Company details

HEADCOUNT

25-99

ORG TYPE

Startup

SECTOR

Healthcare & Life Sciences

WEBSITE

http://www.teton.ai/

About the company

Teton.ai builds computer-vision and multimodal AI that helps care staff monitor residents and patients and reduce documentation burden in hospitals and senior living. The company positions the platform as a real-time “data layer for the point of care”, with deployments across multiple countries. Teton.ai is headquartered in Copenhagen and is scaling commercial teams across the US and parts of Europe. Public announcements in 2025 describe a Series A sized to expand predictive care and rollout.

Locations and presence

Teton.ai is office-first in Copenhagen, with many roles tied to being on-site there. The company is also hiring US-based commercial roles and has advertised a Vienna-based business development role.

Palpable Score

52.9

/ 100

Teton.ai has a few credible early-career entry points, but current hiring leans experienced and commercial-heavy, so graduate access looks uneven. Public signals around learning culture exist, yet pay transparency and early-career outcomes are hard to verify from what is publicly posted.

Pillar 1: Early-career access

Score

9.8

/ 20

The company has advertised roles that explicitly fit early-career candidates, such as a Supply Chain / Procurement Specialist framed as suitable for “early-career experience” (2–3 years).
Teton.ai’s current public job board is dominated by director-level and senior commercial roles (for example Business Development Director, Director of Customer Success, Country Director), which reduces the number of 0–3 year entry points.
The company has posted paid internships historically (for example a Data Engineer Intern listing with defined compensation), but internships are not consistently visible as an active route on the current careers board.

Pillar 2: Hiring fairness and transparency

Score

10.8

/ 20

The company uses a consistent hosted careers board (Polymer) for many roles, which supports a standard application path.
Teton.ai job pages include clear responsibility lists and “what we offer” sections, which helps candidates understand scope before applying.
The company has at least one public interview report describing a take-home assignment that felt far larger than stated and unpaid, which is a fairness red flag for early-career applicants.

Pillar 3: Learning and support

Score

12.5

/ 20

The company publicly frames the environment as “learning-focused” and office-first to support close collaboration, which can help juniors ramp faster.
Teton.ai’s early-career operations role copy includes explicit growth potential (for example a path to team lead in 1–2 years in supply chain), which is a concrete development signal.
The company does not publicly spell out onboarding structure, mentoring, or review cadence in role pages, so support quality is hard to confirm across teams.

Pillar 4: Pay fairness and stability

Score

9.3

/ 20

The company frequently mentions stock options or a warrant program as part of compensation in public materials, but most roles do not include salary ranges.
Teton.ai lists standard benefits for some US roles (for example health insurance, PTO, 401(k)), which supports stability where applicable.
The company’s limited first-party pay detail makes it hard for early-career candidates to judge whether offers are market-aligned, especially outside the US.

Pillar 5: Early-career outcomes

Score

10.5

/ 20

The company has a small set of positive employee-review signals describing strong talent density and a demanding environment, but these are not specific to early-career progression.
Teton.ai is expanding across regions and functions, which suggests ongoing team building, but public sources do not confirm junior retention or promotion patterns.
The company does not publish measurable early-career outcomes such as intern-to-offer rates, typical time-to-progression, or cohort-based retention.