Every dollar spent on U.S. healthcare visits starts with a medical chart. A clinician documents the visit. A coder turns the note into billing codes. A health plan decides if the documentation supports the bill. The chart is the backbone of the truth of the entire transaction, and far too often it is wrong.
The consequences land on both sides. For providers, under-documented care goes unbilled, leaving revenue on the table for work they already provided or patients upset with out-of-pocket bills. Over-coded care gets paid, then audited, then fiercely clawed back – sometimes years later – with the findings extrapolated across similar claims. Codes that do not match the note create compliance exposure, with crackdowns looming from payers and regulators. For value-based health plans and provider groups, documentation that fails to capture a patient’s true conditions can distort risk adjustment and quality scores, which determine how these organizations are paid in the first place.
The industry has long accepted this as a cost of doing business. Providers manually spot check 10% of charts or fewer, usually weeks after the visit. Health plans review the same records with different tools and different standards. Errors surface late, if at all, and the two sides spend billions arguing over them. One 2025 report put the cost of claims adjudication for U.S. healthcare practices above $25 billion a year.
AI is making that fight faster, not smaller. Providers are buying AI to defend their bills, and payers are buying AI to challenge them. We believe the real opportunity is upstream: getting the record of truth right for both sides before a claim is ever submitted.
That is why we are excited to lead Charta Health’s $55 million Series B, alongside our friends at Bain Capital Ventures, Madrona, South Park Commons, and QuantumLight.
Why Charta stood out
Charta’s AI reads clinical documentation the way an expert coder and quality auditor would. It pulls every chart from the electronic health record (EHR), checks it against specialty coding guidelines, state and payer rules, and the organization’s own clinical protocols, flagging what the documentation supports and what it does not. Charta corrects simple issues automatically. Nuanced issues route to the clinician inside the EHR before the claim ever goes out.
Going from a 10% spot check to 100% coverage at consistently high accuracy changes the job for customers. Their teams stop hunting for needle-in-a-haystack problems and spend time only on the exceptions. Revenue increases. Audit exposure decreases. A two-person coding team can do the work that used to take 14 people.
What makes this hard is the long tail: nearly 100,000 codes, with every permutation of specialty, state, and payer layering rules on top. Charta configures its engine to each customer’s rules and productizes what it learns, so each deployment makes the next one faster. That is why customers choose Charta and continue to expand with it.
One engine, both sides of the claim
Most companies in this category pick a side. Charta serves both. This round further fuels Charta for Providers and supports the expansion of Charta for Payers, two businesses running on a single, independent AI engine.
For providers, that means claims are built to hold up. Customers already include some of the largest outpatient organizations in the country, across primary care, urgent care, behavioral health, pediatrics, and post-acute care. For health plans, Charta for Payers applies the same engine to risk adjustment and quality, with a product suite designed alongside one of the nation’s largest health plans.
When payers and providers evaluate the same chart against the same standard of accuracy, there is less to fight about. That is how the denials-and-appeals cycle shrinks instead of compounding.
Why we invested
We have tracked AI at the intersection of clinical workflows and the revenue cycle for years. Most of what we saw automated the fight rather than ending it. Charta stood out for three reasons.
Customers love it, and they can tell you why. Enthusiasm for the product was consistent: customers said Charta is more accurate than anything they had tried, live in weeks rather than quarters, and built around how they operate. They described rule changes going live within days and a product that keeps getting pulled into new sites, specialties, and use cases. Several had switched to Charta from another vendor. None had switched away.
The market structure favors a neutral layer. Outpatient care runs on a fragmented set of EHRs, few of which were built to run AI across thousands of payer and specialty rules. Providers also want an independent check on the chart, not a system that grades its own work.
The team is built for this. Cofounders Justin Liu and Scott Morris came from Rockset, the real-time data company that became a centerpiece of OpenAI’s product journey. Before writing a line of code, they spent a year earning Certified Professional Coder credentials and interviewing more than 100 healthcare leaders. Today, Charta’s engineering and growth teams are coding-certified, too. That rigor shows in Charta’s rapid growth and customer love.
What’s ahead
The wedge is pre-bill chart review. The ambition is a shared, accurate record of care that both sides of healthcare payment can trust, unlocking point-of-care adjudication. We want to see Charta reach more outpatient practices, and we believe health plans should work from that same record. Charta for Payers is where that begins.
Healthcare does not need more tools to argue about the chart. It needs one source for getting it right. We are thrilled to partner with Justin, Scott, and the entire Charta team as they build it.
Note: Charta Health is an Insight Partners portfolio company.
