Questions we get asked before every diagnostic.

It’s an infrastructure layer that sits on top of your entire business. It connects your data sources, indexes your meetings and conversations, watches your operations in real time, and gives your leadership team visibility they’ve never had. On top of that foundation, we install AI specialists that handle specific jobs: financial analysis, lead response, client reporting, hiring screening, whatever the diagnostic says you need. Three layers make it work: your business context (strategy, team, processes, history), your live data (CRM, accounting, marketing, email, all connected and updating daily), and an intelligence layer that reads all of it and surfaces what needs attention. The system gets smarter every month because it’s learning from your actual operations, not generic training data.

We’re an AI consulting and implementation firm. We come in, run a diagnostic on your operations, and build the AI infrastructure that gets leadership out of the day-to-day. The diagnostic finds where you’re bleeding money and time. The build connects your data sources, loads your business context, and installs the capabilities that solve specific problems: daily intelligence briefs, meeting summaries, automated reporting, lead response systems, content workflows, financial dashboards. The foundation stays the same. New capabilities plug in on top as you need them.

ChatGPT doesn’t know your margins, your team’s names, your client pipeline, or what happened in yesterday’s meeting. An AI operating system does. It’s connected to your actual data sources, trained on your actual business context, and producing outputs specific to your operation, not generic answers anyone could get.

We interview ownership, key employees, and anyone who touches operations. Every conversation gets recorded and processed. We map your workflows, quantify where you’re losing money and time, and identify where AI closes the gap. The output is a full findings document in plain English, no jargon, no technical specs. You get a prioritized build plan showing exactly what to fix, what it costs you to leave it broken, and what the return looks like if we fix it. You keep the report regardless of whether you move forward.

Typically 1–2 weeks. We conduct 4–6 interviews (60–90 minutes each), process everything between sessions, and present findings at the end. For smaller teams it can be faster. The interviews can happen on-site or via Zoom. We process every transcript the same afternoon so findings compound across conversations. By the time we get to the presentation, we know your business better than most people on your payroll.

The free call is 30 minutes. We look at where you’re bleeding time and money and whether an AI system would actually help. If it won’t, I’ll tell you and we’ll end the call early. If it makes sense, we scope the diagnostic together on that call: number of interviews, timeline, and investment. Think of the call as the surgeon’s consultation. The diagnostic is the tests and imaging before surgery. You wouldn’t trust a surgeon who walked in and started cutting without running tests first.

Every engagement starts with a paid diagnostic. The diagnostic is scoped on the discovery call based on how many people we need to interview and how complex the operation is. After the diagnostic, you see a menu of recommended builds with individual prices. You pick which ones to turn on. Nothing is hidden and nothing is bundled. You see every line item before you commit to anything.

The diagnostic quantifies this for your specific business. Typical outcomes: 2–3 hours per day returned to the founder, 60–90% of recurring tasks automated, and measurable cost savings from eliminating manual work. One client found $84K in wasted marketing spend that their agencies had missed. Another cut $100K in staff costs because the system replaced work that was being done by VAs and contractors. Accenture found companies with AI in their operations grow 2.5x faster than peers. The ROI depends on how much you’re currently losing, and that’s exactly what the diagnostic measures.

The AI tools your system runs on have usage costs: API calls, model access, hosting. These are pass-through costs, not markups. For most businesses it’s a few hundred dollars per month. An optional monthly retainer covers ongoing optimization, system upgrades as AI models improve, and development of new capabilities. Some clients prefer project-based work instead. Either model works.

Everything is installed on your machines, in your environment. No data goes to Kinetic3’s servers. The AI system has folder-level permissions, so it can only access what you allow. We apply a 6-layer security model to every installation: permissions, tool-level blocks, code constraints, environment sandboxing, audit logging, and deployment checklists. Every action the AI takes gets logged. You can see exactly what it accessed and when.

Healthcare clients get HIPAA-compliant configurations by default. No patient data touches non-compliant platforms. Separate workspaces per client, pseudonymized data before AI processing, and tools with signed Business Associate Agreements. The 6-layer security model includes healthcare-specific rules for data patterns, retention, and access control. If your practice handles protected health information, the system is built to respect that from day one.

Healthcare, construction, legal, financial services, home services, e-commerce. We’ve built across all of them. The AI operating system is industry-agnostic because the underlying problems are the same everywhere: manual processes, disconnected data, decisions bottlenecked at one desk. If your business has workflows and data, we can build on it. The diagnostic tells us exactly where.

If you’re doing $2M or more in annual revenue and spending more time managing the business than growing it, you’re worth a conversation. Solo operator or team of 50. The most common thing we hear is “we’re not ready for AI.” That’s usually the sign that you are. It means you recognize the gap but don’t know where to start. The diagnostic exists to answer that question for your specific business.

You can try. Most can’t. We work with companies doing $50M or more in revenue who downloaded the tools, spent a week on it, and gave up. The barrier is willingness to sit in a terminal and figure it out while also running a business. Every hour you spend configuring AI tools is an hour you’re not running your business. You could learn it. The question is whether that’s where your time should go.

Every build comes with a 30-day warranty. During that window we monitor performance and fix anything that comes up. After the warranty, most clients move to a monthly retainer. We optimize the system, upgrade it as AI models improve, and build new capabilities as the business needs them. The diagnostic findings become your roadmap, and every problem we identified is a future module waiting to be turned on. The foundation stays, and the capabilities compound.

It will. That’s the point. AI tools change every quarter. But the AI operating system (your context, your data connections, your workflows) doesn’t change. That’s the durable layer. When a better model drops or a new capability launches, the system upgrades on the same foundation. We keep your system current so you don’t have to keep up with every new release. The change is actually the moat. It means your competitors can never catch up by waiting.