Revenue cycle teams lose hours every week to repetitive, manual processing — data entry, cross-referencing, reconciliation. Through a controlled pilot, we apply AI at exactly those points, working alongside your team’s judgment rather than replacing it.
The workflows we target are rarely glamorous — payment posting, adjustment coding, claims triage — but they’re often where the largest, most avoidable losses in a revenue cycle actually happen. A backlog in payment posting doesn’t just delay your close; it hides the discrepancies that would otherwise surface immediately, letting small errors compound into larger ones by the time anyone notices.
We also pay close attention to how a workflow interacts with the ones around it. Accelerating payment posting without addressing a slow eligibility verification process upstream, for example, just moves the bottleneck rather than removing it — which is why any pilot starts with a clear view of your broader revenue cycle, not an isolated workflow.
Built for the revenue cycle workflows where your team loses the most time
Claims Intake & Triage
Automatically routing incoming claims based on payer, priority, and completeness so your team works the right claims first.
Eligibility Verification
Checking coverage and benefits automatically instead of manually calling or logging into multiple payer portals.
Payment Posting
Matching payments to claims and posting them accurately across your payer mix.
Adjustment Coding
Correctly applying CO, PR, and OA adjustment codes based on payer remittance data.
Reconciliation
Catching discrepancies between your billing system, clearinghouse, and bank deposits before they become month-end surprises.
Each of these workflows can be piloted independently or as part of a broader engagement, depending on where your organization’s current bottleneck actually sits.
In every pilot, we deliberately keep your team in the loop at decision points that carry financial or compliance risk. AI handles volume; your team handles judgment calls.
AI Handles
- High-volume, low-ambiguity work
- Reading a remittance
- Matching a payment to a claim
- Flagging an unusual adjustment
Your Team Handles
- Whether to appeal a denial
- How to handle an unusual payer exception
- When a pattern in the data signals a bigger problem worth escalating
- Decisions that carry financial or compliance risk
In practice, this means the AI in a pilot handles the high-volume, low-ambiguity work — reading a remittance, matching a payment to a claim, flagging an unusual adjustment — while your team makes the calls that require judgment: whether to appeal a denial, how to handle an unusual payer exception, or when a pattern in the data signals a bigger problem worth escalating. We design the handoff between AI and human deliberately, rather than defaulting to full automation and hoping for the best.
RCM Workflow Acceleration is currently offered through controlled pilots, so we don’t yet have published outcome data to share — and we’d rather tell you that plainly than imply results we can’t yet back up.
What we can tell you is how we measure success: hours of manual work removed, reduction in days in accounts receivable, and improvement in first-pass posting accuracy — the same metrics your finance team already tracks. Every pilot is scoped with clear, agreed-upon success criteria upfront, evaluated against your own baseline rather than an industry average, and we’ll publish verified results here as pilots complete.
A member of our team will reach out within one business day to schedule a short discovery call — no obligation.