Comparison2026 · LeoRad
Alternative to LeoRad — Laudos.AI with real data (2026)
Evaluating an alternative to LeoRad? Here's the direct comparison with real data — sub-1min median on more than half of reports, documented institutional governance and 14-day assisted migration.
TL;DR
LeoRad was built as a dictation + structuring solution for clinics. Laudos.AI is built as speech-to-REPORT — the radiologist speaks naturally and AI delivers the structured report without dictated punctuation. For teams with high volume, critical findings and signature time pressure, Laudos.AI shows sub-1min median TAT on more than half of reports. For teams satisfied with classic dictation already calibrated on LeoRad, switching may not be a priority.
Who should stay on LeoRad
Teams that: (a) already have LeoRad deployed for years with calibrated templates and fluid workflow; (b) operate low volume (<30 reports/day/radiologist) where TAT gains don't justify migration; (c) work with niche modalities where LeoRad already has heavy hospital-customized templates; (d) don't want generative AI for structured impressions and prefer classic dictation with macros. Honest take: switching reporting tools is costly in adaptation time, and LeoRad gets the basics done in many established setups.
Who should evaluate Laudos.AI
Teams that: (a) currently dictate punctuation and formatting manually and want to stop; (b) operate high volume (>40 reports/day/radiologist, on-call, teleradiology) where sub-1min median TAT means hours of productivity per shift; (c) need contract-level traceable critical-findings (CRIT) workflow with acknowledgement logs and scoped SLA; (d) want LGPD governance with DPO, audit trail, and documented access segregation; (e) operate multi-site or multi-client (teleradiology, hospital networks) needing per-client template standardization; (f) want radiology AI that understands BR context — terminology, ACR/CBR classifications, BI-RADS/TI-RADS/PI-RADS/Lung-RADS native to the workflow, not as an add-on.
Auditable comparison
Laudos.AI vs LeoRad — criterion by criterion
| Criterion | Laudos.AI | LeoRad |
|---|---|---|
| Usage model | Speech-to-report: natural speech → structured report | Dictation + fixed-template structuringsource: leorad.com.br |
| Manual punctuation | No. AI writes punctuation, paragraphs, transitions | Partial in workflowsource: leorad.com.br |
| Median TAT (telemetry) | 52s (median over 97 finalized reports, 2026-05) | Not publicly published |
| Modality coverage | CT, MRI, US, X-ray, Mammography, Doppler, PET-CT | CT, MRI, US, X-ray, Mammography, Dopplersource: leorad.com.br/produto |
| Structured classifications | BI-RADS, TI-RADS, PI-RADS, Lung-RADS, LI-RADS, RECIST, Fleischner, Bosniak native | Per template; depends on setup |
| CRIT — critical findings | Native flow with acknowledgement, escalation, contract SLA | Not documented as native workflow |
| LGPD governance | Designated DPO, audit trail, access segregation, legal-review docs | Public privacy policy; operational details on request |
| PACS/RIS integration | Dedicated engineer per scope; HL7 v2 ORM/ORU, FHIR, DICOM-SR, REST API + webhooks | Integration support; scope varies by clientsource: leorad.com.br/produto |
| Mobile editor | Web + iOS + Android with feature parity | Web; partial mobile |
| Multi-site / multi-client | Templates per unit, contract, role; institutional dashboard | Yes, per config |
| Public price | Published plan from BRL 199/mo (individual radiologist) | On requestsource: /en/pricing |
| Assisted migration | Template import + 14-day pilot at no charge | Not publicly documented |
| Trial | 14-day with card · Cancel in 1 click · 30-day refund | Not documented |
Real telemetry
Production data, not promise
Numbers below are real Laudos.AI production telemetry as of 2026-05. We report median, not mean, to avoid outlier bias. Data reflects full reports (editor open through signature), not transcription time alone.
Laudos.AI Labs·Production telemetry2026-05-09
Rolling 30-day window · median TAT 52s · 430.2h returned vs manual transcription
Measurement methodology, telemetry pipeline and reporting cadence operated by Laudos.AI Labs.
- Finalized reports
- 3,900
- Median TAT
- 52s
- Mean TAT
- 3.4 min
- Under 1 min
- 54.6%
TAT distribution
- Sub-min (54.6%)
- 1–5 min (24.7%)
- 5+ min (20.6%)
<30s
30–60s
1–2 min
2–5 min
5–15 min
>15 min
Laudos.AI vs traditional transcription (3,900 reports)
Laudos.AI
Manual transcription (estimated)
- Laudos.AI time
- 217.1 h
- Manual estimate
- 651.3 h
- Hours saved
- 430.2 h
- Median speedup
- 3.0×
Source · Laudos.AI Labs
- Window: 2026-04-09 → 2026-05-09 (30 days)
- Refresh: monthly · next snapshot at month rollover
- Cohort: finalized reports (status = signed) by radiologists on the Pro plan during the rolling window, excluding internal QA and Laudos.AI staff accounts
- Pipeline: copilot.laudos.ai · production telemetry pipeline
- Exported on: 2026-05-09
TAT = time between editor open and signature, computed per finalized report (status=signed). Manual baseline estimated at 10 min/exam for transcription + structuring, compared against actual editor time. Speedup is the ratio of manual baseline to observed median TAT, conservative.
Audit-grade verification on request: oi@laudos.ai
LeoRad → Laudos.AI migration — 14-day checklist
- 01
D1–D3: technical kickoff. Map modalities, daily volume, critical report templates, current PACS/RIS integrations and signing roles.
- 02
D4–D7: assisted template import. Laudos.AI engineering maps current LeoRad templates to native structure, preserving service-specific language.
- 03
D8–D10: pilot with 1 volunteer radiologist on real routine (not demo), parallel to LeoRad. Measures TAT, rework, review friction.
- 04
D11–D13: fine tuning. Service-specific vocabulary, shortcuts, CRIT workflow, signature integration, PACS/RIS export.
- 05
D14: go/no-go decision based on TAT, clinical satisfaction, governance and TCO. No billing until go.
FAQ
Does Laudos.AI replace LeoRad?
Functionally yes — covers dictation, structuring, templates, integration, signature. Operationally it depends: some services have deeply customized LeoRad flows and migration needs a plan. The 14-day pilot measures the transition in real production before any billing.
How long does it take to migrate from LeoRad to Laudos.AI?
Median technical pilot closes in 14 days: 3 days mapping, 4 days assisted template import, 3 days routine pilot, 3 days fine-tuning. No billing during the pilot. Go/no-go decision is data-based, not pre-committed.
Are LeoRad templates preserved?
Yes. Deployment team performs assisted import — current LeoRad templates are mapped to native Laudos.AI structure preserving service language, shortcuts and standards. Radiologists don't relearn vocabulary.
Does Laudos.AI integrate with existing PACS/RIS?
Yes. We work with the service's infrastructure — no PACS, RIS or viewer replacement required. We support HL7 v2 (ORM/ORU), FHIR, DICOM-SR and REST API + webhooks. Every integration is scoped by dedicated engineer, not self-service.
What about LGPD? Who is responsible for the data?
Laudos.AI has designated DPO, audit trail, role-based access segregation and documentation for legal and technical review. We operate as data processor under controller (institution) direction. DPA and mapping docs are provided in deployment scope.
How does the trial work?
14 days with card (cancel in 1 click). Pro monthly R$ 219 or annual R$ 2,190 (2 months free). Full refund within 30 days if charged. Stripe billing.
Why is Laudos.AI faster than LeoRad on short reports?
Because the radiologist doesn't dictate punctuation, header or transitions. On normal reports (chest X-ray, simple OB ultrasound, normal head CT), AI generates the structured text from short speech. Telemetry shows 54.6% of reports under 1 minute.
How does CRIT work in Laudos.AI?
Critical findings have native flow: radiologist marks, platform logs, triggers communication to requester, captures acknowledgement, keeps auditable trail. SLA, escalation and responsibilities are contract-defined, not brittle config.