It didn't start with a mandate from the board. It didn't come from a new CHRO with a transformation agenda. At Rainbow Insurance, the push for formal performance management came from exactly where it should: the people doing the work.

When Desiree Therianos joined Rainbow as a fractional HR leader, she started with a simple pulse survey, and a lightweight eNPS to gather insights from employees as to how likely they were to recommend Rainbow as a place to work, and what they wanted to see more of. The response was consistent and clear. Employees wanted to know how to grow.

"In that feedback loop process, a lot of people wanted to hear about career planning options. How are career pathing and career progression conversations at Rainbow handled? Because there just wasn't anything formalized."

— Desiree Therianos, Fractional HR Executive

Rainbow Insurance is a post-Series A insurtech company serving small business customers In its first few years, like most fast-growing startups, it had relied on manager one-on-ones and informal check-ins to steer employee development. That worked at ten people. At thirty, it wasn't enough.

The challenge wasn't just scale:  it was equity. Without a structured process, employee growth depended entirely on which manager you had. Some managers were seasoned veterans. Others had never run a formal review in their lives. And none of them had ever used an AI-augmented tool.

Desiree's question became the north star for everything that followed:

"How do we do it in a fair, equitable way where everyone knows those elements that they're being assessed on? How do we do it transparently and in an empowering way?" — Desiree Therianos

Six Weeks. Zero Prior Baseline.

Working with Zal.ai, Desiree designed and launched Rainbow's first formal review cycle from scratch, a 360-degree process that included self-assessments, two manager-selected peer reviews, and manager assessments, all synthesized by Zal.ai's AI. The entire cycle ran from early December through mid-January: six weeks, start to finish.

Before a single review was written, Desiree convened Rainbow's people managers as a group for the first time. She ran training sessions, invited managers to co-design elements of the process, and built shared ownership before the cycle even began.

The result:

A 97% completion rate on a first-ever review cycle is, to put it plainly, exceptional. In Desiree's experience, there is always a subset of employees who simply don't finish. Not here.

The AI-powered synthesis also delivered something less expected: time savings that managers hadn't anticipated until they experienced them firsthand.

"The feedback I got that was really nice was: 'Oh wow, it did save me a lot of time.' Because it was able to synthesize information in a way that made it easy for me to review and add my own inputs and build upon."

— Desiree Therianos

Beyond efficiency, the platform helped address something more structural: bias. Recency bias, the tendency to let the last two weeks overshadow a full year of work, is one of the most common and damaging failure modes in performance reviews. Zal.ai's synthesis draws from the entire review period, giving managers a fuller picture before they write a single word.

"Your manager shouldn't just only remember the things you did in the last two weeks when this is a year-long assessment period."

— Desiree Therianos

The Review Was the Beginning, Not the End.

At a leadership offsite after the cycle closed, the Rainbow team asked the question that a well-run performance review should always surface: what does high performance actually look like here, in each team, at each level? The data gave them the language to start answering it.

Rainbow is now building a transparent compensation philosophy, mapping department-specific career progression journeys, and deepening manager training on bias, all work that the first review cycle made possible. The cadence has also shifted to July/August, giving the team room to breathe and reflect outside of their busiest season.

Desiree put it plainly when reflecting on what the tool made possible and what it didn't try to replace:

"I think a tool isn't going to solve that for you. But having a tool to augment the process  where you can be really confident in the ability only helps build that process infrastructure of confidence. And that layer is really important."

— Desiree Therianos

The full story is in the case study.

Inside, you'll find the complete account of how Rainbow Insurance designed and executed its first-ever review cycle: the obstacles, the process, the results, and the roadmap they built from the data. If your organization is at a similar inflection point, this is the blueprint.

Case Study coming soon…