Your billing team checks claims, works denials and builds the month-end report by hand. We build AI agents that take the first pass inside your clearinghouse, billing system and EHR, and a person on your team approves anything sent to a payer. Patient data stays in infrastructure you control.
We also build scheduling, patient intake and prior authorization agents, under the same patient data controls. Jason, our COO, runs the call and scopes the first workflow with you.
What the agent can seeOnly the fields this denial needs. The rest of the chart is never retrieved.
Illustrative run. Codes, rules and routing are set per workflow during scoping.
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Pick the workflow that costs your team the most hours. We scope each one as its own build, and the sixth card covers the front office.
The agent checks each claim against the payer's rules and your own edits before it leaves, and sends it back to a biller with the field that would fail.
How the agent knows each payer's rulesThe agent reads every remittance, groups denials by reason code, and drafts the corrected claim or appeal letter with the supporting chart facts attached, for a biller to approve.
How approval gates workThe agent posts what the remittance says was paid, compares it with the contracted amount, and lists every underpayment above your threshold for review.
Built on self-hosted n8nBefore a claim is built, the agent finds unsigned notes and open coding queries and sends each one to the clinician or coder who owns it, with the note attached.
How a context layer protects chart dataThe agent reads the day's denials, accounts receivable and exceptions, and sends each manager the lines that moved, so a payer change shows up the next morning instead of at month end.
See how a build runsThe agent places appointments in open slots, reads referrals into your intake queue and assembles prior authorization packets for your staff to submit. Patient questions go to a chat agent whose replies a second agent checks before they send.
How a second agent checks every replyof claims submitted to private payers are initially denied
Source: Premier Inc., survey of 516 hospitals on their 2022 claims (published March 2024)Premier priced the work that follows a denial. Each figure maps to the step an agent takes on.
More than half were paid in the end, after rounds of appeals. The agent drafts the corrected claim or the appeal with the chart facts attached, and a biller approves it.
The agent sorts each denial by reason code and puts the known fix in front of the person who can approve it, so your staff start from a draft.
That is what providers spend adjudicating with payers. Every claim the agent corrects before submission is one fewer denial to work.
Denials that come back for the same reason, such as missing information (CO-16), have written fixes and a person to approve them. The AI Audit ranks your candidates by value, effort and risk.
Source: Premier Inc., Trend Alert: Private Payers Retain Profits by Refusing or Delaying Legitimate Medical Claims (March 2024).
Six steps from a signed note to a reported payment. The agent takes the first pass at each, and every decision that carries money or clinical weight stays with your staff.
Illustrative. Which steps an agent takes, and which thresholds send work to a person, are set per workflow during scoping.
Every claim line carries protected health information, so the controls sit in the architecture, before a prompt is built.
A context layer between your systems and the agent limits each task to the fields it needs, in line with HIPAA's minimum necessary standard, and masks identifiers it does not need. A denial agent sees the claim lines, the reason code and the supporting note, and never the full chart.
See the context layerWe deploy on self-hosted n8n inside your cloud or data center, so the workflow, its logs and the patient data it touches stay with you. An external model call carries scoped fields only and runs under your own business associate agreement with that provider, or goes to a model you host. Ovidius does not sign business associate agreements.
Read the healthcare architectureA biller approves anything sent to a payer, and a clinician signs off on anything clinical. Every run records the record it read, what it changed and who approved it, so your compliance team has something concrete to review.
See AI governanceOne team carries your workflow from scope to the system running in production, and every build is tested in staging before it goes live. See how we work
Eight phases across strategy, operations, data and systems over 4 to 8 weeks, ending in a ranked 90-day roadmap. The fee is credited toward your first build.
One workflow, the systems it touches and what it will take, agreed before you commit. Owen joins the first calls until you are onboarded.
Built against your real data, in your environment, as production software from the first week.
Into production behind your auth, your governance and your monitoring, with your team trained on it.
Watched, fixed and extended in weekly sprints by the engineers who built it.
AI can automate parts of both, with a person on every decision that carries money. An agent can check claims before submission, post payments from remittance files, sort denials by reason code and draft corrected claims and appeals. For coding, the agent drafts codes from the signed note with the lines that support each one, and a certified coder confirms them. In our builds a biller approves anything sent to a payer.
Our builds keep a person on every decision. The agent takes the first pass, such as finding why a claim was denied and assembling the paperwork, so your staff spend their time approving drafts and fixing exceptions. Which tasks move to the agent is agreed in the scope.
It reads each remittance as it arrives, groups denials by reason code, matches each one to its known fix, and drafts the corrected claim or appeal letter with the supporting chart facts attached. A biller approves before anything goes back to the payer. In Premier's 2024 survey, 54.3% of private payer denials were overturned in the end, so the appeals are worth working.
No, Ovidius does not sign business associate agreements. Any model call that touches patient data runs under your own business associate agreement with the model provider, or goes to a model you host, and the context layer passes it only the fields the task needs. The workflow itself runs on self-hosted n8n in your cloud or data center.
Read access to what your systems already produce: 837 claim files and 835 remittance files from your clearinghouse, your billing or practice management system through its API or a database view, and the payer rules your team works from. The AI Audit confirms what each system allows before anything is quoted.
Yes. An agent can place appointments in open slots, read referrals into your intake queue, assemble prior authorization packets for your staff to submit, and answer patient questions through a chat agent with a second agent checking each reply. They run under the same patient data controls as the billing agents, and the first one can start as an AI pilot.
Each workflow is priced in a written scope before you sign. If you start with the AI Audit, it costs $10,000 to $100,000 depending on scope, takes 4 to 8 weeks, ends in a ranked 90-day roadmap, and its fee is credited toward your first build.
The one with the most volume and the clearest written rules, usually denials that repeat for the same reason or claim checks against known payer edits. If you already know which, book a discovery call and Jason scopes it with you. If you have several candidates, the AI Audit ranks them by value, effort and risk.
If your team also works insurance claims, reconciles payments or keeps records under privacy rules, these pages cover the workflows next to yours.
Quote intake, renewals, certificates and claims intake for agencies, brokers and MGAs, with a licensed person approving coverage.
See AI for insurance agentsBank reconciliations, close files, tax workpapers and client documents, prepared for an accountant to sign off.
See AI in accountingAnswer a few questions about your team and what you want automated, then Jason scopes it with you on the call.
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