Company details

HEADCOUNT

100-499

ORG TYPE

Startup

SECTOR

Technology & Digital

WEBSITE

https://www.aily.ai

About the company

Aily Labs builds an enterprise “decision intelligence” product that puts AI-driven recommendations into the hands of business users, often through a mobile-first app experience. Public materials position the product around turning siloed data into actionable insights for functions like finance, supply chain, R&D, and commercial teams. The company presents as a fast-growing scale-up selling into large enterprises, with technical teams spanning data science, engineering, and customer-facing “AI adoption” work.

Locations and presence

Public profiles and job posts reference hubs across Munich, Barcelona, Madrid, Cluj, and New York. Hiring also points to hybrid setups in Spain and a US commercial footprint in New York.

Palpable Score

62.4

/ 100

Aily Labs offers real early-career entry points in technical roles, including a clearly titled junior infrastructure role and internship options in data science. The overall score is limited by inconsistent pay transparency outside the US and mixed public signals on interview experience and work-life balance.

Pillar 1: Early-career access

Score

14.7

/ 20

The company has publicly listed a Junior Infrastructure Engineer role (hybrid in Barcelona or Madrid), which is a direct 0–3 year entry point rather than a disguised mid-level post.
Aily Labs has also listed Data Science Intern roles (Barcelona or Madrid) with day-to-day data scientist tasks, plus an internship initiative framed around bringing more women into AI.
The company’s wider hiring mix still skews senior across many functions, so early-career access looks present but not consistently high-volume.

Pillar 2: Hiring fairness and transparency

Score

12.0

/ 20

The company describes a structured interview flow in public hiring materials, commonly framed as three interviews including a technical step and leadership conversation.
Aily Labs has a mixed public interview signal, including Glassdoor reporting a low share of positive interview experiences, which raises uncertainty about consistency across teams.
The company rarely posts clear timelines, stage-by-stage expectations, or assessment details on the core careers site, so candidates can’t reliably predict effort and turnaround.

Pillar 3: Learning and support

Score

13.0

/ 20

The company’s internship and ML role descriptions emphasize collaborative work with data scientists and engineers, which is the right setup for early-career learning-by-doing.
Aily Labs includes “continuous learning” and skills growth language in role pages, alongside day-to-day ownership that can accelerate development in a scale-up environment.
The company does not publicly spell out onboarding plans, mentoring cadence, or promotion-ready skill expectations for juniors, so support quality is hard to verify beyond role wording.

Pillar 4: Pay fairness and stability

Score

11.7

/ 20

The company publishes salary ranges for some US roles on LinkedIn, which helps early-career candidates avoid pay ambiguity when applying in that market.
Aily Labs advertises concrete benefits in several role pages such as performance bonus, private health insurance, flexible benefits, and hybrid work policies.
The company does not consistently publish salary ranges for European roles, which caps confidence on pay fairness for early-career applicants before interview stage.

Pillar 5: Early-career outcomes

Score

11.0

/ 20

The company has mixed employee sentiment on Glassdoor, including mid-range work-life balance and only moderate recommendation rates, which suggests uneven early-career sustainability depending on team.
Aily Labs shows ongoing hiring that includes junior and intern roles, but public evidence of structured progression from junior to mid-level inside the company is limited.
The company’s public data does not include early-career retention, time-to-promotion, or internal mobility reporting, so outcomes can’t be scored higher without stronger evidence.