ci·pher (noun) — an algorithm used to encrypt and decrypt data; the key that turns unreadable code back into plain text.
About Cipher

Your claims data is written in code. We built the key.

To most people responsible for a health plan's budget, claims data might as well be encrypted. Thousands of rows, opaque codes, formats that change by carrier. The information is all there; it's just unreadable. Cipher is your key.

Why We Exist
The problem we lived

The people managing America's largest segment of healthcare spend are flying blind.

Employer-sponsored health plans cover 150 million Americans and more than $1.5 trillion in annual spend — and the people responsible for that money get tools that would be unacceptable anywhere else in the business: analytics that make fundamental errors, reports that never become action, and data locked in someone else's warehouse.

We started Cipher because two things finally changed: employers won the right to their own data, and AI made senior claims expertise deployable as software. Someone had to put those together properly.

Founding Team
Operators who lived this problem
Ben Sanders, Co-Founder and CEO of Cipher
Co-Founder · CEO

Ben Sanders

Healthcare executive with a track record of scaling businesses. Former SVP at Lantern Specialty Care on the CEO's leadership team, where he launched the cancer and infusion service lines and led the firm's analytics and data science organization. Before Lantern, Engagement Manager at McKinsey & Company, directing multi-billion-dollar transformations for Fortune 100 enterprises.

Education — MBA, Finance · Kellogg School of Management · BS, Northwestern University
Sarah Hewes, Co-Founder and Head of Engineering of Cipher
Co-Founder · Head of Engineering

Sarah Hewes, PhD

Healthcare strategy and data science leader with deep expertise in medical claims data, computational modeling, and applied AI. Former Director of Strategy & Research at Lantern Specialty Care, where she translated the firm's specialty-care bundling methodology into deployable client packages and built its first machine-learning models — including predictors of surgical need. Before Lantern, consultant at Boston Consulting Group on digital transformations and claims-based healthcare research.

Education — PhD, Bioengineering · Rice University · BS, Johns Hopkins University
How We Work
Four rules, no exceptions
01

Plain English

If a report needs a translator, it isn't finished.

02

Conclusions first

Every page leads with what it means, not how we got there — the workings are underneath for anyone who wants them.

03

Evidence over anecdote

Benchmarks and quantified drivers, not hunches.

04

Actions, always

Analysis that doesn't end in a decision is decoration.

We'd like to show you your plan in a new language.

Thirty minutes, no obligation — bring your CFO, or your toughest client.

Book a demo  →
or write to info@cipherhealthanalytics.com