How Omnea Is Building an AI-Native Talent Function to Win Competitive Talent

Building a Talent Function for Hypergrowth

As Founding Head of Talent at Omnea, Joshua Voisey is building the recruiting infrastructure behind one of Europe’s fastest-growing technology companies.

Omnea has more than tripled headcount and revenue over the past year. For Joshua, keeping pace with that kind of growth does not simply mean adding more recruiters. It means designing a talent function that can scale differently.

And a central part of that strategy is figuring out where AI and automation can genuinely make recruiters better at their jobs.

“I want our recruiters to be at the value end of AI automation. And I believe where AI can drive the most value is building pipelines at the top of the funnel.”

That philosophy matters even more in the market Omnea is hiring into.

Among London’s fastest-scaling technology companies, competition for top engineering talent is intense. Joshua estimates that fewer than 20% of Omnea’s hires over the last year came through inbound, while engineering hiring is effectively an outbound-only motion.

At the same time, AI and automation make it easier than ever to scale outbound, leaving candidates inundated with recruiting messages.

“The market is just absolutely suffocated from generic messaging. We need to deliver a more white-glove service.”

For Joshua, simply increasing outreach volume was never going to solve the problem.

His team needed to identify highly specific candidates and approach them with outreach that felt thoughtful and individual.

Exploring the Recruitment Technology Market

When Joshua joined Omnea with a clear point of view on sourcing technology. At his previous company, Gelato, his team extensively evaluated sourcing platforms rather than adopting tools based on feature lists alone.

One of his tests was intentionally difficult: ask each platform to find an Account Executive who speaks German, based in Germany. Most tools struggled to interpret the requirement. Some returned candidates in London, while others surfaced English speakers.

Juicebox was the only exception.

“Juicebox was the only one that could do it and it was the only one that came back with relevant candidates.”

The platform went beyond literal profile fields, using signals such as candidates attending German universities to infer who could be relevant.

Joshua had tested Juicebox in other ways too, including asking it to surface company information around funding, headcount, and scaling businesses. His conclusion was straightforward:

“It was so far advanced compared to the rest.”

That testing gave Joshua confidence to make Juicebox part of the recruiting infrastructure he was building at Omnea.

Finding the Profiles Traditional Search Misses

Omnea hires against an unusually specific talent bar.

The team looks for a track record of excelling at something hard: signaling real drive, ownership, and rigor. That might show up in previous experience, competing in sports, founding businesses, standing out in academia, and just as often somewhere far less obvious.

Those requirements are difficult to translate into traditional recruiting filters. Natural-language search lets Joshua’s team describe the profile they actually want rather than reverse-engineering it into a series of keywords.

“We have an incredibly high bar with specific requirements, and  it’s extremely hard to find that without having that natural language capabilities.”

The difference he saw when using Juicebox to spot this talent was both quality and speed.

“Juicebox is allowing us to find incredibly niche profiles. And it's doing it quicker. It allows us to access similar data to other platforms but within much deeper parameters and inputs.”

For Joshua, that means recruiters spend less time searching broadly and more time engaging the candidates who actually fit Omnea’s bar.

Turning Agents Into Extra Sourcing Capacity

Joshua has taken that philosophy one step further by integrating Juicebox Agents directly into how the recruiting team allocates its time.

Omnea currently runs seven Agents across a six-person talent team, including three focused on engineering. Evergreen roles can run more autonomously, while Agents are also assigned to highly specific searches where manually finding even a small number of relevant profiles can consume hours.

Joshua thinks about that allocation in terms of return on recruiter time.

“If it’s a particularly unique role that takes time to find the right 5–10 profiles. I want them using the Juicebox Agent for that. Then they can focus their time on the lower-hanging fruit where they can move faster.”

Joshua estimates that generating 10 to 15 interviews a week through manual sourcing would take a recruiter around five hours per day. With Agents handling that work, it's 25+ hours returned to the recruiter every week.

“If the Juicebox Agent can generate 10–15 interviews a week, it cuts my recruiter’s sourcing workload in half and frees them up to spend more time on calls and adding value to the business.”

Making Outbound Feel Personal at Scale

The Omnea team applies the same thinking to candidate outreach.

In a market saturated with generic recruiting messages, Omnea needs their outbound messages to feel meaningfully different. To do this, the team feeds Juicebox deep context for each role, covering the job description, the characteristics candidates should spike on, and the personality profile they are looking for.

“We are creating some really creative and original outbound that we could do at scale which we just cannot do on other recruiting platforms.”

Using Juicebox Sequences alongside Agents and the Send on Behalf feature, his team can then turn that context into individualized messaging automatically.

“We run Juicebox Agents autonomously and create unique messaging for every candidate, so each outreach feels like a personalized letter.”

The Results

Omnea is growing and hiring fast, and the pressure of that lands squarely on a highly efficient talent team.

As a result, Joshua and team rebuilt how they source: surfacing profiles traditional search never returned, cutting the manual work that used to fill their days, and putting those hours back into candidate conversations and pipeline movement.

The results speak for themselves:

• 50% more sourcing capacity for recruiters across technical roles

• 25+ hours saved per recruiter per week by automating manual sourcing

• 100+ qualified candidates found per week through Juicebox Agents

• 10 to 15 engineering calls generated per week from an agent-driven pipeline

“Juicebox Agents give us the equivalent of four or five extra sourcing headcount at a fraction of the cost of other alternatives in the market.”