Mission
Make opportunities discoverable, understandable, and actionable for everyone-regardless of geography or background.
Who we serve
Students, early-career talent, mid-career professionals, and hiring teams seeking high-quality, intent-driven matches.
Core capability
Convert unstructured resumes & job posts into structured career signals and deliver semantic, personalized recommendations.
Our Values
What guides us - principles we use to build fair, useful, and scalable career products.
Equity
Opportunity for every geography and background - we build features that widen access and remove location bias.
Clarity
Actionable, understandable signals - not black-box recommendations. Users and employers see why a match was suggested.
Control
Users own their data and experience - configurable privacy controls let candidates decide what to share and when.
Scale
Built to serve millions without losing relevance - efficient pipelines and model design keep results fast and accurate at scale.
What is Vertices?
Vertices is a purpose-built career intelligence platform that helps people find the right next step in their careers—whether that’s an internship, a role change, or a leadership position. We apply machine learning to transform messy inputs (resumes, job descriptions, employer signals) into structured, interpretable career signals. Using multi-dimensional embeddings that capture skills, professional tone, and intent, Vertices delivers semantic search and personalized recommendations that prioritize fit and future potential over surface-level keyword matches.
- Convert resumes into editable, structured career profiles that evolve with the user.
- Create role- and skill-level representations to power intent-aware recommendations.
- Continuously vet and refresh listings so results stay relevant and timely.
- Provide privacy-first controls and clear match explanations so users stay in control.
How our AI helps people
We focus on three practical signals: what a person can do (skills), what they want next (intent), and how they present themselves (tone/summary). By modeling these dimensions, we can surface roles that fit a candidate’s trajectory and explain why a match was recommended.
Intent-aware matches
Recommendations weighted for what the candidate actually wants next—not just their past roles.
Living profiles
Editable profiles that improve over time as candidates refine their experience and goals.
Trust, privacy & fairness
Users control what they share with employers. Our recommendations emphasize interpretability—clear reasons why a role was suggested—and we continually audit models to reduce bias and promote equitable outcomes.