Headcount planning and management
Workforce planning and management
Budgeting and forecasting

How Rad AI scaled from 80 to 220+ employees on a single source of truth with TeamOhana

80 to 220+
Employees scaled in 18 months on one aligned plan
140 hires
Managed in a single year against one reconciled plan
Overview
Rad AI builds generative AI tooling for radiologists, and it is growing fast. Will Barnett, Head of Talent, joined when the company was around 80 people. Eighteen months later it is past 220, after roughly 140 hires in a single year. Will spent over a decade at Facebook running high-volume hiring, where a purpose-built headcount tool tied recruiting to finance. At Rad AI he found the opposite: finance, recruiting, and the executive team each working off a separate spreadsheet export. He did not want to scale that way. Alongside his VP of People, who had used the same category of tooling, he made the case for a real headcount system before the growth curve turned the gap expensive. The company had already stood up Rippling as its HRIS and adopted Ashby as its ATS. TeamOhana became the layer that connected them and gave every function one number to trust, and one place to approve against before anyone gets hired.
Challenges
Finance, recruiting, and the executive team each ran headcount off their own spreadsheet export.
Hours a week lost reconciling who owned which role and where priorities actually stood.
Priorities shifted at startup speed, and no shared record kept up.
Time spent proving what to hire for, instead of finding the talent to hire.
01
The challenge
02
Our solution
03
Key workflows
04
Impact and results

When Will joined, Rad AI was small but built to scale. It already ran Rippling for HR and had just adopted Ashby as its ATS. Headcount itself, though, lived in Google Sheets, with finance, recruiting, and the executive team each operating off their own export. Even at 80 people, keeping those copies in sync cost hours a week.

The hours were not the real problem. The misalignment underneath them was. Priorities moved weekly at startup speed, and every move had to be reconciled by hand across three versions of the truth. Time went to proving what to hire for instead of finding who to hire.

Will had run high-volume hiring at Facebook, where a purpose-built headcount tool tied recruiting to finance. He wanted that back, and he saw the trap in waiting. People teams accrue their own version of technical debt, he argues: fast early hiring decisions, made without alignment, that the company pays down later. The tools you adopt early decide how much of that people debt you carry.

The economics closed the case.

“If we make one mis-hire, that's potentially hundreds of thousands of dollars a year. That compares so favorably to the pricing that it becomes a pretty easy rationalization for finance.” — Will Barnett, Head of Talent, Rad AI

He and his VP of People, who had used the same category of tooling before, aligned fast.

“Good enough is not good enough. We really want a tool that's going to make us better and keep us ahead of this ball.” — Will Barnett, Head of Talent, Rad AI

Our solution

Rad AI made TeamOhana the single source of truth for headcount: one place to identify, approve, maintain, and manage every role, with Finance, HR, Talent, and the executive team working the same plan. It connected the systems already in place, so headcount moved out of exports and into one governed record that every function approves against.

The change was not a nicer dashboard. It was a different relationship with the data. Will calls it headcount engagement.

“It's not cost savings. It's not headcount tracking. It's headcount engagement. It's how it enables everyone, from every corner of the organization, to engage with the headcount that they're responsible for and accountable to.” — Will Barnett, Head of Talent, Rad AI

Rollout matched the ambition. Will credits a consistent partnership from Rudy, his account executive, through implementation and 18 months of customer success, including TeamOhana's CEO jumping into Slack. The team also pushed Rad AI on structure, suggesting ways to organize the data so executives could read it cleanly and department heads could run audits against it.

Key workflows

One record everyone approves against

Every role is identified, approved, and tracked in TeamOhana, so Finance, HR, Talent, and the CEO align on what is being hired and why before anyone opens a req. When finance ran its own model in parallel to validate the numbers, TeamOhana held up.

“It came out that TeamOhana was right every time. I never made an adjustment to TeamOhana, because it actually was the source of truth.” — Will Barnett, Head of Talent, Rad AI

Real-time answers instead of reconciliations

Rad AI retired its quarterly headcount reconciliations and monthly look-backs. Status lives in the tool as it changes, and Will keeps TeamOhana open all day, using it more than his ATS on the talent side.

“Every talent leader has had the fire drill Slack message. I just click over to a tab and I have the answer in two seconds. I never have to pull a report.” — Will Barnett, Head of Talent, Rad AI

Time-to-fill as a live conversation

Will tracks time-to-fill against agreed priorities in real time, which turns hiring into a running strategic discussion rather than a monthly report. When a priority role stalls, he can flag it, reprioritize, or reset expectations with the business on the spot.

Executive and CEO self-serve

Rad AI's CEO works directly in TeamOhana, reading a live and accurate headcount picture: open heads per team, role status, H2 commitments, what Q3 and Q4 will bring. No spreadsheet archaeology, and often no 7 p.m. Friday fire drill to answer the question.

TeamOhana Computer for the question you didn't ask

TeamOhana Computer adds an agentic layer on top of that governed data. The value is not the interface, it is the comprehensive, unified record underneath it.

“It has such a comprehensive understanding of my headcount that it'll answer my question, but it'll also offer up a better answer to a question that I didn't ask.” — Will Barnett, Head of Talent, Rad AI

Ask about attrition and it returns the number, the breakdown by org, benchmarks, and the corner worth worrying about. Context a static monthly report would miss.

Impact & results

  • Scaled from 80 to more than 220 employees in 18 months with Finance, HR, and Talent aligned on one plan.
  • Managed roughly 140 hires in a single year without headcount drifting out of sync.
  • Eliminated weekly spreadsheet reconciliation, monthly look-backs, and quarterly headcount reviews.
  • Fire-drill headcount questions answered in seconds, with no report to pull.
  • Validated as the source of truth against Finance's parallel model, correct on every adjustment.
  • Mis-hire risk, where a single bad hire can represent hundreds of thousands of dollars, reduced by aligning every role before it opens.
  • Finance, initially running its own model on the side, now actively adopting TeamOhana.
  • CEO self-serves a live, trusted headcount picture across current roles and future commitments.

Rad AI's CFO, who joined after the rollout, put the outcome plainly.

“One of the first observations he had is that we have one of the tightest headcount models he's seen at any company our stage. I credit that entirely to TeamOhana and the team aligning around this tool.” — Will Barnett, Head of Talent, Rad AI

For Will, the payoff is bigger than any single number.

“There's nothing more expensive to a company than making the wrong hire, or hiring for a team that people weren't aligned to. An organization that is engaged with their headcount is making better decisions, and maintaining a stronger upward trajectory.” — Will Barnett, Head of Talent, Rad AI
80 to 220+
Employees scaled in 18 months on one aligned plan
140 hires
Managed in a single year against one reconciled plan

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