Company details

HEADCOUNT

25-99

ORG TYPE

Startup

SECTOR

Retail & Consumer

WEBSITE

https://www.neurolabs.ai

About the company

Neurolabs builds an enterprise image recognition platform called ZIA for consumer packaged goods brands and retailers. The platform uses synthetic data and digital twins so teams can recognise products on shelves faster than traditional computer vision approaches that rely on huge volumes of real-world labelled images. Neurolabs positions the product around retail execution visibility, catalogue management, and workflow automation for field and commercial teams. The company operates as a remote-first team with offices that anchor hiring and collaboration.

Locations and presence

Neurolabs lists a London office in King’s Cross and an Edinburgh office, alongside remote and hybrid working arrangements depending on role. Some job listings also reference additional European presence for distributed teams.

Palpable Score

65.0

/ 100

Neurolabs shows real early-career entry points through roles capped at up to three years’ experience and a visible internship-to-lead progression example. Hiring steps are often clearly spelled out with timeboxes, but candidate feedback mentions long waits and inconsistent interview execution, which pulls the score down.

Pillar 1: Early-career access

Score

13.1

/ 20

The company has advertised roles explicitly open to early-career candidates, including an Implementation Engineer role asking for up to 3 years’ experience.
Neurolabs has evidence of internships feeding into longer-term roles, including machine learning internship experience referenced publicly.
The company currently shows “no job openings” on the primary application portal, which limits the observable volume and consistency of 0–3 year hiring right now.

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Pillar 2: Hiring fairness and transparency

Score

11.2

/ 20

The company’s job ads can be unusually specific about stages, including an intro call, take-home task limits, culture interview, and founders interview with approximate timings.
Neurolabs outlines multi-stage assessment processes (including take-home work and follow-up reviews) that set expectations, but the workload can be heavy relative to some roles.
The company has candidate feedback describing long waiting times and interview rounds where interviewers appeared unprepared, which is a fairness and consistency risk.

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Pillar 3: Learning and support

Score

15.3

/ 20

The company describes structured support habits such as regular check-ins, feedback sessions, and open-door access to management in public culture content.
Neurolabs has employee feedback pointing to frequent 1:1s and deliberate attention to personal development from founders and managers.
The company has intern feedback describing encouragement to join meetings outside a narrow remit, which is a practical signal of learning-by-exposure rather than sink-or-swim delivery.

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Pillar 4: Pay fairness and stability

Score

13.2

/ 20

The company has published salary ranges in some listings, including an SDR range (£40–50k) and a stated salary cap for an Implementation Engineer role (up to £50k).
Neurolabs lists tangible benefits that matter for early-career stability, including private medical coverage (post-probation in some listings), equity options, and generous time off.
The company does not show consistent pay ranges across all roles publicly, and the available third-party salary sample is small, which caps confidence on pay fairness.

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Pillar 5: Early-career outcomes

Score

12.2

/ 20

The company has a publicly highlighted progression example from a machine learning internship to an engineering lead role over a multi-year tenure, which is a concrete outcome signal.
Neurolabs has generally positive employee sentiment in reviews that reference skill growth, regular feedback, and support, but the review volume is limited.
The company has advertised junior and mid-level roles (including commercial roles and early-career technical roles), yet there is limited public evidence on promotion rates, retention across cohorts, or repeat annual junior intake.

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