Persimmon AI (ex-Kollektiv.ai) Early-Stage AI Startup Landed 5 Unicorn-Grade Engineers Who Had Offers from FAANG

  • AI Team Setup
  • Eastern Europe
  • Hard-to-Find Tech Skills
HQ
USA
Company size
11-50
Funding raised
Undisclosed
Lead investors
Undisclosed
Team location
Europe
Cooperation time
since 2025
Product
AI platform for dental revenue cycle management
Clients
Not yet disclosed

PERSIMMON: 5 Unicorn-Grade AI Engineers in 13 weeks

Persimmon AI (ex-Kollektiv.ai) is an early-stage US AI startup on a mission to automate dental revenue cycle management – one of the most complex and consistently underserved administrative functions in healthcare. Its AI platform handles the full billing workflow autonomously, from insurance eligibility checks and pre-authorization to claims management and payment reconciliation.

Issue:

Persimmon AI had a clear vision and a high bar. To build an AI platform that could genuinely automate dental revenue cycle management at scale, the company needed engineers who had already solved hard problems.

The challenge wasn’t knowing what they needed. It was finding it.

Early-stage startups compete for the same top-tier AI talent as every well-funded AI startup in the US. Without a recognized brand, a polished careers page, or an established engineering reputation in the market, the best candidates have little reason to respond – and every reason to stay where they are.

Standard recruiting approaches don’t work at this level.

Eastern Europe had the talent density and the engineering caliber Persimmon AI needed. What it lacked was a partner who could headhunt at the top of that market, sell an early-stage opportunity to candidates with better-known options, and deliver a pipeline precise enough that leadership time wasn’t wasted on irrelevant CVs.

Solution:

Alcor assigned 7 recruiters and researchers to the search, with a sourcing strategy built for the top 10% of the market.

The approach centered on a targeted list of high-caliber tech companies, with short, precise outreach and structured follow-ups that consistently outperformed standard InMail response rates. The result was a pipeline where every candidate was genuinely worth the client’s time – including profiles sourced directly from Google and NVIDIA.

Persimmon AI’s requirements went well beyond a strong tech stack – Master’s degrees, FAANG pedigrees, research publications, and proven experience on complex, high-ownership engineering projects. Every profile that entered the pipeline had already been filtered for technical depth, seniority, and the problem-solving mindset Persimmon AI needed.

SOLUTION

5 senior AI engineers in 13 weeks
Alcor built a team of 5 senior AI engineers in 13 weeks – Master’s degrees, FAANG backgrounds, LLM production experience required. With an average of 8 CVs per hire, that’s not a timeline volume recruiting can deliver.
Google and NVIDIA in the pipeline
Alcor’s tech recruiters reached engineers at Google and NVIDIA – profiles that don’t respond to standard outreach. Targeted messaging with deliberate follow-ups made the difference.
2 hires from 6 candidates
Drawing from its 325K-candidate pool, Alcor ran a full end-to-end recruitment process for both Senior ML Research Engineer roles and produced just 6 candidates. Both positions were filled. No pipeline noise, no wasted interview cycles.
"Insane" candidate quality
Andrey Akselrod described Alcor’s candidate quality as “INSANE levels.” For the Backend Engineer role, he skipped initial screening entirely and went straight to a full technical interview. The candidate’s profile made it an easy call.
Beat a FAANG Offer
One top ML Research Engineer had multiple competing offers, including one from a FAANG company. Alcor and the CEO ran a coordinated engagement push that clearly articulated the candidate’s potential impact at Persimmon AI. He chose the startup over the tech giant.
Hired experts in:
Python PyTorch TensorFlow HuggingFace LLM Tooling RAG Architecture AWS Docker Kubernetes Kafka

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