Leal Health
AI-powered platform matching cancer patients to advanced treatments and clinical trials.
Website: https://leal.health/
Cover Block
From the public record
| Field | Value |
|---|---|
| Company | Leal Health |
| Tagline | AI-powered platform matching cancer patients to advanced treatments and clinical trials. |
| Headquarters | New York, US [LinkedIn] |
| Founded | 2017 [Crunchbase] |
| Stage | Series A [Startup Intros] |
| Business model | B2B2C |
| Industry | Healthtech |
| Technology | AI / Machine Learning |
| Geography | North America |
| Growth profile | Venture Scale |
| Founding team | Tzvia Bader, Avital Gaziel, Guy Gildor, Noam Geva [leal.health] |
| Funding label | Series A |
| Total disclosed funding | $27.7 million [Business Insider, July 2023] |
Links
From the public record
- Website: https://leal.health/
- LinkedIn: https://www.linkedin.com/company/lealhealth
The Short Version
PUBLIC Leal Health is building an AI-guided oncology decision-support platform that matches cancer patients to advanced treatments and clinical trials, a wedge that merits attention because the company sits at the intersection of patient navigation, provider decision support, and pharma trial recruitment [Business Insider, July 2023] [TechCrunch, December 2019] [leal.health]. The company was founded in 2017 and traces its origin, in part, to CEO and co-founder Tzvia Bader’s experience as a stage-IV melanoma survivor, according to the company’s January 2023 account of its founding story [leal.health, January 2023].
The product thesis is relatively clear even where public operating data is thin: Leal says its platform analyzes patient information against treatment and trial options, and it has since expanded beyond trial matching into FDA-approved cancer treatment decision support, which suggests a broader workflow than a single-use referral tool [Business Insider, July 2023] [TechCrunch, December 2019] [Fierce Biotech]. The company also discussed a generative-AI feature intended to assist patients and staff in a March 2024 interview, though the practical adoption and clinical impact of that layer are not yet well documented in public sources [Techstrong.ai, March 2024].
The team reads as founder-led and mission-driven, with Bader publicly identified as CEO and co-founder, Guy Gildor as CTO and co-founder, Avital Gaziel as co-founder and chief scientific officer, and Noam Geva as founder and VP of Product and Product Design [TechCrunch, November 2021] [Bloomberg Markets] [ZoomInfo] [Noam Geva - Leal Health | LinkedIn, Retrieved 2026]. Public biographies indicate relevant prior startup and technical experience, particularly on the product and data side, but the stronger claims around founder background remain unevenly corroborated across sources [Forbes, December 2020] [TechCrunch, October 2013].
On capitalization, the public record supports a seed round of $2.7 million in December 2019 and a $20 million Series A in February 2022, while Business Insider reported total funding of $27.7 million as of July 2023 [Startup Intros] [Business Insider, July 2023]. The business model is best described as B2B2C from the available evidence, with value flowing to patients while monetization appears tied to healthcare and life sciences stakeholders that need treatment-navigation and trial-matching infrastructure [Business Insider, July 2023] [leal.health].
Over the next 12 to 18 months, the central questions are whether Leal can show independently verified enterprise adoption, sustain differentiation as oncology navigation and trial-matching markets become more crowded, and translate company-reported engagement into repeatable commercial outcomes [leal.health] [Techstrong.ai, March 2024]. The most encouraging public signal remains category fit: TechCrunch reported the company was on track to match 50,000 cancer patients with clinical trials in 2021, with 35% of matched patients from underrepresented groups, but investors will still want cleaner third-party proof of customer concentration, clinical workflow penetration, and revenue durability [TechCrunch, November 2021].
Single-source, plausible -- Supported by a mix of independent reporting, company materials, and database profiles; funding and leadership are partially corroborated, while several operating claims remain company-sourced.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Series A |
| Business Model | B2B2C |
| Industry / Vertical | Healthtech |
| Technology Type | AI / Machine Learning |
| Geography | North America |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding | Total disclosed ~$27,700,000 |
The Company in Brief
PUBLIC
Leal Health traces back to 2017 and presents as a New York based healthtech company focused on helping cancer patients identify treatment and clinical trial options [Crunchbase] [leal.health, Unknown]. The company was previously known as TrialJectory, a detail that matters because much of the earlier public record, including funding and media coverage, still sits under the prior name rather than the current brand [Crunchbase].
The founding story is unusually direct and, in this case, company-sourced. Leal says CEO and co-founder Tzvia Bader started the company after her own stage IV melanoma experience, with the broader aim of making advanced cancer care easier to access for patients facing a fragmented treatment search [leal.health, January 2023]. The company website and founder pages identify Bader, Avital Gaziel, Guy Gildor, and Noam Geva as co-founders, with Gaziel serving as chief scientific officer, Gildor as CTO, and Geva in product and design leadership roles according to their public profiles [leal.health, Unknown] [Crunchbase] [LinkedIn, Retrieved 2026].
The public milestone record is still fairly compact. Crunchbase lists the company as founded in 2017, while the better-documented early operating milestone is a December 2019 seed round, followed by a February 2022 Series A that pushed disclosed funding to roughly $27.7 million on later public tallies [Crunchbase] [leal.health, Unknown]. Over time, the company appears to have broadened from clinical trial matching under the TrialJectory name to a wider cancer treatment decision-support platform under the Leal Health brand, based on the current website positioning and archived coverage tied to the earlier name [leal.health, Unknown] [Crunchbase].
Single-source, plausible -- Based primarily on Crunchbase and the company website, with founder-role corroboration from public profiles but limited legal-entity detail in the reviewed sources.
What They Have Built
Mixed sourcing
Leal Health is selling a narrower product than the broad "AI in healthcare" label might suggest. Public sources describe the platform as a cancer treatment decision-support system that analyzes patient information against treatment and clinical trial options, with the core job of helping patients find advanced therapies and helping biopharma sponsors improve trial recruitment [Business Insider, July 2023] [TechCrunch, December 2019]. The company says the product serves patients, clinicians, and pharmaceutical companies, and that it offers a single access point to treatment options based on a patient’s medical profile, biomarkers, and preferences [leal.health] [Fierce Biotech].
The product surface appears to have expanded beyond trial matching. TechCrunch described the earlier workflow as using self-reported clinical data to match patients with trials in 2019, while later coverage and company materials position Leal as covering both clinical trials and FDA-approved cancer treatments [TechCrunch, December 2019] [Fierce Biotech] [leal.health]. That suggests the company is trying to own a larger share of the oncology decision journey rather than remaining a point solution for trial discovery alone.
Leal’s public AI claims are directionally clear, but the evidence is stronger on use case than on technical architecture. The company and press coverage consistently describe the platform as AI-powered, and a March 2024 interview referenced a generative AI feature intended to assist patients and staff, but none of the reviewed public materials substantiate model provenance, regulatory positioning, or workflow-level performance metrics beyond company-reported match volume [leal.health] [Techstrong.ai, March 2024]. Leal reports more than 3,000,000 treatment matches to date, which indicates substantial throughput if measured consistently, though that figure remains company-reported and is not independently reconciled in the public record [leal.health].
Unconfirmed -- Product scope is partially corroborated by Business Insider, TechCrunch, and Techstrong.ai, but several material claims, including AI positioning and cumulative match volume, rely on company statements.
Market Size and Demand
From the public record
Cancer navigation and trial-matching software matters now because oncology remains one of the few care pathways where small improvements in matching, timing, and treatment awareness can change both patient outcomes and the economics of drug development, yet the public record for this company does not include a third-party market size study specific to its niche [TechCrunch, December 2019] [Business Insider, July 2023]. In that absence, the cleaner read is to frame Leal Health against adjacent, better-documented markets: digital patient engagement in oncology, clinical trial recruitment software, and AI-assisted clinical decision support, all of which are directionally relevant but not exact proxies for Leal's addressable market.
The demand signal surfaced in the available reporting is less about abstract healthcare AI spending and more about workflow friction. TechCrunch described the company's early product as using self-reported clinical data to match cancer patients with trials, which points to a longstanding bottleneck in oncology: patient eligibility is fragmented across diagnosis, biomarkers, prior therapies, geography, and protocol design [TechCrunch, December 2019]. By late 2021, TechCrunch reported the company was on track to match 50,000 cancer patients with clinical trials that year, with 35% of matched patients coming from underrepresented groups, suggesting demand may be strongest where existing referral pathways miss patients or move too slowly [TechCrunch, November 2021].
The commercial tailwind is similarly practical. Business Insider's 2023 profile describes Leal as serving cancer patients while also helping pharmaceutical companies recruit trial participants, which places the company in an area where patient acquisition, enrollment velocity, and diversity goals increasingly intersect [Business Insider, July 2023]. Fierce Biotech's coverage of the platform's expansion into FDA-approved treatment decision support suggests the company is also reaching into a broader care-navigation budget, not only trial recruitment, although the public materials reviewed do not quantify how much of usage or revenue comes from each side of that split [Fierce Biotech].
| Cited market signal | Figure | Relevance to Leal |
|---|---|---|
| Patients matched with clinical trials in 2021 | 50,000 | Indicates reported demand for oncology trial-matching workflows rather than market size [TechCrunch, November 2021] |
| Share of matched patients from underrepresented groups | 35% | Suggests value in diversity-focused recruitment and patient access workflows [TechCrunch, November 2021] |
| Reported treatment matches to date | 3,000,000 | Signals breadth of matching activity, though company-reported and not independently verified [leal.health] |
| Reported total funding | $27.7M | Indicates investor appetite for the category, not end-market size [Business Insider, July 2023] |
The table does not establish TAM, but it does show where the public evidence is strongest: demand appears to cluster around trial discovery, treatment-option awareness, and access gaps for patients who are underserved by existing oncology pathways. That is a meaningful market signal, even if the precise budget line remains hard to isolate from adjacent care-navigation and life sciences software spend.
The adjacent markets are broad enough to matter. One substitute path is traditional oncology navigation delivered by hospitals, advocacy groups, and manual concierge services; another is point-solution trial recruitment sold to sponsors and contract research organizations. Leal's stated positioning across patients, clinicians, and pharmaceutical companies suggests it sits between those categories rather than neatly inside one of them, which can expand the opportunity set but also complicates procurement, product design, and proof of ROI [leal.health] [Business Insider, July 2023].
Regulation and macro conditions cut both ways. The supportive side is straightforward: oncology remains a research-intensive category, diversity in clinical trials has become more visible as an industry objective, and FDA-approved treatment pathways create room for software that helps organize options rather than replace clinician judgment [Fierce Biotech] [TechCrunch, November 2021]. The limiting side is equally clear: any platform handling patient-reported or clinical information in cancer care faces higher scrutiny around privacy, accuracy, explainability, and workflow integration, and generative AI features raise an additional burden to show that assistance tools improve navigation without introducing unsafe simplifications [Techstrong.ai, March 2024].
The practical market view, then, is narrower than generic healthcare AI framing would suggest. Public evidence supports a real need in oncology matching and navigation, especially where trial enrollment and advanced-treatment discovery are inefficient, but the record provided here is not sufficient to size the market with precision or to determine whether the larger budget pool sits with providers, life sciences companies, or direct-to-patient acquisition channels.
Single-source, plausible -- Based primarily on TechCrunch and Business Insider, with additional company and trade-publication context; no independent third-party TAM study was available in the provided sources.
Who Else Is Fighting for This
Positioning
MIXED Leal Health sits in a narrow but important part of oncology software: it is positioned less as a general hospital system and more as a matching layer that helps patients, clinicians, and pharma teams identify advanced treatments and relevant clinical trials from patient-specific data [Business Insider, July 2023] [TechCrunch, December 2019] [leal.health].
That framing matters because the company is not competing head-on with every healthcare AI vendor. The clearest public alternatives are established clinical-trial search pathways, oncology decision-support tools tied to provider workflows, and patient-navigation or advocacy channels that influence how patients discover treatment options. The challenge is that the structured public record here does not name direct rivals, so the competitive map has to be drawn by function rather than by a clean list of peer companies [Business Insider, July 2023] [TechCrunch, November 2021].
Within that function-based map, incumbents are likely to be the existing trial-discovery and care-navigation routes that already sit near oncologists, hospitals, or patient communities, while challengers are software companies trying to make matching faster and more personalized through data science. Adjacent substitutes include pharmaceutical recruitment programs and advocacy organizations that help patients reach trials through human support rather than software-first workflows. Leal's public materials suggest it wants to bridge those segments by serving patients directly while also supporting clinicians and pharmaceutical companies, which is strategically attractive but can produce a longer proof burden because each constituency evaluates value differently [leal.health] [Business Insider, July 2023].
Leal's defensible edge, based on public evidence, is its specialization. The company has stayed focused on cancer treatment and trial matching since its earlier TrialJectory branding, and that focus appears to have let it build a workflow around self-reported clinical data, biomarker and treatment-preference inputs, and a broader treatment-decision surface that now includes FDA-approved options alongside trial matching [TechCrunch, December 2019] [Fierce Biotech] [leal.health]. If durable, that edge would come from accumulated matching logic and user trust in a sensitive category. If perishable, it is because much of the visible differentiation is product-scope and user experience rather than a publicly verified exclusive dataset, regulatory moat, or owned distribution channel.
The biggest exposure is channel control. Public sources show ambition across patients, clinicians, and pharma, but they do not identify named health-system customers, distribution partners, or enterprise accounts that would suggest Leal already owns the referral path at scale [Business Insider, July 2023] [leal.health]. That leaves the company vulnerable to any better-capitalized oncology workflow vendor, trial-recruitment platform, or provider-embedded tool that can meet users earlier in the care journey. It also limits the confidence one can place on durability of the reported 3,000,000 treatment matches, since the company cites the figure publicly but the underlying source mix, repeat-user dynamics, and conversion into paid enterprise relationships are not independently disclosed [leal.health].
The most plausible 18-month scenario is that the competitive field bifurcates between workflow owners and specialist matchmakers. Leal is the likely winner if cancer programs, advocacy groups, or pharma sponsors continue to prefer a specialist layer focused on patient-level matching rather than a broad hospital software stack, particularly if the company's newer generative-AI features reduce navigation friction for patients and staff without compromising trust [Techstrong.ai, March 2024]. Leal is the likely loser if oncology discovery consolidates inside incumbent provider workflows or sponsor-controlled recruitment channels before the company secures visible, repeatable distribution at the point of care. In that case, the better-positioned player would not necessarily have the best matching interface, but the one that already owns the clinician or patient relationship.
Opportunity
Upside case
From the public record If Leal Health executes cleanly, the prize is not a niche patient-navigation tool but a default decision-support layer for oncology treatment selection and trial access across patients, providers, and life sciences workflows [Business Insider, July 2023] [leal.health] [Fierce Biotech].
The clearest upside sits in becoming the system of record for matching cancer patients to both standard-of-care options and trial opportunities. That outcome is reachable, not merely aspirational, because the company is already positioned across the three constituencies that matter in oncology access: patients, clinicians, and pharmaceutical companies [leal.health] [Business Insider, July 2023]. Public reporting describes a platform that analyzes patient information against treatment and trial options, while the company says it has already made more than 3,000,000 treatment matches to date [Business Insider, July 2023] [leal.health]. Even allowing for the fact that the treatment-match figure is company-reported, the product direction is unusually specific: Leal is not trying to be a general healthcare AI layer, it is concentrating on the high-friction oncology workflow where therapy complexity, biomarker requirements, and trial eligibility create real search costs for patients and sponsors [TechCrunch, December 2019] [Fierce Biotech].
A second reason the outcome is plausible is that Leal appears to have expanded beyond trial matching into FDA-approved treatment decision support, which materially widens the surface area from episodic trial referral to recurring care-navigation utility [Fierce Biotech]. Trial matching alone can produce a useful product; treatment guidance plus trial matching is closer to workflow infrastructure. The company has also raised a reported $27.7 million, including a $20 million Series A led by Insight Partners, which suggests it has had enough capital to build product depth rather than remain a lightweight matching interface [Business Insider, July 2023] [Startup Intros] [Tracxn, 2026].
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Patient gateway in oncology | Leal becomes a widely used front door for cancer patients seeking both approved treatments and trial options, with advocacy groups and patient-support channels driving top-of-funnel demand | Continued expansion of the treatment-matching product and deeper partnerships with advocacy and patient-support organizations [leal.health] | The company already positions itself as a single access point for treatment options based on medical profile, biomarkers, and preferences, and says it has partnered with advocacy and patient-support organizations [Fierce Biotech] [leal.health] |
| Sponsor recruitment infrastructure | Leal becomes an operating layer for pharmaceutical and biotechnology companies that need qualified patient identification and recruitment support for oncology studies | More enterprise adoption from pharma as trial recruitment pressure remains high and Leal's matching workflow proves useful at scale [Business Insider, July 2023] [TechCrunch, December 2019] | Business Insider explicitly describes a model that supports patients while helping pharmaceutical companies recruit clinical-trial participants, and the original product was built around structured clinical-trial matching [Business Insider, July 2023] [TechCrunch, December 2019] |
| AI copilot for oncology navigation | Leal turns its generative-AI functionality into a productivity layer for patients and internal support teams, improving conversion, throughput, and service economics | Productization of the generative-AI assistant discussed publicly in 2024 [Techstrong.ai, March 2024] | The company has already discussed a generative-AI feature intended to assist patients and staff, which indicates management is thinking beyond static search into guided interaction [Techstrong.ai, March 2024] |
These scenarios point to different entry points, but they all rely on the same underlying claim: oncology matching is valuable enough that whoever reduces search friction can sit in the middle of multiple transaction flows. The evidence in hand does not prove Leal has already won that position, but it does show a product footprint broad enough to pursue it.
What compounding would look like here is straightforward. More patient usage can generate more matching activity, which can improve the system's relevance and workflow design; better matching and navigation can make the platform more useful to providers and trial sponsors; sponsor demand can then support broader distribution and more reasons for patients to start their search inside Leal [TechCrunch, December 2019] [Business Insider, July 2023] [leal.health]. The company-reported milestone of more than 3,000,000 treatment matches is the early signal to watch, because even if the figure is not independently verified, it suggests the platform may already be accumulating interaction volume that can inform ranking, eligibility interpretation, and user guidance over time [leal.health]. The underrepresented-patient statistic reported by TechCrunch is also relevant here: if Leal is better at reaching populations often missed by traditional recruitment channels, that can become both a mission advantage and a commercial one for sponsors trying to improve enrollment diversity [TechCrunch, November 2021].
The size of the win is difficult to anchor precisely because the input set does not include a confirmed market-sizing source or a named public comparable devoted to this exact workflow. Even so, the scenario analysis can still be framed conservatively. If Leal were to become a meaningful oncology access and recruitment platform, spanning patient acquisition, treatment decision support, and sponsor recruitment, it would likely be valued more like healthcare workflow software than like a single-purpose consumer tool (scenario, not a forecast) [Business Insider, July 2023] [Fierce Biotech]. The path to that outcome depends less on headline AI claims than on whether Leal becomes embedded in the recurring decisions around cancer care and trial enrollment. That is a large prize because oncology is one of the few clinical domains where matching accuracy, speed, and trust have immediate consequences for patients and measurable value for drug developers [TechCrunch, December 2019] [Business Insider, July 2023].
Single-source, plausible -- Based on a mix of independent reporting from Business Insider and TechCrunch, plus material company claims from leal.health and product-expansion reporting from Fierce Biotech.
Sources
From the public record
[Business Insider, July 2023] VCs Name the Most Promising Healthtech Startups in 2023 | https://www.businessinsider.com/vcs-most-promising-startups-healthtech-2023-6
[TechCrunch, December 2019] Trialjectory uses self-reported clinical data to match cancer patients with clinical trials | https://techcrunch.com/2019/12/17/trialjectory-uses-self-reported-clinical-data-to-match-cancer-patients-with-clinical-trials/
[Leal Health, January 2023] Leal Health, Our Story | https://leal.health/post/our-story
[Techstrong.ai, March 2024] AI Leadership Insights: AI for Health Platform | https://techstrong.ai/videos/ai-leadership-insights-ai-for-health-platform/
[TechCrunch, November 2021] Trialjectory on track to match 50K cancer patients with clinical trials this year: 35% are from underrepresented groups | https://techcrunch.com/2021/11/12/trialjectory-on-track-to-match-50k-cancer-patients-with-clinical-trials-this-year-35-are-from-underrepresented-groups/
[Forbes, December 2020] 5 Bold Predictions For Israeli Tech In 2020 | https://www.forbes.com/sites/eyalbino/2020/12/31/5-bold-predictions-for-israeli-tech-in-2020/
[Leal Health] Leal Health | https://leal.health/
Articles about Leal Health
- Leal Health's AI Already Matched 3 Million Cancer Patients to Treatments — The platform, founded by a stage-IV melanoma survivor, aims to connect patients with clinical trials while helping pharma companies recruit.