Cubit by Maiden Labs

Maiden Labs Intelligence API

Measure. Don't Guess.

Programmatic access to the world's most comprehensive data on AI and work. 923 occupations. 18,000+ tasks. Empirically grounded.

923

Occupations scored

18,796

Task-level analyses

182K+

AI benchmark evaluations

120

Skills & abilities mapped

A Multi-Dimensional Framework

Single “automation risk” scores conflate distinct phenomena. Cubit separates AI exposure into three independent pillars, each measuring a different dimension of how AI intersects with human work.

Structural Exposure

Can AI technically access and execute this work? Measures how rule-based and digitally accessible each task is.

Built from Procedural Intensity and Digital Accessibility scores.

Human Imperative

Does the work fundamentally require human presence? Captures physical embodiment and socio-emotional depth.

Patients want human doctors. Clients want human advisors. This pillar quantifies that.

Demonstrated Capability

Can current AI models actually perform the required skills? Grounded in 182,000+ empirical benchmark evaluations, not expert opinion.

Mapped from Stanford HELM to O*NET task requirements.

These three pillars combine to classify every task into one of four strategic zones: Automation, Augmentation, Human-Centric, and Status Quo — enabling precise, actionable workforce strategy.

What the API Does

Six capabilities that turn workforce intelligence from a static report into a programmable platform.

Job-Level AI Impact Scores

Automation susceptibility, human resilience, and balanced impact scores for every occupation. Custom-weightable.

Task-Level Decomposition

Drill into the specific activities within a job. Each task scored on four dimensions with natural language explanations.

Semantic Search

Move beyond SOC codes. Find matching occupations, tasks, and skills from natural language descriptions.

Regional Intelligence

Employment, wages, and risk metrics broken down across 384 metro areas with at-risk wage calculations.

Career Transitions

Data-driven reskilling pathways using 120-dimensional skill profiles, gap analysis, and training priorities.

Custom Scoring

Apply your own dimension weights. Same data, different strategic lens — because context matters.

Built for Decision-Makers

Cubit serves organizations that need to act on AI workforce intelligence, not just read about it.

Enterprise Companies

AI exposure and reskilling dashboards across your entire organization.

Consulting Firms

Data-backed workforce strategy and industry disruption reports for clients.

HR Tech Platforms

Embed AI readiness scores directly into workforce planning tools.

Researchers & Academics

Structured, reproducible data for research on AI, labor, and job markets.

Government Agencies

Model employment impacts by region and industry to drive policy decisions.

Financial Institutions

Quantify workforce risk and conduct due diligence on AI automation claims.

Built on Stanford HELM & O*NET · Validated against ILO, OpenAI & CAIS datasets

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