Insurance / Benefits Administration
AI Claims Processing & Benefits Administration Platform
A benefits platform administering plans end to end, from enrollment and premium collection to claims and reimbursement, with document-heavy claims processed by an AI pipeline rather than by hand.
- Role
- Platform development, AI pipeline, integrations, and ongoing delivery
- AWS
- OCR
- NLP and LLM extraction
- Plaid
- QuickBooks
- HubSpot
- Paycom payroll
- Flutter mobile app
The challenge
What the business was running into
- Every claim arrived as documents that had to be read by a person, and many were poorly scanned, photographed at an angle, or handwritten
- One claim might arrive as a clinic's printed invoice and the next as a note scrawled on a receipt, so there is no fixed format to parse and no field that sits in the same place twice
- Manual review did not scale, and volume growth translated directly into headcount rather than into margin
- Automating claim decisions without a human path for exceptions would trade a slow process for a confidently wrong one
The approach
Insurance claims are a document problem before they are a decision problem. A member submits whatever they have, which means a phone photograph of an invoice taken at an angle, a scan with half the page cut off, or a provider's handwritten note. Someone then reads each one, finds the fields that matter, types them into a system, and decides what the plan pays. It works, it is slow, and it scales only by hiring more people to read more paper.
We built the platform that administers these plans end to end, and then automated the part that consumed the most human time. Submissions are cleaned before anything is read from them, since in practice most extraction failures are caused by the photograph rather than the model. Optical character recognition, machine learning, and language models then turn the document into structured claim data, which is validated against the member's plan so that rules can determine eligibility and payment. Nine in ten now reach a decision without anyone opening the document.
The design decision that matters most is the one about the remaining tenth. A claims system that automates confidently and silently is worse than a manual one, because a wrong approval is invisible and a wrong denial reaches a member who was counting on the money. So confidence is measured per claim, ambiguous cases route to an agent with the original document and the extracted values shown together, and the automation's job includes recognizing its own limits.
Around the claims pipeline sits the rest of the business: member and group enrollment including payroll-deducted employee benefits, premium invoicing and automatic collection with non-payment handling, reimbursements by transfer or check with cashed status tracked, several distinct plan brands administered from the same platform, and a searchable provider directory members use before booking. Claims automation gets the attention, but a benefits platform is only as good as the administration underneath it.
Key capabilities
What the system does
Document intake and cleanup
Submitted images and PDFs are cleaned before anything is read from them, because most of the accuracy problem in claims automation is the photograph rather than the model.
Extraction and interpretation
Optical character recognition combined with machine learning and language models turns unstructured submissions into structured claim data, including the fields that move position from one provider's invoice to the next.
Eligibility and rules
Extracted data is validated against the member's plan, then rule-based actions determine eligibility and what the plan pays, so a claim arrives at a decision rather than at a queue.
Agents on the exceptions
Confident cases process automatically and anything ambiguous routes to an agent with the document and the extracted values side by side. The measure of the system is not how much it automates but how reliably it knows when not to.
Enrollment and membership
Member enrollment, plan changes, cancellations, and re-enrollment, including group enrollment through employers and payroll-deducted benefits.
Premium collection and billing
Invoicing, automatic payment collection, non-payment handling, and reconciliation against the accounting system, with the payment status of every member traceable.
Reimbursements
Member reimbursement by transfer or check, with cashed status tracked, because an uncashed reimbursement is an open liability rather than a closed claim.
Multiple plan brands
Several distinct plan brands administered from one platform, each with its own products, pricing, and member experience, rather than one codebase forked per brand.
Provider directory
Searchable provider network with location-aware results, so a member can find a participating practice before the visit rather than discovering the answer at checkout.
Outcome
Nine in ten submissions now reach a decision without anyone reading the document, claims resolve in near real time, and agents spend their day on the cases where judgment actually changes the answer.
Results
What changed for the business
Claims resolved in near real time
Processing that used to wait for a person to open a document now completes as the submission arrives, which members experience as a faster answer.
Volume without proportional headcount
Claim volume can grow without hiring reviewers at the same rate, which changes the economics of the whole operation.
Fewer transcription errors
Removing manual data entry removed the errors that came with it, and the errors that remain surface as exceptions rather than as quiet mistakes inside approved claims.
Agents moved up the value chain
Staff time shifted from typing values off scanned paper to handling the complex cases and the member relationships that actually need a person.
Related Services
Custom Software Development
Purpose-built systems that replace manual work and outgrown software. Designed, built, and supported by the same senior team.
AI/ML Solutions
AI grounded in your data and workflows: automation, prediction, and governed access to the models your team already uses.
Cloud Development
Cloud infrastructure that scales with the business and costs less to run than the servers it replaces.