Stop leaving money on the table with manual billing workflows

Your billing team is trapped in a spreadsheet maze, and every error costs you days of rework.

Charge capture happens across multiple systems with no validation layer. Coding errors slip past because human coders review hundreds of charts a day. Claims bounce because submission workflows are manual, error-prone, and slow. Meanwhile, your cash flow stalls while claims sit in queues waiting for a human to notice a coding mistake.

Missed or late charge capture

Charges slip through gaps between EHR, billing system, and departmental worklists. Finance discovers missing revenue weeks later.

Coding accuracy bleed

Human coders miss nuance or misapply guidelines. Invalid codes ripple downstream, causing denials and rework cycles.

Manual claim submission delays

Claims sit in batch queues or wait for a human to hit 'submit.' Secondary insurance claims take weeks to route correctly.

First-pass denial rates that crater AR

Each denial means staff time spent investigating, recoding, and resubmitting. Some never recover.

Tribal knowledge in coding rules

Senior coders hold payer-specific workflows in their heads. New hires ramp slowly. Turnover stalls operations.

No visibility into billing bottlenecks

You know billing is slow, but can't pinpoint where claims get stuck or why denial rates spike.

AI billing automation works when you build it inside your operation, not when you buy it off a shelf.

We don't ship generic billing software. We embed a small product and engineering team inside your billing operation, map your exact workflows (payer rules, charge capture touchpoints, coding variations), and deploy AI agents that validate charges, suggest correct codes, and route claims to submission without human friction. Your team gains leverage instead of losing control.

Score the workflow first

We map your charge capture, coding, and submission processes in detail. We quantify the cost of each error and delay. Only then do we scope an AI build against the bottlenecks with the highest $ impact.

Build into your systems, not around them

AI works best when it lives inside your EHR, billing system and claim submission flow — not as a separate tool your team has to context-switch into.

Validation before automation

We design coding validation and claim readiness checks into the workflow so humans catch edge cases before they become denials.

Payer-specific, not one-size-fits-all

Every payer has different coding rules and submission requirements. We encode your payer matrix into the system so the AI respects your contract terms.

First-pass accuracy over speed

It's faster to submit a claim with 98% confidence than to rush and spend 2 weeks on rework. We optimize for clean claims, not throughput.

Your team stays in control

We design human review and escalation paths so your coders make the final call, and the AI surfaces risk before submission.

From workflow analysis to production billing AI in six weeks

We start with an Opportunity Sprint to map your exact billing workflows and score the highest-impact automation opportunity. Then we deploy a small forward-deployed team to ship production AI into your operation.

Opportunity Sprint · Week 1

We embed with your billing, coding, compliance and IT leads. We trace charges from point of capture through submission. We quantify error rates, denial reasons, processing time, and cash impact for each step.

System design and payer ruleset · Week 2

We translate your chosen opportunity into a technical design. We map your payer contracts, coding rules, and submission requirements. We design human escalation paths so your team stays in the loop.

Forward-deployed build · Weeks 3–6

Our engineers sit with your billing and coding team and ship the system against real claims data. We test on staging, monitor for edge cases, and refine based on your team's feedback before production rollout.

Measure, refine, and compound · Week 7+

We track actual impact against the success metric from week 1. We surface the next highest-opportunity workflow and queue it. Each new build is faster because your billing data, payer rules, and integration substrate are already in place.

Relevant services

Most engagements combine three or four of these. Start with what hurts most.

AI workflows we've deployed in health billing operations

Each build targets a specific bottleneck inside your billing workflow. These are the patterns that move revenue recognition fastest.

• 01
  Charge validation and completeness agent

  Reads charges from your EHR, validates against billing rules (correct department, correct code range, required modifiers present), and flags incomplete or suspicious charges before they hit the billing system.

  +18% charge capture, −65% billing rework

• 02
  Coding suggestion and compliance engine

  Analyzes clinical documentation and suggests primary and secondary codes using your payer guidelines. Flags codes that violate bundling rules or exceed frequency limits before submission.

  +22% first-pass accuracy, −41% denials

• 03
  Claim readiness bot

  Checks each claim against submission requirements: correct payer format, valid patient insurance, required documentation attached, coding consistent with your contracts. Routes clean claims to submission automatically.

  −8 days in claims queue, +34% on-time submission

• 04
  Secondary insurance routing copilot

  Identifies claims eligible for secondary billing, determines correct payer sequence, and auto-generates secondary claims with adjusted coding. Handles COB rules and carve-outs.

  +$2.4M annual secondary revenue

When to talk to us

Some patterns we hear on the first call. If two or more of these are true, the conversation is worth having.

• →Charges slip through gaps between EHR, billing system, and departmental worklists. Finance discovers missing revenue weeks later.
• →Human coders miss nuance or misapply guidelines. Invalid codes ripple downstream, causing denials and rework cycles.
• →Claims sit in batch queues or wait for a human to hit 'submit.' Secondary insurance claims take weeks to route correctly.
• →Each denial means staff time spent investigating, recoding, and resubmitting. Some never recover.
• →Senior coders hold payer-specific workflows in their heads. New hires ramp slowly. Turnover stalls operations.
• →You know billing is slow, but can't pinpoint where claims get stuck or why denial rates spike.

What health billing leaders ask us