- Revenue: $157 million in Q1 FY2027, up 7% year over year, exceeding the high end of guidance.
- Adjusted EBITDA: $75 million, representing a 48% margin, an 8% beat versus the high end of guidance.
- Non-GAAP Gross Margin: 88% in Q1, down from 91% in the prior year due to increased AI compute spend.
- GAAP EPS: $0.13 per share in Q1.
- Non-GAAP EPS: $0.29 per share in Q1.
- Stock-Based Compensation (SBC): $37 million in Q1, or 23% of revenue; excluding a fiscal '26 AI-focused R&D grant, SBC would have been approximately 19% of revenue.
- Free Cash Flow: $40 million in Q1, with a decrease versus the prior year attributed to normal fluctuations in collections.
- Cash Position: $688 million in cash, cash equivalents, and marketable securities; company remains debt-free.
- Share Repurchases: $92 million worth of shares repurchased in Q1; approximately $400 million remaining in the repurchase program.
- Customer Metrics: 127 pharma and hospital customers generating more than $500,000 in annual subscription revenue on a trailing 12-month basis, up 7% year over year, contributing 83% of total revenue.
- Net Revenue Retention (NRR): Overall NRR was 107% in Q1 on a trailing 12-month basis; top 20 customers produced NRR of 112%.
- Q2 FY2027 Revenue Guidance: Expected range of $170 million to $171 million, representing 1% year-over-year growth at the midpoint.
- Full-Year FY2027 Revenue Guidance: Revised range of $671 million to $681 million, representing 5% growth at the midpoint.
- Q2 FY2027 Adjusted EBITDA Guidance: Expected range of $80.5 million to $81.5 million, representing a 48% margin at the midpoint.
- Full-Year FY2027 Adjusted EBITDA Guidance: Revised range of $309 million to $329 million, representing a 47% margin at the midpoint.
Release Date: August 06, 2026
For the complete transcript of the earnings call, please refer to the full earnings call transcript.
Positive Points
- Revenue growth reaccelerated to $157 million in Q1, up 7% year over year, beating guidance by 3%.
- Adjusted EBITDA was $75 million with a 48% margin, exceeding the high end of guidance by 8%.
- Doximity's AI product 'ask' led the independent NOHARM study with the lowest clinical error rate (4.8%) among US models, outperforming competitors like Anthropic.
- Quarterly active workflow prescribers grew over 30% year over year, with nearly half using AI tools and AI prompt volume up 25% quarter over quarter.
- AI search monetization is off to a strong start, with over two dozen programs onboarded and a robust pipeline, driving a full-year revenue guidance raise.
- The company has 165 signed health system AI clients, including top hospitals like Northwestern, Penn Medicine, and the University of Michigan.
- AI scribe users grew 10 times year over year in July, positioning Doximity as a top-three player in both AI search and scribe markets.
- AI search unit economics are favorable, earning more than 10x per search in revenue compared to costs, with potential for margin expansion.
- The company maintains a strong balance sheet with $688 million in cash and no debt, and repurchased $92 million in shares during the quarter.
- SMB pharma business grew over 100% in the quarter, diversifying the customer base and expanding market opportunities.
Negative Points
- Q2 revenue growth is expected to be only 1% year over year due to tough comparisons and modest AI search revenue recognition.
- Gross margin declined to 88% from 91% year over year due to increased AI compute spend, with expectations of mid-to-high 80% margins for the year.
- The overall pharma spending environment remains tight, with budget stability but not significant growth.
- AI search revenue is not recognized in Q1, and the majority of contracted revenue is expected to be recognized in Q3, creating timing uncertainty.
- Free cash flow decreased to $40 million in Q1 due to normal fluctuations in collections, which may impact near-term liquidity.
- Stock-based compensation increased to 23% of revenue, primarily due to an AI-focused R&D grant, which could pressure earnings.
- The company is investing heavily in AI, with over 90% of AI expenses focused on responding to demand, potentially limiting near-term profitability.
- GAAP effective tax rate rose to 40% from 17% due to equity compensation treatment, impacting reported earnings.
- The AI search product is still in early stages with conservative inventory caps and short-term contracts, limiting immediate revenue contribution.
- Competition in clinical AI is intense, with major players like Microsoft and UpToDate, and the market is still evolving toward enterprise adoption.
Q & A Highlights
Q: What does the NOHARM study mean for Doximity from a competitive perspective, and how can it influence trust and usage among physicians?
A: Jeff Tangney, CEO, highlighted that the independent Stanford and Harvard-led NOHARM study, which evaluated 24 clinical AI models across 1,100 real-world patient cases, ranked Doximity's "ask" product as the top US model with the lowest clinical error rate (4.8% vs. 13.6% for Anthropic's best model). He attributes this to the company's unique built-in drug reference and its 12,000 physician "check editors" who continuously refine AI outputs. This validation is crucial for hospital AI steering committees concerned about liability and patient data privacy, positioning Doximity to win enterprise contracts as the market shifts from the "AI Wild West" to an enterprise-driven, accountability-focused model.
Q: Can you provide more detail on the economics of AI search and the company's investment strategy for fiscal 2027?
A: Jeff Tangney, CEO, explained that over 90% of AI spend is directed toward serving doctors and improving answer quality, driven by better-than-expected usage. He noted that the unit economics are strong, with the company earning more than 10x per search in revenue compared to the cost of running it, and expects AI costs to decrease over time as models become more efficient. CFO Matt Sonefeldt added that the company is intentionally investing heavily in AI this year, which will pressure gross margins to the mid-to-high 80% range, but this is a deliberate trade-off to capture the significant long-term opportunity, with AI search expected to be accretive to margins in fiscal 2028 and beyond.
Q: How is the overall pharma buying environment, and how is the launch of AI search impacting budget dynamics?
A: CFO Matt Sonefeldt stated that while the overall pharma spending environment remains "tight," it is more stable. The launch of AI search has allowed Doximity to tap into new "AI innovation budgets" and "insights and analytics budgets" that were previously inaccessible. This has opened up higher-level conversations with C-suite executives and is fueling demand across the broader pharma portfolio. The company has already onboarded its first cohort of AI search customers across more than two dozen programs, with the majority of contracted revenue expected to be recognized in Q3.
Q: What is the strategy for scaling AI search contracts, and how is the product being packaged for the upcoming upfront season?
A: CFO Matt Sonefeldt and SVP of IR Perry Gold explained that the initial launch used conservative inventory caps and shorter 3-4 month contracts to protect the user experience and iterate on the product. As they move into the upfront, the focus shifts to larger, longer-term contracts with greater inventory across more therapeutic categories. Perry Gold noted that the company is expanding the ways customers can buy, including category-specific, keyword-specific, and target-list-based options, which is driving increased deal velocity and engagement from the sales team.
Q: Can you elaborate on the growth of the AI scribe product and its role in the broader AI strategy?
A: Jeff Tangney, CEO, highlighted that AI scribe usage grew 10x in July year-over-year and is the company's fastest-growing product in terms of new physician adoption. He sees it as the "connected glue" between Doximity's telehealth and clinical decision support (ask) tools, forming the core of a future "doctor's digital assistant." This integrated platform approach is a key differentiator, as health systems prefer comprehensive platforms over point solutions. Doximity is now top three in both AI search and scribe markets, a position no other competitor holds.
Q: How is the AI search product creating an accretive effect on the core legacy offerings?
A: Jeff Tangney, CEO, confirmed that AI search is creating a "one plus one equals three" effect. Conversations about AI search, which reveal specific physician concerns (e.g., side effect profiles or dosing conversions), are generating additional opportunities for Doximity's core telehealth platform to address those needs. This synergy between "signal" (from AI search) and "reach" (from the core platform) is unlocking new value for clients and driving growth across the entire business.
Q: What is the status of the 165 signed health system AI clients, and how is the market for enterprise AI adoption maturing?
A: Jeff Tangney, CEO, stated that Doximity is live at all 165 health systems, though they are at various stages of EHR integration. He noted a shift from "AI adoption to AI accountability," with health systems increasingly blocking unauthorized AI tools due to concerns about patient data (PHI) leakage and liability. This trend favors Doximity, which has privacy agreements and a proven track record of safety and accuracy, positioning it to win as the market consolidates around enterprise-approved solutions.
Q: How large are the AI budgets for pharma customers, and where does Doximity stand in capturing this spend?
A: Jeff Tangney, CEO, acknowledged that pharma AI budgets are still nascent, with a recent analyst survey suggesting they represent less than 10% of overall budgets. However, the same survey indicated that Doximity is the number one choice for where pharma buyers would spend their AI budget, despite the product being only a few months old. He sees the total addressable market as very large, potentially exceeding the $14 billion Google paid search spend by pharma, as AI becomes more ingrained in medical decision-making.
Q: Can you provide more color on the proprietary drug reference component of the AI model and its importance?
A: Jeff Tangney, CEO, drew on his 11 years of experience in the drug reference space to explain that a built-in drug reference is critical for clinical decision support, citing UpToDate's success after acquiring Lexicomp. Doximity's "ask" product integrates discrete drug data elements, enabling accurate dosing, indication matching, and drug-drug interaction checks. This, combined with the 12,000 physician "check editors" who review outputs, is a key reason for the company's top performance in the NOHARM study and a significant competitive moat.
Q: How is the performance of the SMB pharma segment, and is it seeing similar buying dynamics to large pharma?
A: SVP of IR Perry Gold reported that the SMB segment has been "really strong,"
For the complete transcript of the earnings call, please refer to the full earnings call transcript.
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