HRPulsar measures AI fluency from real work, not self-reported confidence — inside an open-source talent platform you can audit and self-host.
Most companies still can't answer four questions about their own workforce:
Which skills does your team already have?
Titles and org charts don't say what people can actually do.
Which capabilities are missing?
Gaps surface as missed deadlines and failed hires — not as data.
Who is ready to work with AI?
Adoption is uneven, and self-reported confidence is not a signal.
How do you develop talent for what's next?
Without a skills baseline, development budgets are spent on guesses.
Without this foundation, scaling AI across the organization stalls.
The measurement sits inside a talent platform for AI-first companies: people, skills, hiring and development in one system. All of it ships today — open the tour or the demo and see for yourself.
Define & measure
Model the skills your company needs, then check them with assessments and exams.
Hire & mobilize
Bring demonstrated skills in from outside — or find them on teams you already have.
Develop & promote
Close the measured gaps and connect growth to a career ladder people can see.
The AI layer
Not a separate module — it works inside every module above.
Framework generation, semantic search and suggestions across every module.
AI Fluency is an observable skill, not self-reported confidence. HRPulsar measures it with a methodology based on Reid Hoffman's three levels.
Find capability gaps, compare teams, and build development programs that close them.
A measurement that can be verified and that travels with the person becomes a standard over time. A standard belongs to whoever holds the network behind it — and a network is the one thing that cannot be bought with a funding round. Three of the four below do not exist yet, and the cards say which.
An HR score dies with the HR system that issued it.
A level earned at one employer will travel with the person to the next — signed, and owned by the person it describes.
A claim on a CV is a claim.
A third party will check a stated level against our signed API, so the level can be verified rather than trusted.
A single company only sees itself.
The Hoffman 60 / 30 / 5 distribution across companies, published per industry once it clears the 20-tenant k-anonymity threshold.
AGPL gives the product away.
The core is live and self-hostable, and that is the distribution channel. What no single instance can build alone is the network above it — which is where the business will sit.
The network has no cohort today. It starts with the first design partners.
There will no longer be solo specialists working alone. Each of us will operate together with our own set of AI agents.REID HOFFMAN · LINKEDIN CO-FOUNDER · FEBRUARY 2026
Today HRPulsar manages the human side of an AI-first company. V2 extends the same skills-first core to AI agents — one workforce graph, a shared capability model, governed work routing.
Competencies, assessments, development, recruiting, grading, exams, talent market and analytics — open source, live in the product and the demo today.
Agent profiles next to people, work orchestration, quality controls and outcome analytics for hybrid teams — the roadmap we are building toward.
Spin up a sandbox preloaded with a sample team and its usage signals. No installs, no spreadsheets — see how the fluency map reads, which gaps it surfaces, and what a manager does and does not get to see. Your own data comes later, on your terms.
Before that: the signals we use, and the ones we refuse to collect →
Eight companies, six months, measuring the same thing the same way. They get the first numbers and a say in what gets built; we get a dataset nobody else has. That is the whole trade.
Free, self-hosted
Credits
