Haplotype Labs

What do they actually do

Haplotype Labs builds HaploHub, a SaaS platform for organizations to store and manage population‑scale genotype data, run standard genetics pipelines (phasing, imputation, IBD) without custom code, and apply polygenic risk models to cohorts or individual patients. It accepts data from common lab technologies, including microarrays, short‑read sequencing, and methylation assays [homepage] [YC page].(https://www.haplotypelabs.com/)(https://www.ycombinator.com/companies/haplotype-labs)

Customers upload or connect their lab pipelines, run analyses via a UI or APIs, and score patients with published or private models (the company says it supports 4,000+ published models). Results are stored in HaploHub for downstream use like clinical reporting, cohort stratification, or prevention workflows [YC page] [homepage].(https://www.ycombinator.com/companies/haplotype-labs)(https://www.haplotypelabs.com/)

The company is early‑stage (YC Winter 2024) with a small team and active hiring. Public materials emphasize the platform and target customers but do not include named customer case studies or outcome metrics, so the product should be considered in‑market/early access rather than broadly deployed at scale [YC page] [WorkAtAStartup] [LinkedIn].(https://www.ycombinator.com/companies/haplotype-labs)(https://www.workatastartup.com/companies/29484)(https://www.linkedin.com/company/haplotype-labs)

Who are their target customer(s)

• Genetic testing labs: Need to offer new genetic risk reports without building and maintaining complex analysis pipelines, and to cut per‑sample costs to stay competitive. They want a managed way to run standard workflows and, where possible, shift to lower‑cost sequencing options [homepage] [YC page].
• Concierge / prevention‑focused medical practices: Want to use genetic risk to guide prevention but lack engineering/analytics teams to process raw data and compare models. They need reliable, secure results they can act on in care, rather than bespoke research code [homepage] [YC page].
• Clinical‑trial operations / sponsors: Need simple, auditable ways to genotype and stratify participants for enrollment or subgroup analysis, without long pipeline validation cycles. Logistics and cost of generating usable genetic data at scale are ongoing hurdles [homepage] [YC page].
• Consumer genetics product teams (DTC/wellness): Want to add validated polygenic‑risk features quickly without building or hosting backend pipelines (phasing, imputation, scoring). Need to run many published models and keep results secure for customers [homepage] [YC page].
• Payers and healthcare providers: Want to identify high‑risk people for prevention programs but lack easy, standards‑based ways to ingest and act on genetic risk scores while meeting privacy/compliance needs. They need reproducible, population‑level analytics tied to operational workflows [homepage] [YC page].

How would they acquire their first 10, 50, and 100 customers

• First 10: Run 6–12 week, paid or low‑cost pilots with a handful of regional genetic labs and concierge prevention clinics to validate workflows and quantify cost savings; use founder outreach and YC network to secure pilot contracts and referenceable results [YC page].
• First 50: Convert early pilots into case studies and scale through two repeatable channels: lab partnerships (integration + potential revenue share) and CRO/clinical‑trial relationships (turnkey genotyping + stratification). Package onboarding (API connectors, compliance checklist, SLAs) and run targeted outreach/webinars using pilot outcomes as the primary asset [YC page] [homepage].
• First 100: Formalize channel partnerships with a sequencing provider and lab‑automation vendors, publish benchmarked model comparisons and a security/compliance pack, and hire a small BD/sales team for enterprise and mid‑market motions. Add self‑serve for consumer‑genetics teams and attend focused clinical‑genetics/trial‑ops conferences to drive inbound [WorkAtAStartup] [homepage].

What is the rough total addressable market

Top-down context:

Across adjacent markets Haplotype touches (genetic testing, clinical genomics, DTC testing, and genomics data analysis), public estimates sum to roughly USD 30–40B annually, noting overlap and double counting [Grand View Research] [GM Insights] [CoherentMI] [Nova One/GlobeNewswire].(https://www.grandviewresearch.com/industry-analysis/genetic-testing-market-report)(https://www.gminsights.com/industry-analysis/direct-to-consumer-dtc-genetic-testing-market)(https://www.coherentmarketinsights.com/industry-reports/clinical-genomics-market)(https://www.globenewswire.com/news-release/2025/10/31/3178133/0/en/Genomics-Data-Analysis-Market-Size-to-Surpass-USD-28-74-Bn-by-2034.html)

Bottom-up calculation:

A practical proxy for HaploHub is the genomics data‑analysis/software slice, which recent reports place in the high single‑digit to low‑teens of billions (roughly USD 7–13B). Adding only the software/analysis portions of DTC (~USD 4B) and clinical genomics (~USD 12B) budgets as an upper bound suggests a conservative TAM of ~USD 7–10B and an upper ceiling in the USD 30–40B range, with overlap caveats [Nova One/GlobeNewswire] [GM Insights] [CoherentMI].(https://www.globenewswire.com/news-release/2025/10/31/3178133/0/en/Genomics-Data-Analysis-Market-Size-to-Surpass-USD-28-74-Bn-by-2034.html)(https://www.gminsights.com/industry-analysis/direct-to-consumer-dtc-genetic-testing-market)(https://www.coherentmarketinsights.com/industry-reports/clinical-genomics-market)

Assumptions:

• Only a fraction of total testing/clinical budgets is spent on software, managed analysis, and reporting relevant to HaploHub.
• Adoption of PRS and population‑scale analytics continues to expand across labs, clinics, trials, and DTC over the next few years.
• Market reports overlap categories; figures are used directionally, with data‑analysis/software as the main TAM proxy.

Who are some of their notable competitors

• Genomics plc / Mystra: Commercial human‑genetics platform and polygenic‑risk products sold to healthcare systems, insurers, and pharma; bundles large curated datasets, risk models, and services for population health and drug development, overlapping with Haplotype’s target payers/providers and trial customers [newsroom/Mystra].(https://www.genomics.com/newsroom/genomics-mystra-ai-enabled-human-genetics-platform)
• Allelica: Clinic‑grade PRS specialist offering validated testing and lab partnerships (including CLIA capability), serving providers and labs that want turnkey risk reports rather than hosting pipelines themselves [Allelica].(https://www.allelica.com/)
• DNAnexus: Enterprise cloud platform for secure storage, pipeline execution, and audit‑ready analysis used by labs, biobanks, and pharma; directly overlaps on population‑scale data management and standardized genetics workflows [DNAnexus population genomics].(https://www.dnanexus.com/use-cases/population-genomics)
• SOPHiA GENETICS (SOPHiA DDM): Commercial SaaS for diagnostic labs to standardize and certify genomic analyses and reports; competes where buyers need validated, regulatory‑focused workflows and data governance [SOPHiA DDM].(https://www.sophiagenetics.com/sophia-ddm/)
• Lifebit: Cloud/federated genomics platform with managed pipelines (including imputation/PRS), data lakehouse and federation features for population genomics and trials; targets organizations wanting turnkey pipeline hosting and governance across sites [Lifebit].(https://lifebit.ai/)