. Our approach: deploy tactical interim solutions now to remove immediate friction, which creates breathing room to properly standardize processes. Then when more advanced AI becomes available, you have clean foundations to build on. Companies that wait end up further behind because they never fixed the underlying chaos.
We define clear KPIs upfront in the ROI Mapping phase (the "R" in TRIAGE). Typical metrics:
• Time savings: Hours recovered per employee per week
• Cost reduction: Operational waste eliminated (calculated in dollars)
• Capacity gained: FTE equivalents freed up for higher-value work
• Process reliability: Error rates, completion time, consistency
Every metric ties directly to financials. If we can't measure it, we don't build it.
You get a complete report: every friction point mapped, financial impact quantified, and a prioritized roadmap for fixes. From there, you have three options: take the roadmap and execute internally, bring us on for a targeted quick-wins phase (4–8 weeks), or engage us for the full TRIAGE implementation (scoped and priced based on your specific findings). There is zero pressure to continue — the discovery deliverables are yours regardless.
Our Research & Results
Research, analysis, and real results from AI implementation in growing companies.
From Excel Hell to AI Automation
How we saved an accounting team 70+ hours per month by automating QuickBooks branch payment reconciliation. Real numbers, real ROI: $42K recovered annually.
Read Case Study → White PaperThe 95% Failure Rate: A Structural Analysis
MIT research reveals 70% of AI failures stem from organizational issues, not technology. Analysis of $47.4B in enterprise investment and what the 5% who succeed do differently.
Read Analysis → Deep DiveWhy F100 Companies Waste Billions on AI
42% of companies abandoned most AI initiatives in 2025 (Gartner). Research reveals why shareholder mandates, data blindness, and the IT trust gap doom enterprise AI—and how mid-market companies avoid these mistakes.
Read Analysis →