Hippocratic AI pricing

About

Hippocratic AI is a safety-focused healthcare LLM company, founded in January 2023 by CEO Munjal Shah with a team drawn from El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, and NVIDIA. Its product is a fleet of patient-facing AI agents that handle low-risk, non-diagnostic clinical tasks — appointment scheduling, patient intake, screening outreach, vaccination campaigns, post-discharge readmission-prevention calls, chronic-care check-ins — over real-time voice. The agents run on Polaris, a “constellation” of 25+ task-specific 70B+ LLMs built (per the company) on 180m+ patient interactions, with a heavy emphasis on safety and not crossing into diagnosis.

Hippocratic raised a $53M Series A in March 2024 ($500M valuation, co-led by Premji Invest and General Catalyst, with a16z Bio+Health, SV Angel, and health systems Memorial Hermann, UHS, Cincinnati Children’s and WellSpan), a $141M Series B in January 2025 ($1.64B — unicorn status, led by Kleiner Perkins), and a $126M Series C in November 2025 ($3.5B valuation, led by Avenir Growth), for roughly $402M total raised and 50+ health-system partners. In March 2024 it partnered with NVIDIA on real-time “empathy inference” (low-latency, emotionally responsive voice on H100/H200 GPUs).

For the most current information, visit Hippocratic AI. Note: there is no public pricing page — the /pricing URL returns a 404.

Pricing summary : How Hippocratic AI’s pricing model works

Hippocratic prices its agents like labor, not software. The reported operational rate is about $9 per agent-hour — health systems “pay only for active agent time spent on patient interactions” — explicitly benchmarked against the ~$39/hour median wage of a registered nurse. There are no seats and no tokens: the meter is the hour of active patient interaction, and the company frames the whole offering as on-demand “AI staffing” — you “hire” an agent the way you’d staff a shift, and the bill scales with hours used.

On top of the buyer-facing meter sits a two-sided AI Agent App Store (launched January 9, 2025): licensed clinicians design and certify specialty agents (in under 30 minutes, safety-tested) and earn 5% of the base rate (typically ~$10/hour) plus 70% of any premium rate they set, capped at $5,000 per agent. That turns nurses and doctors into the supply side of a marketplace whose demand side pays per hour.

What makes this different: almost every other AI company in this corpus meters tokens, requests, seats, or completed tasks. Hippocratic meters the agent-hour of human-equivalent work and prices it directly against a wage. That makes the value proposition legible to a hospital CFO (“$9 vs $39 an hour”) in a way tokens never could — but it also imports the volatility of labor: usage-based hourly billing means cost spikes in high-demand periods, and the buyer doesn’t fully control how long each interaction runs. (In this corpus’s taxonomy the agent-hour maps to the canonical voice-call meter media-minutes — time-based agent–patient interaction normalized regardless of per-minute or per-hour quoting — alongside interactions for the per-conversation view.)

Pricing by product

Sales motions across products: sales-led only — demo → scoping → contract. There is no public self-serve checkout and no free tier. The clinician App Store is a creator/supply funnel, not a buyer self-serve plan. The ~$9/agent-hour and creator-share figures are company- and third-party-reported and indicative; the actual contract is quoted.

Hidden costs : What Hippocratic AI users actually pay

The headline “$9 vs $39 an hour” is compelling, but the real cost is shaped by how many agent-hours you actually consume, and the agent — not the buyer — partly determines call length. Because billing is on active patient-interaction time, a campaign that triggers many long conversations (chronic-care check-ins, post-discharge calls) accrues hours fast, and high-demand periods drive the bill up with no published per-interaction cap.

Other things to budget for outside the active-hour meter: enterprise integration into EHR/scheduling systems, clinical oversight and safety review, and HIPAA/security/compliance work are part of an enterprise engagement, not a line on a public rate card. And because there is no public price page, buyers cannot model spend precisely without a sales conversation — the $9 figure is a reported operational rate, not a contracted, self-serve sticker.

Want to estimate your own Hippocratic AI bill? Use the Hippocratic AI pricing calculator to model your costs based on agent-hours and interaction volume.

Pricing evolution : Hippocratic AI pricing history and changes

Cadence

Tracked range: 2024–present. Hippocratic has never published a public rate card, so there are no Wayback price snapshots to chart — the evolution here is product and go-to-market (staffing meter → App Store creator share → new agent surfaces), not posted prices.

Notable changes

• 2024-03 — Introduces a “staffing marketplace” where health systems “hire” non-diagnostic patient-facing agents; the reported operational rate is ~$9 per agent-hour vs ~$39/hr for an RN. Series A ($53M, $500M valuation). NVIDIA empathy-inference partnership announced the same month.
• 2025-01 — Launches the AI Agent App Store; licensed clinicians build/certify agents and earn 5% of base + 70% of premium, capped at $5,000/agent. Series B ($141M, $1.64B valuation, Kleiner Perkins) — unicorn status.
• 2025-11 — Series C ($126M, $3.5B valuation, Avenir Growth); 50+ health-system partners. The per-agent-hour meter is unchanged — the model scales on hours of patient interaction delivered.

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

1. The agent-hour as the value metric. In a corpus of token-, request-, and seat-metered tools, Hippocratic meters the hour of active patient interaction and prices it directly against a nurse’s wage. The unit is intuitive to a hospital CFO and ties the price to the labor it displaces — a genuinely different anchor from “per 1M tokens.”

2. Priced as labor you hire, not software you license. The framing is AI staffing: you “hire” an agent for a shift’s worth of work and pay only for active time. That makes the buy resemble a contract-labor or staffing-agency line item, not a SaaS subscription — and it sidesteps the “what’s a token?” education problem entirely.

3. A two-sided clinician marketplace on top of the meter. The App Store pays the licensed clinicians who build agents (5% of base + 70% of premium, $5,000 cap), creating a supply curve of certified specialty agents. The buyer pays per hour; the creator earns a share of that hour — usage-based pricing wrapped around a marketplace, which is rare in healthcare AI.

Strengths & weaknesses

Billing UX : Hippocratic AI billing controls and transparency

• Billing controls — Enterprise, contract-based: deployments are scoped and quoted with sales, not toggled in a self-serve dashboard. Usage accrues on active agent-hours, so spend is governed by how much patient-interaction volume you route to agents rather than by a fixed subscription.
• Usage visibility — The product surface emphasizes safety and clinical outcomes (the Safety Portal login, benchmarks, case studies). There is no public cost calculator or published rate card, so a health system cannot model spend without a sales conversation; the ~$9/agent-hour figure circulates via press and the company’s own statements rather than an in-app meter preview.
• Payment options — Invoiced enterprise contracts via direct sales. The AI Agent App Store adds a creator-payout rail (5% base + 70% premium, capped $5,000/agent) for clinicians who publish agents — a payments surface aimed at supply, not at buyer self-serve.

Strategic wins : Why Hippocratic AI’s pricing decisions worked

1. Pricing against a wage, not a token

By metering the agent-hour and benchmarking it at ~$9 against a ~$39 RN wage, Hippocratic gives buyers a value story they already understand — labor cost — instead of asking a hospital to reason about tokens or API calls. The meter is the displaced unit of work. See choosing the right usage metric.

2. Selling AI as staffing, not subscription

Framing agents as on-demand staffing slots the spend into a labor budget, where there’s far more money and far less SaaS-fatigue than in software line items. It also makes the value proposition outcome-adjacent — hours of patient work delivered — without committing to hard outcome pricing. Related: how AI companies are shifting away from per-user licenses.

3. A clinician App Store as a supply flywheel

Paying licensed clinicians to build and certify agents (5% base + 70% premium) turns the people who best understand the work into the supply side of the marketplace — expanding agent coverage across specialties while keeping safety review in clinician hands. See outcome-based pricing trends.

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

1. The buyer doesn’t fully control the meter

Billing on active agent-time means cost rises with call duration and volume — and the agent, not the buyer, partly decides how long an interaction runs. Without a per-interaction cap or a budget ceiling, heavy-demand periods carry unbounded hourly cost. See bill shock and cost unpredictability.

2. No public price transparency

The ~$9/agent-hour figure is everywhere in the press but nowhere on the site (the /pricing URL 404s). A posted “starting at ~$9/agent-hour” with a simple methodology would shorten cycles and let buyers self-qualify without a sales call.

3. Per-hour vs the outcome it sells

The agent’s job is to complete a clinical task (a screening, an intake, a check-in), but the meter charges for time, not completion. As outcome pricing matures in healthcare AI, a per-completed-interaction or per-resolved-task option would align price with the result buyers actually want — and remove the incentive to run longer calls. See usage-based pricing strategy.

Key takeaways

1. Hippocratic prices AI like labor. The meter is the agent-hour (~$9 of active patient time), benchmarked against a ~$39/hour RN wage — a CFO-legible value story no token meter can match.
2. It’s staffing, not subscription. You “hire” agents and pay only for active time; spend lives in a labor budget, not a SaaS line item — but it inherits labor’s demand-driven volatility.
3. No public price, no free tier. The /pricing URL 404s; the $9 figure is company- and press-reported, and every deployment is sales-led.
4. The App Store is a two-sided marketplace. Clinician creators earn 5% of base + 70% of premium (cap $5,000/agent), building a vetted supply of specialty agents on top of the per-hour meter.
5. Time vs outcome is the open question. Charging for hours rather than completed tasks works today but sits in tension with where healthcare AI pricing is heading.

UBP implications

1. A wage can be the most persuasive value metric. Pricing per agent-hour against a known labor rate makes usage-based AI legible to non-technical buyers — a pattern any vertical replacing human work can borrow. See usage-based pricing strategy.
2. Time-based usage meters import demand volatility. Without per-interaction caps, hourly billing reproduces the unpredictability buyers fear; the lesson is to pair an active-time meter with budget ceilings or completion-based options.
3. Marketplaces let usage pricing scale supply. A creator revenue share turns the buyer’s per-hour spend into supply-side incentive — a structural way to expand catalog breadth that pure first-party usage pricing can’t.

Sources

• Hippocratic AI official website (live capture, accessed 2026-06-10)
• Hippocratic AI — View All Agents (live capture, accessed 2026-06-10)
• eesel — Hippocratic AI pricing overview (~$9/hour, creator program) (accessed 2026-06-10)
• Sacra — Hippocratic AI valuation, funding & “$9 per agent-hour” (accessed 2026-06-10)
• Contrary Research — Hippocratic AI business breakdown (accessed 2026-06-10)
• Fierce Healthcare — Hippocratic banks $53M Series A (accessed 2026-06-10)
• Maginative — $141M Series B, AI Agent App Store launch (accessed 2026-06-10)
• NVIDIA — Hippocratic AI customer story (Polaris, H200, empathy inference) (accessed 2026-06-10)
• nurse.org — “$9 Per Hour” AI nurse agents (accessed 2026-06-10)

Bottom line

Hippocratic AI is a safety-focused healthcare LLM company (~$402M raised, $3.5B valuation) whose patient-facing agents handle non-diagnostic clinical tasks over real-time voice. Its pricing is its signature: agents are sold as on-demand AI staffing at roughly $9 per agent-hour of active patient time — benchmarked against a ~$39/hour RN wage — with no seats, no tokens, and no public self-serve price (the /pricing URL 404s). A January 2025 AI Agent App Store adds a two-sided marketplace where clinician creators earn 5% of base + 70% of premium (capped $5,000/agent). The model is legible and labor-anchored, but it bills for time rather than outcomes and gives buyers limited control over the meter. Browse the pricing blueprint for more fully-researched company profiles.

Want to compare Hippocratic AI against other AI-agent and healthcare companies? Browse the pricing blueprint.