Rad AI pricing

About

Rad AI is a San Francisco–based generative-AI company for radiology, founded in 2018 by CEO Doktor Gurson and Dr. Jeff Chang (a radiologist who was among the youngest in the US to become board-certified). Its software sits inside the radiologist’s existing PACS, RIS, and EHR workflow and ships as three modular products: Rad AI Reporting (full GenAI report drafting in each radiologist’s own voice — up to 2x faster dictation, up to 90% fewer words), Rad AI Impressions (auto-generates the impression section from dictated findings in 0.5–3 seconds, saving 60+ minutes per shift), and Rad AI Continuity (detects, tracks, and closes the loop on incidental-finding follow-ups across 50+ categories). The reporting platform launched commercially as Omni Reporting at RSNA 2023.

Rad AI raised a $50M Series B in May 2024 led by Khosla Ventures (with Gradient Ventures, ARTIS, OCV, Kickstart, WiL and others), then a $60M Series C in January 2025 led by Transformation Capital at a roughly $525M valuation — about $143M total raised. The company reports that its tools are used by more than a third of US health systems and 9 of the 10 largest US radiology practices, including Mayo Clinic, Cleveland Clinic, Yale New Haven, and Cincinnati Children’s, with follow-up models trained on over half a billion radiology reports.

For the most current information, visit Rad AI. Note: there is no public pricing page — the /pricing URL returns a 404, and every CTA routes to a demo request.

Pricing summary : How Rad AI’s pricing model works

Rad AI is fully sales-led: there is no published price list, no self-serve signup, and the public /pricing URL 404s. Every button on the site says “Request Demo.” Pricing is a quoted annual enterprise contract scoped to each radiology practice or health system, sold modularly across the three products — Reporting, Impressions, and Continuity — so total contract value depends on which products you buy, how many radiologists use them, and your report volume.

The distinctive twist is Continuity’s value framing. Rather than lead with a seat or per-report fee, Rad AI’s Continuity page publishes an interactive ROI calculator: you set annual report volume, the share of reports with follow-up recommendations (default ~15%), and net reimbursement per imaging study ($50–$250), and it projects the additional revenue from lifting follow-up rates (e.g. from a 30% baseline to ~70%). A sample configuration surfaces a “$8,400,000 potential additional revenue opportunity” — the pitch is that Continuity pays for itself in recovered downstream imaging, so the buying conversation is about ROI, not list price.

What makes this different: unlike the token- and request-metered AI tools elsewhere in this corpus, Rad AI sells into clinical-workflow and revenue-cycle budgets. Reporting and Impressions monetize radiologist time saved (60+ minutes per shift, up to 90% fewer words dictated); Continuity monetizes a clinical-and-financial outcome (more resolved follow-ups → earlier cancer detection → more reimbursable imaging). All of it is wrapped in a custom enterprise contract with no posted price.

Pricing by product

Sales motions across products: sales-led only — demo request → scoping → custom quote → annual contract. No free tier, no monthly option, no self-serve. Continuity is frequently positioned as ROI-positive (Rad AI notes that running Continuity alongside Impressions can lift clinically appropriate follow-ups by up to 40%). All prices are quoted; figures shown are from Rad AI’s own product pages, not posted contract prices.

Hidden costs : What Rad AI users actually pay

Because pricing is quoted and modular, the real cost is shaped by which products you attach and the scale of your deployment (radiologist count, report volume, number of sites), not a published rate card. The biggest cost-shaping factors: each product (Reporting, Impressions, Continuity) is a separate line, so bundling all three multiplies contract value; deployment touches PACS, RIS, and EHR integration; and Continuity in particular requires EHR/HL7 connectivity and patient-outreach plumbing (SMS, direct mail, EHR messaging, fax) that has to be configured per health system.

Outside the quote itself, the things to budget for are annual commitment (this is enterprise software, not month-to-month), integration and change-management effort (Rad AI emphasizes a lightweight, zero-footprint client, but EHR-connected follow-up workflows are non-trivial), and the opacity of comparison — with no posted price, apples-to-apples evaluation against competitors requires running a sales process. The flip side is Continuity’s explicit ROI math: if its $50–$250-per-study revenue model holds for your population, the product is pitched to be net-positive rather than a sunk cost.

Want to estimate your own Rad AI bill? Use the Rad AI pricing calculator to model your costs based on products and deployment scale.

Pricing evolution : Rad AI pricing history and changes

Cadence

Tracked range: 2018–present. Rad AI has never published a public price list, so there are no Wayback price snapshots to chart — the evolution here is product and go-to-market (funding, product launches), not posted rate cards.

Notable changes

• 2023-08 — Omni Reporting launches commercially around RSNA 2023 (“Speak Less, Say More”), adding full GenAI report drafting and Omni Unchanged to the existing Impressions product. No public pricing.
• 2024-05 — $50M Series B led by Khosla Ventures (total funding crosses $80M). Pricing stays sales-led.
• 2025-01 — $60M Series C led by Transformation Capital at a $525M valuation ($143M total raised); Rad AI cites use by a third of US health systems and 9 of the 10 largest US radiology practices.
• 2026-06 — Live site has no pricing page (/pricing 404s); all CTAs are “Request Demo.” Three modular products are quoted per health system, and Continuity ships an interactive ROI/revenue calculator ($50–$250 net reimbursement per study) as the value frame.

What’s unique : Rad AI’s distinctive pricing mechanics

1. ROI-as-pricing for Continuity. Instead of leading with a fee, Rad AI hands buyers a revenue calculator: set your report volume and net reimbursement per study ($50–$250), and it projects the additional imaging revenue from lifting follow-up rates. The product is sold as a profit center (“$8,400,000 potential additional revenue opportunity” in the sample), reframing the purchase from cost to ROI — rare in a corpus dominated by per-unit metered tools.

2. Modular clinical SKUs, one quote. Reporting, Impressions, and Continuity each price separately and target different budgets — radiologist productivity (time saved per shift) versus health-system revenue-cycle (follow-up reimbursement). The same buyer can attach one or all three, so two health systems of similar size can pay very differently depending on product mix.

3. Fully gated, enterprise-only. Nothing is published; every path is “Request Demo.” There is no self-serve tier, no monthly option, and no posted price — a classic regulated-healthcare enterprise posture (HIPAA, EHR integration, BAAs) and the opposite of the self-serve PLG tools elsewhere in this corpus.

Strengths & weaknesses

Billing UX : Rad AI billing controls and transparency

• Billing controls — Enterprise contract-based: annual commitment, no self-serve plan changes, no monthly billing. Adding products (e.g. attaching Continuity to an existing Impressions deployment) or scaling seats goes through the account team and a contract amendment, not an in-app toggle.
• Usage visibility — Continuity provides operational dashboards (real-time follow-up status, audit trail, population-level tracking), and Rad AI’s products report time-saved and quality metrics — but there is no public cost calculator or posted rate card for the software itself. The one public “calculator” is the Continuity ROI tool, which models downstream-imaging revenue, not your bill.
• Payment options — Invoiced annual enterprise contracts via direct sales, typically alongside a HIPAA/security review and BAA. Deployment is a lightweight, zero-footprint cloud client integrated into existing PACS/RIS/EHR systems; Continuity adds EHR/HL7 connectivity for automated patient and provider outreach.

Strategic wins : Why Rad AI’s pricing decisions worked

1. Selling outcomes, not tokens

By framing Continuity around downstream-imaging revenue ($50–$250 per follow-up study, follow-up rates lifted from ~30% to ~70%), Rad AI sidesteps the “what does this cost?” objection and makes the product a profit center for the health system. That ROI-first posture is far more durable in a budget-constrained clinical setting than a per-seat fee. See outcome-based pricing trends.

2. Modular packaging for land-and-expand

Starting with Impressions (radiologist productivity) and expanding into Reporting and Continuity (revenue cycle) creates a natural expansion path within the same account — growing contract value without a fresh procurement cycle each time. See how AI companies structure pricing.

3. Enterprise commitment for predictable revenue

A sales-led, annual-contract motion concentrated on large health systems and the biggest radiology practices trades a broad self-serve funnel for revenue predictability and deep integration moats (PACS/RIS/EHR), where switching costs are high. See choosing the right usage metric.

Areas to improve : Gaps in Rad AI’s pricing approach

1. Zero list-price transparency

A 404 on /pricing and no published rate card force every buyer into a demo just to learn rough cost. Even a posted “starting at” or a public methodology would reduce friction for smaller practices and shorten evaluation cycles. See bill shock and cost unpredictability.

2. ROI math depends on the buyer’s numbers

Continuity’s revenue case hinges on each system’s reimbursement rates, follow-up baselines, and imaging capacity — variables that differ widely. Without transparent assumptions and conservative defaults, the headline “$8.4M opportunity” risks reading as marketing rather than a defensible forecast.

3. High floor blocks smaller practices

An enterprise-only, integration-heavy motion shuts out small radiology groups that could benefit from Impressions. A lighter, capped self-serve or pilot SKU would widen the funnel without undermining the health-system motion.

Key takeaways

1. Rad AI publishes nothing — pricing is fully sales-led. The /pricing URL 404s and every CTA is “Request Demo”; expect a quoted annual enterprise contract scoped per practice or health system.
2. Three modular products. Reporting (report drafting), Impressions (auto-impressions), and Continuity (follow-up management) price separately, so contract value scales with product mix and deployment size.
3. Continuity is sold on ROI, not a fee. A published revenue calculator ($50–$250 net reimbursement per study, follow-up rates lifted ~30%→70%) frames the product as a downstream-imaging profit center.
4. Enterprise posture, no free tier. Annual commitment, HIPAA/EHR integration, and BAAs signal regulated-healthcare enterprise software, not a self-serve tool.
5. Strong adoption underwrites the model. Used by a third of US health systems and 9 of the 10 largest radiology practices, with ~$143M raised at a ~$525M valuation.

UBP implications

1. Outcome framing beats unit framing in clinical budgets. Rad AI’s Continuity calculator shows that tying price to a measurable financial outcome (reimbursable follow-up imaging) can convert a cost conversation into an ROI conversation — a powerful move where buyers are budget-constrained. See usage-based pricing strategy.
2. Full opacity is a deliberate enterprise choice, trading shorter sales cycles for negotiating leverage and deep integration moats; it works at high ACV in regulated healthcare but blocks the bottom-up adoption that powers PLG competitors.
3. Modular value metrics let one vendor span budgets — radiologist time saved (productivity) and imaging reimbursement (revenue cycle) — so the same account can be monetized from two different P&L lines. See choosing the right usage metric.

Sources

• Rad AI official website (live capture, accessed 2026-06-10)
• Rad AI Reporting product page (live capture, accessed 2026-06-10)
• Rad AI Impressions product page (live capture, accessed 2026-06-10)
• Rad AI Continuity product page (with ROI calculator) (live capture, accessed 2026-06-10)
• Rad AI /pricing URL — returns 404 (live check, accessed 2026-06-10)
• Rad AI demo-request page (live capture, accessed 2026-06-10)
• TechCrunch — Rad AI raises $50M Series B from Khosla Ventures (accessed 2026-06-10)
• Rad AI — closes $60M Series C (accessed 2026-06-10)
• MobiHealthNews — Rad AI scores $60M, ~$525M valuation (accessed 2026-06-10)
• Rad AI — Omni Reporting launch (RSNA 2023) (accessed 2026-06-10)

Bottom line

Rad AI is a San Francisco–based radiology-GenAI company (~$143M raised, ~$525M valuation, used by a third of US health systems) selling three modular products — Reporting, Impressions, and Continuity — into clinical and revenue-cycle budgets. Its pricing is fully sales-led with no public list (the /pricing URL 404s; every CTA is “Request Demo”): quoted annual enterprise contracts scoped per practice or health system. The distinctive mechanic is Continuity’s ROI framing — an interactive revenue calculator ($50–$250 net reimbursement per follow-up study) that pitches the product as a downstream-imaging profit center rather than a line-item cost. Browse the pricing blueprint for more fully-researched company profiles.

Want to compare Rad AI against other healthcare and enterprise AI companies? Browse the pricing blueprint.

Pricing timeline : Major events on a vertical axis

Each milestone below corresponds to a public pricing change, product launch, or material adjustment. Major events use a filled marker; minor adjustments use a faded one.

Sales-only enterprise model, modular products, Continuity ROI calculator

Jun 2026

Live capture: radai.com has no pricing page (/pricing 404s); every CTA is 'Request Demo'. Three modular products — Reporting, Impressions, Continuity — are quoted per health system. Continuity ships an interactive revenue calculator ($50-$250 net reimbursement per study) framing value as downstream-imaging ROI rather than a posted fee.

$60M Series C at ~$525M valuation

Jan 2025

Rad AI closed a $60M Series C led by Transformation Capital at a roughly $525M valuation (~$143M total raised), citing use by more than a third of US health systems and 9 of the 10 largest US radiology practices. Pricing model unchanged: quoted enterprise contracts, no public rate card.

$50M Series B (Khosla Ventures)

May 2024

Rad AI closed a $50M Series B led by Khosla Ventures (with Gradient Ventures, ARTIS, OCV, Kickstart, WiL and others), bringing total funding to over $80M. Pricing remained sales-led with no published list.

Rad AI Omni Reporting launches at RSNA

Aug 2023

Rad AI introduced Omni Reporting, its generative-AI radiology reporting platform ('Speak Less, Say More'), made commercially available across the US around RSNA 2023, alongside Omni Impressions and Omni Unchanged. No public pricing accompanied the launch — enterprise sales only.