How Aleph Alpha grew from 150 to 320 people with help from Tribe

Aleph Alpha is an AI company founded in 2019 and based in Heidelberg. Its product, PhariaAI, is a full-stack platform that enterprises and public institutions use to build AI applications they keep control of, built for organisations with sovereignty, security and trust requirements they cannot compromise on.

In November 2023 the company raised more than $500 million dollars in a Series B round led by the Innovation Park Artificial Intelligence, Bosch Ventures and the Schwarz Group. This kicked off a high growth period where scaling the company was a priority. Tribe stepped in to help develop better processes and find ideal candidates during a growth period that more than doubled the size of the company in under a year.

Key data

• Project period: September 2024 to June 2025
• Hires: 48
• Company headcount over the period: 150 to 320
• 3 Tribe embedded recruiters, one each on product, engineering and customer-facing roles
• Source of hire moved from full dependency on applicants to a sourcing-led model

Context

When we joined in September 2024, Aleph Alpha was scaling across three areas at once: product, engineering and the customer side. Each of these needed different market knowledge and a different approach to candidates.

Hiring during a scaling phase comes in bursts tied to funding, roadmap and team structure. Building a permanent internal team large enough to absorb the peaks means carrying that cost through the quiet months too. Aleph Alpha wanted capacity it could turn up and down, which is why the engagement ran for 10 months rather than as a fixed project.

Almost all of Aleph Alpha's candidates were coming from applications. For an AI company competing for the same specialists as every other well-funded lab in Europe, that limits who you ever get to consider.

Needs analysis

Challenges

• Hiring volume that rose and fell with the scaling phase, difficult to staff with a fixed internal team
• Specialist depth needed across product, engineering and customer-facing roles at the same time
• A talent pipeline built almost entirely on inbound applications

Opportunities

• Add sourcing capability to reach candidates who were not applying
• Diversify sources of hire across the three functions
• Give the head of TA support on structure and strategy, not only on delivery

Action plan and implementation

Three Tribe recruiters joined the Aleph Alpha team, each taking one area: one on product, one on engineering, one on customer-facing roles. They worked inside the company's own tools and processes rather than running a parallel agency process alongside them. This is where a strategic recruitment partnership really allows a scaleup company to find their feet and start running, fast.

The team size flexed with demand. When hiring picked up, we scaled up. When it slowed, we scaled down, so the cost followed the actual need rather than a fixed retainer.

Alongside delivery, the consultants worked with the head of talent acquisition on how the function itself ran. That meant building targeted sourcing into the process, giving hiring managers and stakeholders a shared basis for agreeing on what a profile actually required, and supplying the hiring data the team needed to make those calls.

Results and reflection

Tribe's embedded recruiters made 48 hires between September 2024 and June 2025, during which Aleph Alpha went from 150 to 320 employees.

While 48 hires in 10 months is an impressive number, the significant overall growth at Aleph Alpha during this period would not have been possible without a change to the fundamental hiring strategy. By the end of the engagement the team was sourcing for roles that had previously waited on applicants. That gave the company access to candidates who would never have applied on their own.

The recruiters also worked as internal partners rather than external suppliers. They helped stakeholders reach agreement on hiring profiles before roles opened, which is where most of the wasted time in a hiring process is spent, and they left the team with more structure and better data than they had in September.

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