Worki Raises $2.75M for Healthcare’s AI Workforce Stack

By Daniel Okafor

Worki closed a $2.75 million pre-seed round led by Redesign Health and Healthliant Ventures, according to Co-Founder and CTO Harvey Hongwei Li. Li said Healthliant Ventures is the venture arm of Tanner Health System and Worki already works with Tanner Health, BJC Healthcare, and several other large systems across the country.

What does Worki’s five-layer system do?

Li describes Worki as infrastructure for integrating AI into healthcare operations while people keep control of critical decisions. He said it connects fragmented systems, finds improvement opportunities and coordinates people and workflows.

• Career Amplifier: Li said it personalizes internal career paths, required skills and growth opportunities with AI. He said the product improves visibility and connection, not only retention.
• JD Modernizer: Li said it uses AI-powered standardization and workforce analytics to update job descriptions. He said it can revise hundreds or thousands of disconnected records, standardize skills and role requirements, and identify gaps or inconsistencies.
• ShiftSense Scheduling Coordination: Li said it coordinates shift coverage, float pools and open shifts alongside existing scheduling systems.

Li said the products sit within Worki’s five-tier Workforce Unifying Infrastructure.

• Unify: Li said Worki connects data from HR, scheduling, credentialing, learning and payroll platforms into a unified workforce intelligence layer without replacing those systems.
• Pathways: Li said it maps roles, workflows and AI opportunities with research, proprietary workforce datasets and de-identified coalition data from health systems, giving leaders a phased starting plan.
• Orchestrate: Li said governed AI agents research, identify opportunities and coordinate tasks while a Human Conductor retains approvals and decision authority. He said: “But one thing that’s very important to us philosophically is that there is always a human in control.”
• Amplify: Li said governed agents support employee goals, daily tasks and cross-system workflows. They can automate work and make recommendations, but people keep authority.
• Scale: Li said the final tier extends across the enterprise so connected roles, workflows and systems compound the benefits. It supports broader AI-enabled workforce operations without replacing existing infrastructure and enables coalition-level intelligence through Worki’s Infrasharing model.

Why does Li think healthcare needs it first?

Li said he came to the United States more than 16 years ago and earned a Ph.D. in machine learning and AI from the University of California, Berkeley. Berkeley sparked his interest in entrepreneurship, and he chose Uber over opportunities in technology, finance and academia.

At Uber, Li said he joined early, served on the founding team for the Customer Support division and led early machine-learning, AI and data-science initiatives. He spent four years across customer support, Uber Freight, Uber Safety and new business initiatives.

Li said support cost Uber hundreds of millions of dollars annually. Tens of thousands of workers served more than 300 cities, where high attrition reflected repetitive, stressful and emotionally draining work.

Li said his teams used AI to learn agents’ strengths and weaknesses and route tickets to the person most likely to resolve them. Copilots first observed workflows and suggested responses, later drafted replies for human approval, and eventually automated repetitive, low-risk work. He said the system improved customer outcomes and employee experience.

Li sees healthcare at an earlier stage because it is more complex, regulated and human-centered, making trust more important. He believes AI can reduce administrative burden, support decisions and return time to clinicians.

Li joined Airbnb in 2019 as an early machine-learning hire for Airbnb Lux. The pandemic brought crisis leadership at scale, while a nonprofit for people affected by layoffs and a side startup revived his entrepreneurial interest. Conversations across insurance, logistics, real estate and healthcare led him to Worki.

Who is building Worki?

Li said CEO Craig Ahrens brings 20 years in healthcare workforce operations and startup scaling. CCO Michael Biggs brings more than 30 years in healthcare management leadership, finance and consulting.

Li said the founding team combines technical AI knowledge with operating experience. He said: “We’re not building AI to replace workers but to amplify people, reduce operational burden, and help organizations support employees more effectively.”

He described the product internally as an Employee Success Platform, applying customer-success principles to employee support. Li said people handle ambiguity, empathy and judgment, while AI handles speed, automation, pattern recognition and continuous operation.

Li said the AI industry has moved from machine learning to large language models, prompt engineering and AI agents. He views the next phase as human-AI collaboration and says the founding combination is rare in healthcare.

How is Worki positioned against legacy vendors?

Li said Worki does not ask health systems to rip out legacy systems. It integrates existing tools, avoiding the massive migrations and consolidation that he says legacy HRIS vendors require because those projects are expensive and disruptive.

He said most AI systems infer broad skills or generate generic recommendations. Worki focuses on task-level intelligence within actual clinical workflows, not generalized competencies, dashboards or chatbots.

Li said Worki prioritizes amplification because healthcare already faces shortages, burnout and operational overload. Its infrastructure aims to reduce administrative work and simplify workflows while preserving human judgment. Li’s sequence is infrastructure first, intelligence second.

Li said the backing matters because Redesign Health and Healthliant Ventures understand healthcare operations. Additional health-system partnerships and expansions are underway.

What comes after the pre-seed round?

Li said Worki will scale the platform, deepen health-system partnerships and expand the ecosystem’s network effect. To support growth, the company anticipates raising a larger Seed or Series A round.

Li said Worki aims to become infrastructure rather than another healthcare SaaS vendor. He compared the model with Visa: the payment network does not own every bank, but provides rails for the ecosystem to operate together.

Li expects intelligence to compound as health systems join, making workflows smarter, reducing friction and improving economics. Healthcare comes first because fragmentation is severe; logistics, education, public-sector organizations and municipalities face similar needs.

Li’s next test is whether early health-system traction can become repeatable expansion without forcing costly replacements of the infrastructure health systems already use.