Honey Health

The agents' judgment is where the models earn their keep. Classifying and extracting inbound faxes, checking a refill against prescription history and clinical criteria, assembling an authorization packet, coding a claim and writing an appeal all depend on learned models, and Honey's own customer terms define its agents as AI technology including large language models.

Part of the work would run on scripts alone: Connect Any Application moves data between two systems the way a person copying between screens would, and the screen level access to EHRs and payer portals is automation rather than intelligence. The models drive the core modules a buyer pays for, inside a platform that also does plain data movement, and a dedicated success team configures and retrains each customer's agents.

Routine work runs on its own and exceptions go to people. The refill agent checks each request against prescription history, timing, protocol requirements and documented clinical criteria, approves, denies or partially fills it automatically, and tees up complex cases for prescriber review. Connect Any Application flags missing data and high priority cases for a person instead of guessing, revenue cycle agents alert the right team member when information is missing, and fax triage routes documents to staff in the EHR.

All actions are documented in the EHR. What decides a complex refill, a high priority case or a missing item is left to each practice's criteria and not set out, and nothing says how a wrong action already written into the chart is found and reversed.

The agents are described by task and by how they work inside other systems: logged in like a staff member, moving through EHRs and payer portals, trained on each customer's workflows and retrained by a dedicated team as needs change. The customer terms define the underlying AI technology broadly, covering machine learning, deep learning and large language models.

Which models do the reading, deciding and writing, whether they come from an outside provider, and how a customer learns that an agent's model or training changed are not stated. Per customer training is a design choice with consequences for consistency, and nothing describes how it is versioned or tested before an update reaches a practice.

The customer terms recognize subcontractors and third party materials as part of the service. Honey's trust center lists four subprocessors, with Amazon Web Services as the cloud provider alongside GitHub, Google Workspace and Vanta. The model provider behind the agents is not identified.

What the terms do settle is how data moves once it arrives: processing stays in the United States, customer data may not be used to improve the services except in de identified, aggregated form, and data is returned or destroyed on request. Those terms bind Honey, and whether they flow down to subcontractors and model providers is not stated in the material readable before contracting.

One case study carries the results, from an unnamed independent specialty organization seeing 200 patients a day: 150 refills, 200 faxes and 50 prior authorizations handled daily, charts prepped for every visit, and time saved of about 12 hours a day on chart prep, 13.3 on faxes, 10 on prior authorizations and 2.25 on orders and refills.

The homepage summarizes 134 hours saved a week, an annual profit lift of $98,448, an estimated AI cost of $3.91 an hour and a 21 percent rise in patient satisfaction. None of it names the organization or gives a method, baseline or period, and nothing measures how accurately faxes were routed, refills decided or codes assigned.

The customer terms state the training position precisely, and then carve out a grant. Honey may not use customer data or confidential information to train, retrain, tune, validate or otherwise improve its services, except that it may use AI inputs and outputs that are free of personal information, de identified to the HIPAA standard, and aggregated and anonymized to improve the services. Customers can have data returned or destroyed within 30 business days of asking.

The homepage adds that each customer's agents are trained on its workflows alone and never shared. Retention while a contract runs is not stated, and nothing describes guardrails on what the agents write into a chart or send to a payer, or how an error found in production is handled.

The customer agreement, a terms and conditions document dated June 14, 2026 and linked from the site, has Honey acknowledge that it is a business associate under HIPAA and warrant compliance with HIPAA, state medical privacy laws and their guidance. A business associate agreement is attached to that agreement as a schedule, alongside a service level agreement, and governs Honey's use and disclosure of PHI.

The agreement also defines de identified data by the HIPAA standard at 45 CFR 164.514(b) and gives the customer the right to have its data returned or destroyed within 30 business days of a request. The business associate agreement's own text, including its tier and subcontractor terms, does not appear in the linked document.

Honey's trust center, linked from the site footer and hosted on Vanta, names SOC 2 Type II and SOC 3 reports as Honey's own and releases both on request. Neither report's date, audit period or scope shows on the open page. The same page lists the controls Honey monitors, penetration testing among them, with four subprocessors and a security contact.

These are agents that hold credentials to sign in to a practice's EHR and payer portals and act on its behalf, so the SOC 2 report is the independent check behind those controls. The customer agreement covers HIPAA compliance and data return and describes no audited control framework.

Most of Honey's work is administrative, and one agent makes clinical decisions with no regulatory position stated. The refill agent approves, denies or issues partial refills automatically against historical patterns, checklists and clinical protocols, completes them in the EHR around the clock, and sends only complex cases to the prescriber, so the refills it approves on its own reach the patient without a clinician seeing them.

The practice's protocols set the criteria, which places part of the decision with the customer, yet nothing on Honey's pages or in its terms addresses the agent's intended use, the medications or refill types it must not handle, or how it stands under device or pharmacy rules. Fax triage, prior authorization, referral and billing agents raise no such question.

The commitment sits in the contract rather than in published results. Honey warrants to customers that it monitors, measures and assesses its AI features for accuracy and reliability, considering false positive and false negative rates, how people and the AI work together, and whether performance holds beyond the training conditions, and that the AI features will conform to their specifications.

No results from that monitoring are released, nothing breaks performance out by specialty, document type, payer or patient group, and the per customer training means each practice's agents could behave differently with no comparison offered. The warranty gives a customer something to hold Honey to; it does not show how the agents perform.

Contract terms carry the commitments here. Honey warrants that its AI features will conform in all material respects to their specifications, indemnifies the customer against third party claims arising from its material breach of a warranty or its gross negligence, and covers AI output against infringement claims. Liability is capped at the greater of twice the fees paid in the prior 12 months or $3 million, with indemnity outside the cap, and a service level agreement sets coverage rates and remedies.

None of that answers for an individual output being wrong, such as a misrouted fax or an incorrectly approved refill. Every action is documented in the EHR, and no error rate is given for any agent.

The agents work inside the EHR itself, reading charts, creating and updating patient records, placing orders and refills and documenting every action there, and Honey says it integrates with more than 73 EHRs and healthcare applications and is live in about 30 days without an API project. Connect Any Application adds Honey as a user in any two systems and moves data between them.

No EHR is named on the pages, no marketplace listing or partner certification is offered, and no customer is tied to a particular record system, so the reach of the screen level integration cannot be checked. Working through the user interface also means each EHR upgrade can change what the agents see.

The customer agreement licenses Honey to process customer data in the United States, solely as needed to provide the services, which commits the location rather than implying it. The service is hosted by Honey, with agents signing in to the customer's EHR and other systems using credentials and access keys the customer provides.

Each customer gets its own AI team, trained on its workflows alone and never shared with other organizations, which separates the agents themselves. Its trust center names Amazon Web Services as the cloud provider. Whether customer data sits in isolated tenancy, which region holds it, and how agent credentials are stored and rotated are not stated.

Per task prices are set out in Honey's ROI and pricing calculator: $0.20 for a fax routed and its data extracted, $0.25 for a data source fetched and charted or a refill processed, $0.50 for a full benefits check, a payment posted and reconciled or a claim status retrieved, and $2.50 for an end to end prior authorization, a referral processed and scheduled or a denial appealed. Volume discounts start at 5 percent above 5,000 tasks a month and reach 25 percent above 50,000.

The calculator compares the result with staff time at $23 an hour. Getting started still runs through a demo request and a dedicated onboarding team, and implementation, minimums and contract length are set in an order form rather than shown.

Six buyer types are named: health platforms that embed the agents, hospitals and health systems, value based care organizations, RCM and IT managed service firms, MSOs and independent medical groups. Specialties listed include cardiology, orthopedics, endocrinology, primary care, pain management, ophthalmology, gastroenterology, dermatology, oncology, pulmonology and urology, and the agents span clinical operations, revenue cycle, data entry, patient access, credentialing and enrollment, and research operations.

Validation reaches a small part of that range: one anonymous specialty organization's results. Credentialing and research operations appear as categories with little detail behind them, and nothing ties a named customer to any specialty or buyer type.