About Us
Cazimir and Brooks Energy exist because of a gap most insurance technology never addressed. Software vendors kept building tools to move data faster, while the industry kept losing something no dashboard could replace: the judgment underwriters build over decades on the job. Founder Gennaro Brooks-Church started both companies to close that gap directly, not with faster automation, but with AI built to absorb underwriting knowledge instead of ignoring it.
What We Do
We build AI systems that do not just process data—they learn to think like your best underwriters. Most insurance technology focuses on speed at the expense of accuracy. We focus on efficiency through knowledge capture. What we do is turn the messy, intuitive judgment of veteran underwriters into traceable, verifiable software. This allows MGAs, insurers, and wholesale brokers to remove the heavy manual lifting of submission review while ensuring every decision remains grounded in institutional expertise. We aren't offering a replacement for your team; we are offering a way to scale their judgment globally, one learning-based deployment at a time.
Values
Why We Build This Way
My vision is an insurance industry that stops treating AI adoption and underwriting expertise as opposing forces. Right now, too many organizations feel pressure to choose between modernizing their operations and protecting the judgment that makes underwriting reliable. I don't think that trade-off has to exist. Through Cazimir and Brooks Energy, I'm building toward a future where learning-based systems and experienced underwriters strengthen each other, where technology handles volume and repetition while people handle the calls that require real experience. Getting there depends on transparency: underwriters and compliance teams should be able to check a system's reasoning, not just accept its output. As more of the industry adopts AI, I want that standard—traceable, verifiable, accountable to become the baseline expectation, not a differentiator. The goal isn't an industry that relies less on expertise. It's one that finally stops losing it.
How We Work
Knowledge Capture
We begin by observing and recording the judgment calls of your senior underwriters to create a baseline for automation.
System Deployment
The AI is integrated into your workflow, handling data extraction and inconsistency checks with full transparency.
Verification Loop
We work in close partnership with your team, treating corrections as material that makes the system sharper over time.
What We Won't Do
We won’t sell “black box” algorithms that underwriters can’t explain to a client or a regulator. AI that hides its reasoning might provide short-term speed, but it creates long-term risk that we aren't willing to build into our systems. We also won’t approach a project with the goal of replacing human expertise. Our work is designed to capture and amplify judgment, not eliminate it. Finally, we won’t deploy technology that hasn't been tested against the messiest, most complex parts of a workflow. If a system only works on perfectly structured data, it doesn’t belong in a real-world underwriting submission process.
Where We're Headed
My vision is an insurance industry that stops treating AI adoption and underwriting expertise as opposing forces. Right now, too many organizations feel pressure to choose between modernizing their operations and protecting the judgment that makes underwriting reliable. I don't think that trade-off has to exist. Through Cazimir and Brooks Energy, I'm building toward a future where learning-based systems and experienced underwriters strengthen each other, where technology handles volume and repetition while people handle the calls that require real experience. Getting there depends on transparency: underwriters and compliance teams should be able to check a system's reasoning, not just accept its output. As more of the industry adopts AI, I want that standard—traceable, verifiable, accountable—to become the baseline expectation, not a differentiator. The goal isn't an industry that relies less on expertise. It's one that finally stops losing it.