Assistive reporting AI that integrates with your hospital, without replacing what already works

The post-imaging layer comes in after what already runs, without replacing PACS, RIS or worklist.

The connection uses the standards the service already speaks: HL7 v2 (ORM/ORU) for order and result, FHIR R4 for structured resources, DICOM-SR for the structured report and MWL via C-FIND for the worklist. No replacing what works; the platform plugs into the existing bus instead of requiring a new imaging ecosystem.

The Scheduled Procedure Step coming from the MWL is reused, so the exam reaches the editor already with the correct patient, modality and procedure, without retyping. The signed report goes back as ORU and DICOM-SR to the PACS and the RIS, in the format each system expects. The connection is made by a dedicated engineer, not by a generic installer.

The start is small and auditable: one modality or one unit, validation in a test environment with synthetic or anonymized data, and a 30-day pilot. Every message exchange is logged, with an audit trail per exam, so that operations and InfoSec see exactly what came in, what went out and when.

A hospital that grew through units, contracts and mergers rarely has a single PACS.

The reporting layer communicates through standards (HL7, DICOM-SR, MWL), so it is not tied to a single imaging vendor. Each unit keeps its PACS and its RIS, and the structured report flows the same way, with the same structure of Technique, Analysis, Impression and, where applicable, Classification, regardless of which system generated the exam.

During a PACS migration or VNA consolidation, the report is not held hostage by the imaging timeline. Because the layer depends on standardized interfaces and not on a vendor's proprietary format, replacing the image repository or the viewer does not require rewriting the reporting workflow. This reduces risk and dependency in the middle of the migration.

The result is governance over the report text, whatever the source PACS. Visibility is consolidated per unit, even with different installed bases, and coordination sees output and pending items without relying on separate reports from each vendor. The physician remains the author; the layer only organizes what surrounds the report.

On call, time is clinical, and that is where TAT weighs the most.

The REPORT module turns voice into a structured report directly in the editor, and the median from editor to signature is 52 seconds, with 54.6% of reports going out in under one minute (production, 5,200 reports in 30 days). Less typing on shift means less friction precisely when volume and pressure rise.

For time-dependent findings, CRIT is in a controlled pilot. Detection depends on findings provided by the physician; confirmation, channels, recipients, timeframes, contingency and closure are defined and tested for each deployment.

The system can make the institutional SLA and the criticality reported by the physician visible in the queue. It does not interpret images, define clinical urgency or decide management.

For InfoSec and the DPO, what matters is what can be verified.

Controls include role-based access, logical segregation, auditing and encryption in transit. Regions, subprocessors, persistence, logs, retention and backups are documented by feature and deployment.

The evaluation starts in a test environment with synthetic or anonymized data, so security validates the flow without exposing production or real patient data. The per-exam audit trail records who accessed it, what was done and when, at the exam level, which supports investigation and incident response without relying on anyone's memory.

Access goes through the mechanism IT already maintains, with no separate password.

With SSO via SAML, login uses the corporate identity provider, so provisioning and deprovisioning follow the same governance as the rest of the installed base. Fewer loose credentials mean less risk surface for InfoSec to manage, and offboarding an on-call physician does not leave orphaned access in yet another system.

Profiles separate what each role sees and does. The radiologist works on their own reports; the manager sees output and indicators without entering into clinical judgment. Permissions are auditable, and visibility is segmented by unit, so each coordination team sees its own operation without seeing what is not its concern.

This is governance, not surveillance. The dashboard gives visibility into the process (queue, TAT, critical-finding cycle), not a snapshot of individual productivity to apply pressure. The goal is workflow management and access compliance, with the physician always as the author of the report they sign.

Meaningful human supervision is built into the product's design.

CFM Resolution 2.454/2026 requires meaningful human supervision in the use of AI in reports. Laudos.AI is assistive by design: it structures the report and suggests text based on voice and modality, but the physician reviews, edits and signs each report. The AI does not issue diagnoses or replace the radiologist; authorship and clinical responsibility belong to the physician.

No clinical decision is automated. What the platform organizes is everything around the report: the structure of Technique, Analysis, Impression and Classification, critical-finding communication and standardized classifications via the GUIDE module (BI-RADS, LI-RADS, PI-RADS, TI-RADS and Lung-RADS). The radiologist applies the criteria; the tool only reduces the friction of writing and standardizing.

The dashboard delivers governance of the process, not of clinical judgment. It shows flow, timeframes and the communication cycle, but it does not assess whether the report is correct, because that is up to whoever signs. Compliance with the CFM, here, means keeping the human at the center of the decision, from the first draft to the signature.

The recommendation is to evaluate in the real operation, not in a controlled demo.

The 30-day pilot runs on a slice of the operation (one unit or one modality), with integration done by a dedicated engineer and prior validation in a test environment with synthetic or anonymized data. The ROI uses your real exam volume, not an illustrative brochure number, so the calculation is made against the service's own history.

It is worth measuring what changes in practice: time from editor to signature, TAT by modality, percentage of reports completed in under one minute and hours returned by volume. On call, measure the critical-finding cycle from alert to confirmation of receipt. These are numbers the operation itself can check, without relying on our word.

The engagement has no contractual lock-in, because the layer uses open standards (HL7, FHIR, DICOM-SR) and does not require replacing PACS, RIS or VNA. Leaving, if it comes to that, does not dismantle the imaging installed base. Deployment is assisted, with a small scope first and expansion only after the pilot numbers hold up.