Landscape review · working dashboard

The Ophthalmology Startup Landscape

Rev. 03 · 6 Aug 2026

Where capital, patients, and competition actually sit in eye care — and the gaps between them. Built as a live working document: each idea analysed from here on gets logged at the bottom.

At a glance

A large, well-paid specialty with a starved software layer

Eye care has an unusual shape: enormous, well-reimbursed clinical demand sitting on top of almost no venture-scale technology spend. Capital pours into molecules; the delivery layer is nearly unfunded.

People with sight loss

1.1bn

Living with the consequences of vision loss worldwide — mostly for want of access, not want of a treatment.

WHO fact sheet

Annual productivity loss

$411bn

Against an estimated $25bn cost to close the unmet-need gap. A 16× spread.

WHO fact sheet

Ophthalmology VC · 2025

~$2.0bn

▲ 112% vs 2024 — $934m in 2024. Concentrated in retinal therapeutics.

Market Scope funding tracker

Digital eye care VC · 2025

$5.3m

Across 2 rounds through October. Roughly 0.3% of the sector's capital reached software.

Tracxn — digital eye care

Diabetics imaged for retinopathy

4.2%

Received ophthalmic imaging over a five-year window in a US cohort study. Of those, just 2.2% were screened by an AI system.

PMC — US DR imaging cohort

Autonomous AI systems cleared

3

LumineticsCore (2018), EyeArt (2020), AEYE-DS (2022) — plus a further clearance in H1 2026. A billing code has existed since 2021.

Optometry Times — H1 2026 FDA recap

Annual exam adherence

50–70%

Share of diabetic patients who attend their recommended annual eye exam. The rest are the market.

PMC — DR screening adherence

The two numbers to hold together: a screening technology cleared eight years ago, with its own reimbursement code, still reaches roughly one diabetic patient in a thousand. Regulatory clearance and a CPT code are necessary here, and demonstrably not sufficient. Retina Specialist — AI DR screening 2025

Capital

Where the money actually went

2025 was a genuine boom — venture funding more than doubled. But it was a therapeutics boom: four rounds account for most of it, and every one of them is a drug or an implant.

Ophthalmology venture funding by year

US$ · equity rounds
Complete year Partial year to date Market Scope · Tracxn

Market Scope counts venture capital narrowly; Tracxn counts all equity funding. They differ ~2× on 2024 and are shown here on Market Scope's basis. 2026 is a partial year. Market Scope

Table view

The rounds that made 2025–26

CompanyAmountWhat it isSource
Belite Bio$350mOral tinlarebant for geographic atrophy & StargardtMarket Scope
Ollin Biosciences$330mVEGF/Ang2 bispecific (OLN324) for retinal diseaseMarket Scope
Science Corporation$230mPrima subretinal implant for dry AMDCompany
Orasis Pharma$126mPresbyopia-correcting eye dropMarket Scope
ForSight Robotics$125mORYOM robotic cataract surgery platformFierce Biotech

Where exits happen

DealValueBuyer typeSource
Retina Consultants of AmericaCencora$4.6bnDistributorOBN 2025 recap
EyeBioMerckup to $3bnPharmaMerck
PRISM VisionMcKessonundisclosedDistributorOBN 2025 recap
Cimerli franchise → Sandoz$170mPharmaOBN 2025 recap
Belkin VisionAlcon$81m upfrontDevice strategicAlcon

Note the buyer list. Two of the five largest are drug distributors buying practices, not technology. The exit path for eye-care software runs through pharma, device strategics (Alcon, Bausch + Lomb, J&J, Zeiss, Topcon), or the practice roll-ups — not through IPO.

Segments

Eight places to build, and what each one is really like

Maturity is judged by whether a new entrant is joining a fight, a build-out, or an empty room.

Surgical robotics · deep dive

Robots are finally operating on the eye

The eye is one of the hardest organs to operate on — micrometer tolerances, a surgeon's tremor, and a fraction of a millimetre of working space. That is exactly what robots are for, and 2024–26 is the moment it moved from papers to patients: first-in-human robotic cataract surgery, robot-assisted retinal surgery on real eyes, and the first approved endoscope-holding robot. The limiting factor is no longer the engineering; it is reimbursement and workflow.

ForSight Robotics — JASPER / ORYOM First-in-human done

What works: world's first fully robot-assisted in-human cataract procedure, filmed end-to-end. The JASPER platform pairs robotic arms (14 degrees of freedom, micron-level precision, tremor-free) with 3D image guidance, computer vision and software "no-fly zones". Proven by: 300+ fully robot-assisted porcine-eye procedures, ISO 13485 certification, and now human cases + early FDA-track data collection. Next: US regulatory pathway, then India/China/Middle East, then glaucoma & retina. $195m total; ~$500m valuation.

IsraelCataract → retina$125m Series Bfull deep dive →

Preceyes (Carl Zeiss Meditec)

The system that did it first: robot-assisted surgery inside a human eye at Oxford in 2018, removing a membrane a hundredth of a millimetre thick. Joystick telemanipulation, <20 µm precision, tremor-free — now CE-marked and heading toward FDA via New York Eye and Ear.

NetherlandsVitreoretinalWith Zeiss

Horizon Surgical Systems — Polaris

An AI-enabled robotic microsurgery platform for cataract surgery, combining robotic precision with intraoperative imaging. Founded by UCLA retina surgeon Jean-Pierre Hubschman; preparing for first-in-human studies. $30m Series A (2024).

USAI + microsurgery$30m Series A

Riverfield — OQrimo

The world's first approved ophthalmic endoscope-holding robot (Japan, 2023) — a robotic "third hand" that stabilises the intraocular endoscope so the surgeon keeps both hands on instruments. Built on the Eye Explorer research robot from Kyushu University.

JapanEndoscope holderApproved 2023

Acusurgical — LUCA

French robotics (LIRMM) spin-out with a dual-arm telemanipulated robot for full vitreoretinal surgery at up to 10 µm precision. First-in-human results — six vitrectomies for macular pathology — presented at the 2025 Retina World Congress with no device-related adverse events. European trial recruiting.

FranceVitreoretinalFirst-in-human 2025

The research frontier

IRISS (UCLA) — first robot to complete an entire cataract surgery mechanically. Ophthorobotics — head-mounted robot for automated intravitreal injections (the highest-volume procedure in retina). RAM!S (TU Munich) — a 306 g palm-sized robot with 5 µm accuracy for subretinal injection. OctoMag (ETH) — magnetic-field steering of a wireless microrobot inside the eye, achieving retinal vein cannulation in animal models.

Retina Today — robotics in retinal surgery

Why this matters for a new entrant. Every serious platform here is a hardware company with a regulatory path measured in years. But the software surface is wide open and immediately addressable: surgical planning, intraoperative AI (depth sensing, tremor-free target tracking), simulation/training for a field where surgeons train on eyes, and the reimbursement + workflow layer that every one of these robots needs. Note also the buyer dynamic — Zeiss already folded Preceyes in; the rest are acquisition candidates for Alcon, Bausch + Lomb, Zeiss, Topcon and J&J.

Who was first? Two companies claim first-in-human robotic cataract surgery and both are technically right — the claims differ in degree. Horizon Surgical announced (Oct 2025) the first in-human cataract procedures using a robotic and AI-enhanced platform (Polaris), where the robot assists standard steps. ForSight Robotics published (2026) the world's first fully robot-assisted in-human cataract procedure, where the robot performs the surgery with a surgeon in the loop. Watch the distinction: assistive robotics (Horizon) and surgical robotics (ForSight) are different products with different reimbursement and training dynamics. Devgan on Horizon's Polaris · ForSight first-in-human

Cell & gene therapy

The biotech layer — where the science is genuinely moving

Ophthalmology is one of the most active categories in cell and gene therapy: the eye is compartmentalised, easy to dose and image, and has measurable endpoints. This is where the majority of sector capital actually lands — the counterweight to the starved software layer. Companies link to their profiles; each carries its own sources.

Opus Genetics

Nasdaq: IRD

IRDs · gene therapy. OPGx-LCA5 AAV therapy for LCA5-associated Leber Congenital Amaurosis in a registrational Phase 3; enrollment completed Aug 2026. Formed via Ocuphire's acquisition of Opus.

Up to $155m Oberland facility (2026) · source

LCA1 · XLRS. ATSN-101 for GUCY2D-associated LCA1 published 12-month Phase 1/2 data in The Lancet; pivotal Phase 3 expected 2H 2026. ATSN-201 for X-linked retinoschisis.

$150m Series C (2025, Bain) · source

XLRP · gene therapy. laru-zova (AGTC-501) for RPGR-linked X-linked retinitis pigmentosa in a registrational Phase 2/3; VISTA enrollment completed Jul 2025, topline expected 2H 2026.

$170m Series B (2024) + >$75m Series C (2026) · source

SpliceBio

Barcelona

Stargardt · protein splicing. SB-007 — the first dual-AAV gene therapy FDA-cleared for Stargardt disease (ABCA4) — in Phase 1/2.

$135m Series B (2025) · source

Ray Therapeutics

Berkeley, CA

RP · optogenetics. RTx-015 in Phase 1 (ENVISION); FDA RMAT designation (Apr 2026). Series B funds the pivotal trial.

$100m Series A + $125m Series B · source

RP · gene-agnostic optogenetics. MCO-010 works regardless of the underlying RP mutation; rolling BLA submission initiated Jul 2025.

Funding data unverified · source

Kriya Therapeutics

Palo Alto / RTP

GA · platform gene therapy. Broad AAV platform across ophthalmology, neurology and metabolic disease; KRIYA-825 (complement inhibitor, suprachoroidal) in Phase 1/2 for geographic atrophy.

>$900m raised per company · source

Cornea · cell therapy. Allogeneic corneal endothelial cell therapy plus ROCK inhibitor; launched in Japan (2024), Phase 1/2 in the US.

$150m+ disclosed · source

RetinAI (Ikerian)

Bern, Switzerland

AI/data platform. FDA-cleared, CE-marked imaging AI for AMD, DR and glaucoma. The segment's biggest 2025 exit: acquired by EssilorLuxottica.

Acquired Oct 2025 · source

Context: ~75% of ophthalmology investor capital consistently goes to retinal-disorder companies, and the pipeline skews heavily to later-stage assets — investors are paying down clinical risk, not betting on moonshots. Gene therapy faces persistent market-access and manufacturing-cost questions (retinitis pigmentosa funding actually declined in 1H 2025). For a software entrant this layer is competitor, customer and benchmark all at once. Outcome Capital

Who's building

The incumbent set

Who you would be competing with, partnering with, or selling to. Funding figures are latest disclosed.

Scorecard

Segment conditions, scored

Each segment rated 1–5 on how favourable it is to a small, software-first new entrant. Higher is better in every column. These are judgements, not measurements — argue with them.

Entrant conditions by segment

HOSTILE FAVOURABLE

What the grid says. Retinal therapeutics is the only column-topping segment on payment clarity and the worst on everything a small team controls. Clinic operations is the inverse: trivially reachable, immediately payable, and unglamorous. The interesting rows are the ones that are mixed — oculomics and home monitoring both have real whitespace paired with a payment problem, which is a solvable kind of hard.

Barriers

Why good eye-care technology stalls

The graveyard in this space is not full of things that didn't work. It is full of things that worked, got cleared, got a billing code, and still didn't get used.

Adoption

Clearance is not adoption

Three autonomous AI systems have been FDA-cleared since 2018. In a five-year US cohort, 4.2% of diabetics got imaged at all and 2.2% of those via AI. Studies consistently find the binding constraints are workflow integration, EHR plumbing, operator training, and image-quality assurance — not accuracy.

Cleared 2018 · still <0.1% of the eligible population cohort study · barriers review

Payment

A code is not a business

CPT 92229 (2021) was the first AI-specific code in US medicine and lets primary care bill without specialist oversight. It still did not produce adoption: the payment has to exceed the fully-loaded cost of camera, staff time, and failed captures, and the person who bills is often not the person who bears the cost.

First-ever AI CPT code · five years old · marginal uptake CRSToday · Retina Specialist

Buyer

The payer is split in two

Routine vision (exams, glasses, contacts) is paid by vision plans — VSP, EyeMed, Superior, Davis. Disease (glaucoma, AMD, diabetic retinopathy, cataract) is paid by medical insurance and Medicare. A product that straddles the two has no natural budget owner, and that ambiguity kills deals.

Two payers · one patient · no shared budget line vision vs medical

Consolidation

Your customer is being bought

EyeCare Partners, MyEyeDr and Total Eye Care Partners are rolling up practices at 3–6× EBITDA (6–8× for platform assets), with 40+ transactions across 2024–Q1 2025 and a wave of aged PE inventory due to trade again. Selling to independents is a shrinking motion; selling to consolidators means one long enterprise sale.

Fewer, larger, slower buyers each year PGP · FOCUS

Capital

The capital is not for you

Sector funding doubled to ~$2bn in 2025, but digital eye care took $5.3m of it. That is not a signal that software is unwelcome — it is a signal that almost nobody is competing for that capital, and that generalist digital-health investors are not looking at this specialty.

~0.3% of sector capital reached software Market Scope · Tracxn

Supply

The bottleneck is clinician minutes

Cataract and uncorrected refractive error remain the leading global causes of blindness — both fully solvable, both throttled by surgical and examination capacity rather than by science. Anything that converts specialist time into throughput has a real, durable buyer.

Leading blindness causes are capacity problems WHO · workforce

Idea log

Ideas under evaluation

This section grows. Each idea analysed gets an entry with its thesis, the wedge, what would have to be true, and the honest objection.

OPENING Three gaps the data points at

Not proposals — just the three places where the landscape data contradicts itself, which is usually where a business is. Bring me an idea and it gets logged below this.

1. The adoption layer, not the algorithm. Autonomous retinal AI is solved, cleared and billable, and reaches almost nobody. The unbuilt product is whatever converts a cleared algorithm into a screening event inside a primary-care, pharmacy or endocrinology workflow — capture quality, staff time, referral routing, and the billing itself.

2. Oculomics without the payer problem. Retina-as-systemic-biomarker has strong science and no reimbursement. That combination usually means the first buyer is not a payer at all — life insurance, employers, pharma trial enrichment, or health systems with capitated risk.

3. Capacity, not diagnosis. The leading causes of global blindness are capacity-limited, not knowledge-limited. Anything that multiplies scarce ophthalmologist minutes — triage, pre-op, post-op follow-up, surgical throughput — sells into a demonstrable shortage.

Awaiting first idea. Send one and it gets analysed and logged here as IDEA 01 — thesis, wedge, market shape, what must be true, and the strongest objection against it.

Method

How to read this

Funding totals come from Market Scope and Tracxn, which disagree because they count differently — Tracxn tracks equity rounds only, Market Scope includes public offerings and debt. Where they conflict, both are shown. 2026 is a partial year and is marked as such; do not read the drop as a trend yet. Every figure on this page carries an inline source link; hover-tap the small superscript-style links to go straight to the primary source.

Scorecard values are editorial judgements about entrant conditions, not measured quantities. They exist to be argued with, and they will change as ideas get tested against them.

Company profiles live at companies/index.html — one page per company with a description, funding where disclosed, and links to the company website and LinkedIn. Sources are listed per claim.