About
I've spent 20 years in regulated industries—primarily healthcare—watching organizations invest heavily in technology that never makes it to production. Not because the technology didn't work, but because the organization couldn't get it through Legal, Security, and Compliance review.
The pattern was always the same: exciting demos, executive buy-in, then months stuck in procurement answering questions the product team never anticipated.
That's why Incline Protocol exists.
Our Point of View
Most AI conversations focus on capability: what models can do, how fast they're improving, which use cases unlock ROI.
That's necessary. It's not sufficient.
The harder question: Is your organization structured to approve AI systems that touch customer data, make autonomous decisions, and operate at machine speed?
Based on what we see across B2B—usually not yet.
The gap isn't technical. It's governance.
And governance isn't overhead that slows you down. It's the infrastructure that determines which AI projects ship and which ones stall indefinitely.
What We Believe
Three convictions that shape how we work:
Governance is infrastructure, not overhead.
Teams that build compliance into their first AI project spend 20% more time upfront but save 60% on every project after. Teams that retrofit governance spend months re-architecting systems already in production.
Documentation accelerates decisions.
When Legal asks for your AI data governance framework and you send a complete package same-day, you eliminate 3–4 review cycles. The teams that move fastest are the ones who built the artifacts their stakeholders need to approve.
Trust compounds.
The first AI project takes months to approve because you're building governance from scratch. The fifth takes weeks because the infrastructure already exists. Governance isn't one-time work—it's a capability that makes every subsequent project faster.
Why Incline Protocol
I've built AI governance programs inside healthcare organizations. Led SOC 2 readiness for B2B SaaS companies. Evaluated vendors from both sides of the table—as a buyer trying to get projects approved and as a vendor trying to pass security review.
I've seen what breaks: rushed compliance docs that don't match actual architecture, vendor evaluations that drag for months because requirements aren't clear, AI projects that stall because no one knew which stakeholder questions to answer upfront.
I also know what works.
While my background is heavily in healthcare—a regulated industry where trust infrastructure is mandatory—the principles apply broadly. Every B2B organization implementing AI faces the same core questions: How do we govern data access? How do we evaluate vendors? How do we get Legal, Security, and Compliance aligned?
The specific regulations change (HIPAA vs. SOC 2 vs. EU AI Act), but the governance challenges are universal.
The name reflects the approach:
A protocol is structured and repeatable, not improvised.
An incline requires preparation and a clear path.
There are no shortcuts to AI governance—but with the right protocol, you build it once and use it everywhere.
How We Work
We don't do open-ended consulting. We do fixed-scope engagements with defined outcomes:
Build the governance frameworks that get AI projects approved
Enable compliance teams to evaluate vendors confidently
Accelerate product teams from "we need to review this" to "approved"
If you're building AI in-house, evaluating vendors, or trying to get projects through Legal and Security review—let's talk.