Global Innovation Group — the future belongs to the proactive
Like a fractional CFO or CTO — but for AI. We embed in your operating company, set the AI direction, and ship working systems to production every month. A vendor delivers and leaves. We don't leave.
Francisco built the playbook inside his own businesses — a CCIM-credentialed commercial real estate broker (SVP, KW Commercial Beverly Hills) running AI across brokerage, capital markets, and private lending. Cindy turned it into a repeatable practice and leads delivery on every engagement. Kristle makes sure the right operators hear about it. When you hire the partner, you hire these three.
Operator · Broker · Builder
“I run operating companies. Lending, capital markets, brokerage. I started deploying Claude and open-source models inside my own businesses — then operators kept asking how I did it. Global Innovation Group is that answer, packaged.”
Operations · AI Implementation · Delivery
“I started in operations. Francisco showed me what AI could do, then dared me to learn it. Now I lead delivery on every engagement — intake, build, training — taking a client from a manual workflow to a live system, month after month.”
Brand · Demand · Content
“I built the brand and demand engine at Capital Direct Funding — taking a complex private-lending product and making it land with operators who don't have time for fluff. AI is the same job, different stack. The brand has to feel like the people behind it.”
Most companies are stuck between two bad options: hire a vendor who builds a thing and disappears, or wait for an in-house AI hire who never gets prioritized. Neither ships. We took a third path — we run AI inside our own operating companies first, then embed in yours and do the same. Not a deck, not a pilot, not a course. A working AI function, on staff, part-time, every month.
We don't deliver and leave. We're part of your operation — ongoing, accountable, in the room every month.
Invert the problem. What does it cost to not move on AI while a competitor does? We answer that, then act on it.
We run AI in our own businesses — lending, capital markets, brokerage — before we run it in yours.
No theory without a shipped system. Every month of the engagement puts something working into production.
You already know the fractional model — a fractional CFO runs your finance function part-time, a fractional CTO runs engineering. We do the same for AI. A senior team embedded in your business on an ongoing monthly basis: we set the AI direction and we ship the systems. When a build lands, we don't pack up — we're still here next month, owning the next one.
Francisco-led.
Where AI earns its keep in your business changes as you grow. We own the roadmap: which workflows to automate next, which models and stack to run, what to build versus buy, and the hardware direction. You get a standing strategic function, not a one-time recommendation.
Cindy-led.
This is the part most AI engagements skip. Cindy leads delivery end-to-end: agents, automations, CRM enrichment, integrations — built, tested, and wired into your real workflows. Every month of the engagement puts something live, not a slide about something.
Built in.
An AI function you can't operate without us is a liability, not an asset. As we ship, we train your people — playbooks, runbooks, working sessions — so the systems keep running and improving whether we're in the room or not. You are never hostage to the vendor.
Most clients are established operating companies in the $3–5M+ revenue range. Below that, a $15K/mo engagement rarely clears a 2× first-year return — we'll tell you straight rather than sell you something that won't pay back.
See if it's a fitRunning your own open-source models — Llama, Mistral, Qwen — takes real compute. Where that compute lives, and who owns it, drives three things that matter: cost, privacy, and control. So every engagement makes a hardware decision. There are two paths.
Your workloads run on AI infrastructure GIG owns and maintains. We handle provisioning, scaling, and ops — you get capacity without buying or managing hardware. Lower cost, the fastest path to a live system, and no infrastructure on your plate.
We spec, source, and provision hardware that the client owns — on your premises or in your own cloud account. Your data never leaves your environment. You own the asset outright. The right call for privacy-sensitive verticals — healthcare, legal, finance — or for workloads at heavier scale.
The hardware path you choose is one of the inputs that sets where your engagement is priced — alongside scope and commitment length.
The internal model that calibrated our $15K floor — same inputs, same constants, productized. Move the sliders and the math recalculates. No submit, no email, no sales call.
Recalibrate in real time. Pricing is quoted per client; this is a directional read.
Numbers reflect GIG's internal model at current calibration. The actual engagement is quoted in writing.
The engagement opens with a four-phase onboarding arc — it runs inside the three-month minimum term, and month one ships a working automation before the diagnosis is even done. After the first quarter, the partnership continues: the next systems, the next decisions.
First weeks. We map your workflows, data, tools, and team — and we ship one working automation before the diagnosis is even finished. You see value in month one, not month four.
We set the stack and the roadmap. Hardware path, models, integration surface, the order we'll build in. You get an architecture doc and a quarter-one plan you can hold us to.
We build, ship, and wire into production — system after system. CRM integrations, agents, automations, the evals and monitoring that keep it honest. Every month adds something live.
We train your team as we go — playbooks, runbooks, working sessions — so your people can run what we build. And then we don't leave. The partnership continues: the next quarter, the next systems, the next decisions.
Each vertical has a different data surface, different workflow shape, different stakes. We run a Fractional AI Partner engagement in six — see what that looks like for yours.
An ongoing AI function for brokerages, teams, and investment shops.
We run Claude for production-grade agents, Llama/Mistral/Qwen for self-hosted workloads, and fine-tune on whatever Hugging Face has when the task warrants it. No vendor lock-in. No hidden dependencies.
Open source where it earns it. Closed models where it doesn't. Your hardware decision shapes both.
A Fractional AI Partner engagement is a real commitment, and it should be entered with eyes open. The AI Audit is how it begins — a paid, fixed-scope diagnostic (~$1,500) of your business, not a discounted engagement and not a sales call.
A Fractional AI Partner engagement is a real commitment, and it should be entered with eyes open. The AI Audit is how that starts: a fixed-scope, paid diagnostic of your business. We read your operation for its highest-ROI automation targets, recommend a stack and a hardware path, and give you a straight feasibility verdict — is AI worth it here, and where.
It's a fixed fee, not a sales call dressed up. If you proceed to a partnership, the audit fee credits toward your first month.
Tell us about your company below. Cindy reads every inbound, and you'll hear back within 24 hours. If a Fractional AI Partner isn't the right fit for where you are, we'll say so plainly.