Rad AI
AI reporting and follow-up built by radiologists, for radiologists.
By Rad AI, Inc. · 4.0/5 Value-Position score (estimate)
Positioning guardrails
Best for
- Hospital radiology departments and health systems with rising imaging volumes and radiologist burnout
- Radiology practices and teleradiology groups wanting AI-assisted reporting and auto-generated impressions
- Imaging teams that must track, communicate and close incidental-finding follow-up at scale
- Organizations that prefer radiology-specific AI over general-purpose clinical AI
Ideal size: Enterprise health systems and large radiology groups people · Health system or large practice with an imaging-informatics / IT function
Not for
- Non-clinical businesses with no diagnostic imaging or reporting workflow
- Buyers who require published, self-serve list pricing and click-to-buy signup
- Teams that want to bring their own model or run inference on-premises
- Care settings without an existing reporting system, voice recognition or templates to integrate with
Value metrics scorecard
Time-to-Value
~1–2 months (vendor does not publish)
~45 days to first production value
Total Cost of Ownership
On request
Enterprise agreement quoted after a demo; no public list pricing
Implementation Friction
3/5
Engineering + admin effort required
Value-Position score
out of 5 · model estimate
Full cost breakdown
Mandatory implementation fee
None
Seat tiers
Not published by vendor
Add-on costs
- None
Company & support
Who is behind Rad AI, and how your team gets help once it is live.
Company
- Founded
- 2018 · 8 yrs in business
- Headquarters
- Not recorded
How you get support
We haven’t recorded support channels for Rad AI yet. Nothing here means unverified — not absent.
Market position
Where Rad AI sits against its closest alternatives. Pick any two of cost, speed, friction and buyer score, and up to 9 companies to compare.
Quadrant view
Typical annual cost × Time-to-value
The lines cross at the median of the solutions shown, so about half sit on each side of each line. A dashed ring marks an outlier pinned to the edge; hover for its value.
Companies on the chart 6 / 10
- Rad AI
- Elation Health
- Matrix42
- Suki
- Tennr
- Kipu Health
Add or change companies
Up to 10 companies including Rad AI. Listed closest first.
Stack fit signal
Compatibility with standard B2B ecosystems.
No supported MCP path today, so it cannot be driven from an AI client.
AI & MCP readiness
What Rad AI ships in AI, and what it asks of your ecosystem.
AI features shipped
Vendor describes an AI-first, cloud-native reporting product, a generative AI impressions solution trained on each radiologist's voice and phrasing, real-time quality checks, continuous speech recognition, and AI-powered follow-up management over 50+ categories of incidental findings. Models are the vendor's own, purpose-built for radiology.
Your data & models
- Trains on your data
- Not recorded — ask the vendor
- Runs on
- Not recorded
- AI pricing
- Not recorded
In your ecosystem
- AI connection
- Not supported
- Model key
- Vendor's key
- AI usage audit
- Not recorded
Compliance attestations
* IAPP AIGP certifies individuals, not products. It means named staff hold the credential — not that the platform does.
Bottom line
Rad AI builds generative AI software for radiology: AI-first reporting, automated impressions, and follow-up management for incidental findings. Co-founded in 2018 by practicing radiologist Jeff Chang, MD, it says it is used by 11,000+ radiologists at 200+ health organizations and over 40% of U.S. health systems, and claims reports generated up to 50% faster inside the tools radiologists already use. It is SOC 2 Type II and HIPAA+ compliant. Pricing is not published; engagements begin with a demo, and implementations are supported by the vendor.
Frequently asked questions
What problem does Rad AI solve for a hospital or radiology practice?
Rad AI targets rising imaging volumes and radiologist burnout. Its Reporting product provides continuous real-time speech and quality checks before sign-off, Impressions generates personalized report impressions, and Continuity tracks and closes follow-up on actionable incidental findings. The vendor claims reports can be generated up to 50% faster and says it is used by 200+ health organizations.
Does Rad AI replace our existing reporting system or voice recognition?
The vendor states Rad AI Impressions works with your existing voice recognition, templates and reporting system, and inserts clinical guidelines without overwriting the report. Rad AI Reporting is its own AI-first, cloud-native reporting product, so the replacement decision depends on which modules you adopt. Confirm PACS, worklist and dictation integration scope during the technical demo.
How is Rad AI priced and what commitment is required?
Rad AI does not publish list pricing, seat tiers or implementation fees. The website routes buyers through a demo request and the about page references implementation through ongoing support, which indicates a quoted enterprise agreement. Treat pricing, term length and any implementation fee as commercial negotiation items and request a written scope before signature.
Is Rad AI secure and compliant enough for patient data?
Its security page states SOC 2 Type II and HIPAA+ certification for security, confidentiality and availability, an industry-leading de-identification pipeline specialized to radiology reports, continuing 12-month third-party audit cycles, real-time compliance auditing, and 130+ monitoring tests per day. Human-in-the-loop QA is cited from 2019. Ask for the current report and a BAA during diligence.
Does Rad AI train its models on our patient data?
The about page says Rad AI leverages its own generative AI models trained specifically for radiology and healthcare plus a large proprietary radiology report dataset, and Impressions is described as trained on each radiologist's voice and phrasing. Public pages do not state explicit opt-in or opt-out terms for customer data used in training, so that question must be settled in the contract and DPA.
What evidence exists that Rad AI works in production?
The site cites 200+ health organizations, 11,000+ radiologist users across products, work with over 40% of U.S. health systems and 9 of the 10 largest U.S. radiology practices, plus named customer testimonials from radiology chairs, CEOs and COOs. Independent references are available on request; the vendor also cites KLAS consideration and RSNA Ventures partnership.