Hospitals and clinics shouldn't have to choose between financial health and patient health. But today, they do.
Healthcare finance teams are drowning in manual data work—pulling numbers from multiple systems, building spreadsheets, answering endless questions from operators. By the time they finish analyzing last month's performance, they're already behind on this month's decisions.
The result? Finance leaders are forced to make difficult tradeoffs: cut services to stay solvent, or keep services running and risk financial instability.
What We Do
Translucent is healthcare's financial operating system. We automate the manual data work that consumes finance teams—connecting fragmented data sources, running analyses, and surfacing insights instantly.
Instead of spending days building reports, finance teams can focus on what matters: moving the margin and making strategic decisions that improve both financial performance and patient care.
Why It Matters
When healthcare finance teams have the financial clarity they need, hospitals can maintain strong margins while delivering excellent patient care. No more forced tradeoffs between the two.
We serve health systems and medical groups across the United States—from large multi-billion dollar organizations to small rural hospitals where every decision affects whether patients can access care locally.
Our Team & Backing
Translucent is backed by GV, NEA, FPV Ventures, Virtue, and Redesign Health. We're headquartered in New York City and bring together expertise in agentic AI, healthcare operations, and enterprise software.
Rating Reviews
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Pros: The remote work setup at Translucent AI is fantastic, offering genuine work flexibility that really helps with managing personal life. As a Software Engineer in the AI sector, I've had exposure to some really interesting projects. The team environment is supportive, and there's a culture that encourages continuous learning and professional development. It's a great place to grow your skills.
Cons: While flexibility is high, project timelines can sometimes feel a bit rushed, leading to increased workload during crunch periods. Sometimes, decision-making processes or approvals from senior leadership can be a little slow, which can impact development velocity. Overall, these are minor points in an otherwise positive remote tech role.
Advice to Management: Consider streamlining approval workflows to improve project velocity and ensure consistent communication across remote teams about priorities and timelines.
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What is the typical salary range for a Machine Learning Engineer at Translucent AI in San Francisco?
Based on my experience as an MLE at Translucent AI, the compensation for roles like ours in the San Francisco AI sector is quite competitive, often including a base salary plus stock options, aligning with industry standards for a mid-sized tech company.
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