Native Labs
AI-enabled quality and manufacturing platform for cell and gene therapies, unifying data and automating processes.
Website: http://www.nativelabs.ai
Cover Block
From the public record
| Field | Value |
|---|---|
| Company | Native Labs |
| Tagline | AI-enabled quality and manufacturing platform for cell and gene therapies, unifying data and automating processes. |
| Headquarters | Ilford, United Kingdom [Science Creates, October 2026] |
| Stage | Pre-seed [FundedIQ, July 2026] |
| Business model | SaaS |
| Industry | Deeptech |
| Technology | AI / Machine Learning |
| Geography | Western Europe |
| Growth profile | Venture Scale |
| Founding team | Co-Founders (2), Louis Brookstein and Arya Shabani [LinkedIn, Retrieved 2026] |
| Funding label | Pre-seed |
| Total disclosed | ~$200,000 [FundedIQ, July 2026] |
Links
From the public record
- LinkedIn: https://www.linkedin.com/pulse/native-labs-closes-pre-seed-round-advance-ai-platform-brookstein-6yvje
- Science Creates: https://www.sciencecreates.co.uk/companies/native-labs
The Short Version
PUBLIC Native Labs is building an AI-enabled quality and manufacturing software platform for cell and gene therapy production, a narrow but consequential problem set that has begun to attract investor attention because manufacturing reliability remains a persistent constraint in advanced therapies [LinkedIn, May 2025] [Science Creates, October 2026]. The company is early, but the May 2025 pre-seed announcement gives it a clear public timestamp: Native Labs said it would use the financing to deploy its platform into cell and gene therapy manufacturing sites and process-development labs while continuing product development [LinkedIn, May 2025].
The founding story, as described in the company's own announcement, rests on firsthand exposure to bioprocessing pain points rather than a generic software thesis; CEO and co-founder Louis Brookstein said his experience in CAR-T and induced-pluripotent-stem-cell manufacturing shaped the need for better data-driven process and quality infrastructure [LinkedIn, May 2025]. Public materials describe the product as a "Next-Generation Quality Operating System for Drug Manufacturing" that aims to unify manufacturing data, automate quality workflows, and predict issues, with Science Creates separately characterizing the underlying approach as using neural-network models for prediction, process control, and real-time quality verification [LinkedIn, May 2025] [Science Creates, October 2026].
That framing matters because the differentiation, if it holds, appears to rest less on a general AI layer and more on fitting machine learning into regulated, high-variability biomanufacturing workflows already used by therapy developers, manufacturers, and process-development laboratories [LinkedIn, May 2025] [Science Creates, October 2026]. The public record also points to a technically relevant founding pair: Brookstein is identified as founder and CEO, while Arya Shabani is identified across LinkedIn and Science Creates as co-founder and CTO; Shabani's background spans robotics, AI, and biomanufacturing, including prior work tied to patented bioprinting technology [LinkedIn, Retrieved 2026] [Science Creates, October 2026] [Institut de Robòtica i Informàtica Industrial, Retrieved 2026].
On capitalization, the clearest public fact is a Zinc VC-led pre-seed round announced in May 2025, while FundedIQ reports the amount at $200,000; that figure should be treated as a secondary database claim rather than a company-disclosed number [LinkedIn, May 2025] [FundedIQ, July 2026]. The business model is described in the structured research as SaaS, which is directionally consistent with the company's positioning as a quality and manufacturing platform, though public evidence on pricing, pilots, and conversion remains thin [FundedIQ, July 2026]. Over the next 12 to 18 months, the central watchpoints are straightforward: whether early adopter work converts into named deployments or referenceable customers, whether the product can show measurable manufacturing or quality gains in production settings, and whether the company can raise beyond pre-seed on more than technical promise [LinkedIn, May 2025] [Science Creates, October 2026].
Single-source, plausible -- This section relies on one company announcement, one accelerator profile, and founder profile sources; the funding amount and several product details remain only partially corroborated.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Pre-Seed |
| Business Model | SaaS |
| Industry / Vertical | Deeptech |
| Technology Type | AI / Machine Learning |
| Geography | Western Europe |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (2) |
| Funding | Pre-seed, total disclosed about $200,000 [FundedIQ, July 2026] |
The Company in Brief
PUBLIC
The public record on Native Labs is still thin, but a few points are clear. Crunchbase identifies the company as Native Labs, based in Ilford, United Kingdom, while the Science Creates company profile places it within that Bristol-linked startup ecosystem and describes its focus as industrialising cell and gene therapies with AI-enabled software [Crunchbase] [Science Creates, October 2026].
Chronology is limited and should be read conservatively. The earliest clearly attributable milestone in the available company-level record is participation in the inaugural Science Creates accelerator, which the company later referenced alongside prior support including an Innovate UK grant and laboratory access at Stevenage Bioscience Catalyst [LinkedIn, May 2025] [Science Creates, October 2026]. In May 2025, Native Labs announced a pre-seed equity round led by Zinc VC to support platform deployment into cell- and gene-therapy manufacturing environments and continued product development, and secondary funding databases later recorded that round at $200,000 [LinkedIn, May 2025] [Crunchbase] [FundedIQ, July 2026].
Founding details remain partially corroborated rather than fully filed out. LinkedIn profiles identify Louis Brookstein as founder and Arya Shabani as co-founder and CTO of Native Labs, while Science Creates lists Brookstein as CEO and Shabani as CTO, which is directionally consistent on leadership even where a formal incorporation timeline is not evident in the cited public sources [LinkedIn, Retrieved 2026] [LinkedIn, Retrieved 2026] [Science Creates, October 2026].
Single-source, plausible -- Confirmed in part by Crunchbase, Science Creates, and founder LinkedIn profiles; chronology and funding amount rely partly on company announcement and secondary database reporting.
What They Have Built
Product Scope
MIXED The public record is still narrow, but the product direction is consistent across the few attributable sources that mention it. Native Labs describes itself as building an AI-enabled quality and manufacturing platform for cell and gene therapies, aimed at developers, manufacturers, and process-development labs [LinkedIn, May 2025]. In the company announcement tied to its pre-seed financing, the platform was positioned as a system to deploy into manufacturing sites and lab environments, with an emphasis on using historical datasets and co-developing tailored AI solutions with partners [LinkedIn, May 2025].
Science Creates adds one useful layer of specificity: it characterizes the product as applying neural-network models to prediction, process control, and real-time quality verification for bioprocessing environments [Science Creates, October 2026]. That said, several of the more detailed workflow claims, including unified manufacturing data, automated quality processes, issue prediction, and integration into existing workflows, are presently supported only by company-linked descriptions summarized in the available research rather than by an independent product demo or third-party case study [LinkedIn, May 2025].
Technical Positioning
MIXED In plain terms, the company appears to be selling software that sits close to the operational bottleneck in advanced-therapy manufacturing, where process variability, fragmented data, and quality review can slow scale-up [LinkedIn, May 2025]. The technical thesis is plausible: if Native Labs can combine process data, workflow automation, and model-based quality checks inside regulated manufacturing settings, it would be addressing a costly point of failure in cell and gene therapy production [Science Creates, October 2026].
What remains less settled is product maturity. There is no verified public demo, no named customer deployment, and no disclosed technical stack in the materials reviewed here [LinkedIn, May 2025]. The evidence supports an early platform with a defined use case and credible scientific framing, but not yet a fully evidenced claim of production-scale adoption or validated performance in live commercial manufacturing.
Unconfirmed -- Core product claims rely primarily on company announcement language, with partial corroboration from a Science Creates profile.
Market Size and Demand
From the public record This market matters because cell and gene therapy manufacturing remains data-heavy, compliance-bound, and operationally fragile, which creates room for software that can reduce quality delays and process variability if it can fit into existing GMP environments [LinkedIn, May 2025] [Science Creates, October 2026].
The evidence base on market size is thin for Native Labs specifically, so the cleanest way to frame demand is through analogous public markets rather than company-level extrapolation. Public materials place Native Labs in cell and gene therapy manufacturing software and quality operations for advanced therapies [LinkedIn, May 2025] [Science Creates, October 2026]. None of the captured sources cite a named third-party TAM, SAM, or SOM study for that niche, and no disclosed customer count or deployment footprint allows a bottoms-up estimate. That leaves the market case resting on a narrower but still plausible proposition: advanced-therapy manufacturers have unusually high process complexity, fragmented data, and consequential quality risk, which are precisely the workflow problems Native Labs says it is addressing [LinkedIn, May 2025] [Science Creates, October 2026].
Demand drivers are more visible than market sizing. Native Labs' own May 2025 financing announcement said the product is being deployed toward cell- and gene-therapy manufacturing sites and process-development laboratories, and that the company was working with early adopters and inviting beta testers at that stage [LinkedIn, May 2025]. Science Creates separately describes the company as building AI systems for the industrialisation of cell and gene therapies, and characterizes the underlying approach as neural-network-based prediction, process control, and real-time quality verification [Science Creates, October 2026]. Read conservatively, the tailwind is not generic AI adoption. It is the push to make advanced therapy production more repeatable, better documented, and easier to monitor across development and manufacturing handoffs.
The adjacent markets are broader than the initial wedge. Science Creates says the platform's methods may extend beyond regenerative medicine into cultivated protein, which suggests the underlying architecture could map onto other biologics or novel bioprocessing environments if the company proves fit in its first use case [Science Creates, October 2026]. The substitutes are also straightforward: manufacturers can continue using a mix of MES, LIMS, QMS, spreadsheets, internal data engineering, and services-heavy process optimization rather than adopting a unified software layer. That substitution risk matters because it means Native Labs is not only selling a new product, it is asking regulated operators to consolidate workflows that often sit across several incumbent systems.
Regulatory and macro forces support the problem definition, even if the current public record does not quantify the category. Cell and gene therapy manufacturing sits in a compliance-sensitive setting where documentation quality, process reproducibility, and deviation management carry direct operational and regulatory consequences, which raises the value of software that can organize data and flag issues earlier [LinkedIn, May 2025] [Science Creates, October 2026]. At the same time, buyers in this environment typically move carefully. That implies a market that can be meaningful if adoption lands, but one where validation cycles, system integration, and evidence thresholds are likely to shape pace more than headline AI enthusiasm.
| Market lens | Public evidence | What it suggests |
|---|---|---|
| Core wedge | Cell and gene therapy manufacturing and process-development labs [LinkedIn, May 2025] | Initial demand likely comes from specialized advanced-therapy operators rather than general manufacturing software buyers |
| Functional need | Manufacturing data unification, quality-process automation, issue prediction [LinkedIn, May 2025] | Spend case is tied to quality and operational efficiency, not stand-alone analytics |
| Adjacent expansion | Potential applications from regenerative medicine to cultivated protein [Science Creates, October 2026] | Longer-term expansion may exist if the platform proves transferable across bioprocessing settings |
| Buying constraint | Existing workflow integration is part of the product claim [LinkedIn, May 2025] | Adoption likely depends on fitting around incumbent GMP systems rather than replacing them outright |
The table points to a market with clear operational pain but a still-unproven budget owner and adoption path in the public record. For now, the investable question is less total category size than whether Native Labs can convert a narrow, high-need advanced-therapy workflow into repeatable software demand.
Single-source, plausible -- Based primarily on the company's May 2025 LinkedIn announcement and the Science Creates company profile, with no named third-party market sizing report in the captured sources.
Who Else Is Fighting for This
MIXED Native Labs appears to be positioning itself between traditional manufacturing execution and quality software on one side, and newer AI-first bioprocessing tools on the other, with a narrow focus on cell and gene therapy manufacturing workflows rather than general life-sciences software [LinkedIn, May 2025] [Science Creates, October 2026].
The public record is thin on named direct competitors, which matters in itself. Native Labs describes a platform that unifies manufacturing data, automates quality processes, and applies neural-network models to prediction, process control, and real-time quality verification in cell and gene therapy settings [LinkedIn, May 2025] [Science Creates, October 2026]. That places it in a segment usually occupied by a mix of established quality management systems, manufacturing data historians, manufacturing execution systems, and process development software vendors, but the available sources do not identify which vendors the company most often displaces or integrates with [LinkedIn, May 2025] [Science Creates, October 2026].
That ambiguity cuts both ways. On the favorable reading, Native Labs may be entering a market gap where advanced-therapy manufacturers still rely on fragmented workflows and have not yet settled on a category leader for AI-assisted quality operations [LinkedIn, May 2025]. On the less favorable reading, the company is competing against a diffuse set of incumbents that already control the system of record, the validation burden, and the customer relationship, which can make a wedge product harder to land unless it solves a very specific pain point inside process development or batch release [Science Creates, October 2026] [FundedIQ, July 2026].
The clearest edge visible today is domain focus rather than scale. Louis Brookstein is identified as founder and CEO, and public materials tie him to CAR-T and induced-pluripotent-stem-cell manufacturing experience, while Arya Shabani is identified as co-founder and CTO with a background spanning robotics, AI, and biomanufacturing [LinkedIn, Retrieved 2026] [LinkedIn, Retrieved 2026] [LinkedIn, May 2025]. For an early company, that combination is relevant because cell and gene therapy manufacturing has enough process complexity and quality sensitivity that buyers may prefer specialist tools over horizontal AI software. Still, this edge is perishable unless Native Labs can convert early adopter work into proprietary workflow data, validated deployment references, or deep integrations that make replacement costly [LinkedIn, May 2025].
The main exposure is distribution and proof. Native Labs said in May 2025 that it was working with early adopters and inviting beta testers, but the available sources do not name commercial customers, deployment scale, or recurring usage metrics [LinkedIn, May 2025]. In practical terms, that leaves the company vulnerable to incumbent quality and manufacturing software providers that already sell into regulated biopharma accounts, even if those vendors are less specialized in advanced therapies. It also leaves Native Labs exposed to adjacent AI tooling vendors that can pitch analytics on top of existing infrastructure without asking manufacturers to change validated core workflows [Science Creates, October 2026].
The most plausible competitive picture over the next 18 months is a sorting process rather than a winner-take-all outcome. Native Labs is the most visible named contender in the supplied record, but only because the sourced material is company-centered and does not name alternatives [LinkedIn, May 2025] [Science Creates, October 2026]. If specialized cell and gene therapy manufacturers prove willing to adopt a standalone quality operating layer, Native Labs could emerge as a winner if it turns beta engagements into referenceable deployments and captures unique production data. If buyers instead prefer to extend incumbent systems with lighter AI modules, Native Labs is the likely loser if validation cycles run long and the product remains an overlay rather than part of the operational core [LinkedIn, May 2025] [FundedIQ, July 2026].
Single-source, plausible -- Relies on two public sources for Native Labs positioning and team context, but the section lacks independently named direct competitors in the supplied record and therefore uses category-level analysis rather than company-by-company corroboration.
Opportunity
From the public record
If Native Labs executes, the prize is not a niche software tool but a control layer for one of the more operationally difficult corners of biomanufacturing: the systems that sit between experimental cell and gene therapy processes and repeatable, quality-managed production at scale [LinkedIn, May 2025] [Science Creates, October 2026].
The headline opportunity is to become the operating system that advanced-therapy teams use to run quality and manufacturing decisions before those workflows harden around incumbent tooling. That is still an early claim, and much of the product positioning remains company-described, but the direction is coherent across the available sources: Native Labs says it is building an AI-enabled platform that unifies manufacturing data, automates quality processes, and predicts issues for cell- and gene-therapy settings, while Science Creates separately describes neural-network models for prediction, process control, and real-time quality verification [LinkedIn, May 2025] [Science Creates, October 2026]. The reason that outcome looks reachable rather than purely aspirational is timing. The company has already closed a Zinc VC-led pre-seed round and publicly tied the use of funds to deployment into manufacturing sites and process-development labs, which suggests the initial wedge is anchored in real operating environments rather than a research-only concept [LinkedIn, May 2025] [FundedIQ, July 2026].
A few scale paths are visible from the public record, even if none is yet proven.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Quality system of record for advanced therapies | Native Labs becomes the software layer that cell and gene therapy teams use to unify manufacturing and quality data across development and production | Early adopter deployments convert into repeat usage inside manufacturing sites and process-development labs [LinkedIn, May 2025] | The company is already framing the product around those settings, and the May 2025 financing was explicitly linked to deployment there [LinkedIn, May 2025] |
| AI process-control wedge expands into broader bioprocessing | The platform starts in cell and gene therapy, then extends into adjacent biomanufacturing workflows that also need prediction and quality verification | Demonstrated value from neural-network-based prediction and process control in initial therapy use cases [Science Creates, October 2026] | Science Creates describes applications extending beyond regenerative medicine, which at least supports adjacency potential from the same technical stack [Science Creates, October 2026] |
| Ecosystem-backed standard workflow layer | Native Labs turns accelerator, grant, and biotech-campus relationships into a repeatable channel for pilot access and product validation | Support from Zinc VC, Science Creates, and earlier ecosystem backing helps open doors to more labs and developers [LinkedIn, May 2025] [Science Creates, October 2026] | The company had already participated in Science Creates and received other early support before announcing the pre-seed, giving it a credible route into a concentrated buyer set [LinkedIn, May 2025] |
The compounding mechanism here would be data and workflow entrenchment, if the early deployments hold. Native Labs is explicitly seeking partners that can contribute historical datasets and co-develop tailored AI solutions, and that matters because manufacturing software in regulated environments tends to improve as it learns from more process variation, more exception cases, and more quality events over time [LinkedIn, May 2025]. If the product is genuinely able to unify fragmented manufacturing data and embed into existing workflows, each successful deployment could make the models more useful, switching costs higher, and the next sale easier, especially in a field where process knowledge is difficult to standardize across teams [LinkedIn, May 2025] [Science Creates, October 2026]. The public evidence does not yet show named customers or reference accounts, so this flywheel should be treated as plausible rather than demonstrated [LinkedIn, May 2025].
The size of the win is harder to quantify from the available evidence because no sourced market-size study or close public comparable was provided in the record. Even so, the strategic endpoint is legible: if Native Labs became a trusted software and intelligence layer across advanced-therapy manufacturing, it could plausibly support venture-scale outcomes because it would sit inside a regulated, high-value workflow where quality failures are expensive and process reproducibility matters acutely [LinkedIn, May 2025] [Science Creates, October 2026]. A more concrete valuation frame needs external comparables or category TAM data that are not in the public source set here, so any numerical outcome would risk false precision. For now, the upside case is best understood as ownership of a narrow but consequential systems layer in cell and gene therapy manufacturing, with room to widen into adjacent bioprocessing if the first installations generate durable operational evidence [Science Creates, October 2026] [FundedIQ, July 2026].
Single-source, plausible -- This section relies on one independent public profile and one company announcement, with several material product claims still company-described rather than independently verified.
Sources
From the public record
[Science Creates, October 2026] Native Labs | https://www.sciencecreates.co.uk/companies/native-labs
[FundedIQ, July 2026] Native Labs Funding | https://fundediq.co/native-labs-nativelabs-ai-funding/
[LinkedIn, Retrieved 2026] Louis Brookstein - Founder of Native Labs | https://uk.linkedin.com/in/louis-brookstein-4b6147151
[LinkedIn, May 2025] Native Labs Closes Pre-Seed Round to Advance AI Platform Enabling the Industrialisation of Cell and Gene Therapies | https://www.linkedin.com/pulse/native-labs-closes-pre-seed-round-advance-ai-platform-brookstein-6yvje
[Institut de Robòtica i Informàtica Industrial, Retrieved 2026] Arya Shabani | https://www.iri.upc.edu/staff/ashabani
Articles about Native Labs
- Native Labs Wires AI Into the Quality Control Step for Cell Therapies — The UK startup’s platform aims to unify data and automate quality processes for advanced therapy developers, starting with early adopters.