Already used by 100+ labs, the Kitchener-Waterloo company helps life sciences teams automate digital lab work, manage millions of samples, and keep lab operations traceable.

这家位于基奇纳-滑铁卢的公司已被100多家实验室采用，帮助生命科学团队自动化数字实验室工作、管理数百万份样本，并确保实验室操作的可追溯性。

KITCHENER-WATERLOO, ON

安大略省基奇纳-滑铁卢

,

，

June 4, 2026

/PRNewswire/ -

/美通社/ -

Scispot

Scispot

, the Canadian company behind the AI-native operating layer for modern labs, today announced an $8 million USD Series A led by Avenue Growth Partners, a Washington, DC-based investment firm.

，这家为现代实验室提供AI原生操作层的加拿大公司今天宣布完成800万美元的A轮融资，由总部位于华盛顿特区的投资公司Avenue Growth Partners领投。

Scispot is already used by 100+ labs across biotech, pharma, diagnostics, genomics, CRO/CDMO, bioproduction, biobanking, and testing workflows. The company supports 250+ instrument types, 1000+ experiments per month, and millions of samples across high-throughput labs.

Scispot 已被生物技术、制药、诊断、基因组学、CRO/CDMO、生物生产、生物样本库和检测工作流程中的 100 多家实验室采用。该公司支持 250 多种仪器类型，每月处理 1000 多次实验，并在高通量实验室中管理数百万份样本。

Modern labs are under pressure to move faster, but much of their work is still split across disconnected instruments, spreadsheets, electronic lab notebooks, lab information management systems, scientific data systems, reports, dashboards, and manual handoffs. That creates a coordination gap. Teams spend time moving data, checking context, reconciling results, building reports, and making sure work can be traced.

现代实验室面临着加快进度的压力，但其大部分工作仍然分散在相互孤立的仪器、电子表格、电子实验记录本、实验室信息管理系统、科学数据系统、报告、仪表板以及人工交接环节中。这造成了协调上的缺口。团队不得不花费大量时间搬运数据、核对背景信息、整合结果、编制报告，并确保工作可追溯。

This slows experiments, decisions, and the path from lab work to real-world use..

这减缓了实验、决策以及从实验室研究到实际应用的过程。

Scispot gives labs one operating layer for that work. Permissions, audit trails, sample lineage, approvals, and human review are built in. The platform captures context as work happens, traces each step, automates routine digital work, and turns lab activity into structured, traceable data that teams and AI agents can use..

Scispot 为实验室提供统一的操作层，以支持相关工作。该平台内置权限管理、审计追踪、样本谱系、审批流程以及人工审核功能。它能够在工作的同时捕获上下文信息，追踪每一步操作，自动化常规数字任务，并将实验室活动转化为结构化的、可追溯的数据，供团队和 AI 智能体使用。

The same operating layer also matters as AI moves deeper into life sciences. For model builders, hyperscalers, and AI infrastructure providers, the hard problem in life sciences is not only compute or model access. It is access to a real-world lab context with built-in controls: sample lineage, instrument runs, protocol state, approvals, data provenance, exceptions, and human review.

随着人工智能深入生命科学领域，相同的操作层也变得至关重要。对于模型构建者、超大规模云服务提供商和人工智能基础设施供应商而言，生命科学领域的难题不仅在于算力或模型访问，更在于获取具备内置控制功能的真实实验室环境上下文，包括样本谱系、仪器运行记录、协议状态、审批流程、数据出处、异常处理以及人工审核。

Scispot provides a model-agnostic context layer for labs, without forcing teams to lose control of their data or workflows..

Scispot 为实验室提供一个与模型无关的上下文层，无需迫使团队放弃对其数据或工作流的控制。

'Future labs will not run on people stitching together instruments, spreadsheets, reports, and approval steps,' said Guru Singh, founder and CEO of Scispot.  'They will run on an operating layer that connects every sample, instrument run, workflow, result, approval, and decision as the work happens.

“未来的实验室不会依靠人们将仪器、电子表格、报告和审批步骤拼凑在一起来运作，”Scispot 的创始人兼首席执行官 Guru Singh 表示。“它们将运行在一个操作层上，该层在工作进行时连接每一个样本、仪器运行、工作流程、结果、审批和决策。”

Scispot has built that layer, so scientists stay in control while routine digital work runs in the background.'.

Scispot 已构建起这一层，使科学家能够在常规数字化工作在后台运行时始终保持掌控。

For regulated and sample-heavy labs, speed cannot come at the expense of traceability or control. Teams need permissions, audit trails, sample lineage, instrument context, and human review built into the workflow. Scispot helps those pieces work together, so labs can automate more digital work while keeping scientists and lab operators in control..

对于受监管且样本量大的实验室，速度的提升不能以牺牲可追溯性或控制为代价。团队需要将权限管理、审计追踪、样本谱系、仪器上下文以及人工审核集成到工作流程中。Scispot 帮助这些组件协同工作，使实验室能够在保持科学家和实验操作人员控制权的同时，自动化更多的数字工作。

'The life sciences AI stack needs more than compute and models,' said Brian Goldsmith, Founding Partner at Avenue Growth Partners. 'It needs an execution layer that turns physical lab work into structured, traceable context. Scispot gives labs that layer, so AI agents can support real lab work with traceability and control.'.

“生命科学人工智能技术栈需要的不仅仅是算力和模型，”Avenue Growth Partners 的创始合伙人布莱恩·戈德史密斯表示，“它需要一个执行层，将物理实验室工作转化为结构化、可追溯的上下文。Scispot 为实验室提供了这一层，从而使人工智能代理能够在具备可追溯性和控制力的前提下支持实际的实验室工作。”

Scispot's long-term vision is the self-driving lab: a lab where routine coordination, data capture, analysis, and reporting run automatically on an operating layer built for traceability, human review, and control. Scientists and lab operators retain control over judgment, review, validation, and sign-off..

Scispot 的长期愿景是实现“自动驾驶实验室”：在这种实验室中，日常协调、数据采集、分析和报告均在专为可追溯性、人工审核与控制而构建的操作层上自动运行。科学家和实验室操作人员保留对判断、审核、验证及最终确认的控制权。

Scispot is headquartered in Kitchener-Waterloo, Ontario, and is building global life sciences infrastructure from Canada. The company will use the round to grow its product, engineering, AI, implementation, and customer success teams, with a focus on adding high-skill roles in Canada while supporting life sciences customers across North America and globally..

Scispot 总部位于安大略省基奇纳-滑铁卢，正从加拿大打造全球生命科学基础设施。公司将利用本轮融资扩大其产品、工程、人工智能、实施和客户成功团队，重点在加拿大增设高技能岗位，同时为北美及全球的生命科学客户提供支持。

'We are proud to build Scispot in Canada, with our roots in Kitchener-Waterloo,' Singh added. 'This is Canadian-developed life sciences software for labs around the world. This round helps us add high-skill jobs across Canada while supporting teams working on medicines, diagnostics, genomics, biomanufacturing, and scientific testing.'.

“我们自豪地在加拿大打造 Scispot，我们的根基扎根于基奇纳-滑铁卢地区，”辛格补充道。“这是为全球实验室开发的加拿大本土生命科学软件。本轮融资有助于我们在加拿大各地增加高技能就业岗位，同时支持致力于药物、诊断、基因组学、生物制造和科学检测的团队。”

Scispot's media kit, including the announcement video, logo, and founder photos, is available

Scispot 的媒体资料包（包括公告视频、标志和创始人照片）现已提供

here.

这里。

About Scispot

关于 Scispot

Scispot is the AI-native operating layer for self-driving labs. The Canadian-headquartered company helps biotech, diagnostics, pharma, CRO/CDMO, bioproduction, biobanking, and testing teams coordinate lab execution as work happens across instruments, samples, workflows, approvals, data, and AI agents.

Scispot 是面向自动驾驶实验室的 AI 原生操作层。这家总部位于加拿大的公司帮助生物技术、诊断、制药、CRO/CDMO、生物生产、生物样本库和测试团队在仪器、样品、工作流、审批、数据和 AI 代理之间协调实验室执行。

Life sciences teams use Scispot to replace manual handoffs with connected, traceable operations, so they can run experiments, manage samples, review results, and generate reports with less manual coordination. For more information, visit .

生命科学团队使用 Scispot 以互联、可追溯的操作取代人工交接，从而减少人工协调，更高效地进行实验、管理样本、审查结果并生成报告。更多信息，请访问 。

www.scispot.com

www.scispot.com

.

。

About Avenue Growth Partners

关于 Avenue Growth Partners

Avenue Growth Partners is an early growth equity firm backing exceptional founders building category-defining vertical technology companies. The firm partners closely with management teams to help scale durable, category-winning businesses.

Avenue Growth Partners 是一家早期成长型股权投资公司，致力于支持那些打造定义行业垂直领域科技公司的杰出创始人。该公司与管理团队紧密合作，助力企业规模化发展，构建持久且具备行业领先地位的业务。

Learn more at

了解更多，请访问

www.avenuegp.com

www.avenuegp.com

.

。

SOURCE Scispot

来源：Scispot

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