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Scispot Raises $8M Series A to Help Life Sciences Labs Move Faster

Today, we announced Scispot’s $8 million USD Series A, led by Avenue Growth Partners, a Washington, DC-based investment firm.

Scispot is the Canadian company behind the AI-native operating layer for modern labs. We help life sciences teams automate digital lab work, manage millions of samples, and keep lab operations traceable.

Scispot is already used by 100+ labs across biotech, pharma, diagnostics, genomics, CRO/CDMO, bioproduction, biobanking, and testing workflows. The platform supports 250+ instrument types, 1,000+ experiments per month, and millions of samples across high-throughput labs.

The Challenge: The Coordination Gap

Modern labs are under pressure to move faster. But much of their work still runs 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 proving work can be traced. This slows experiments, decisions, and the path from lab work to real-world use.

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The Solution: An Operating Layer for Labs

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.

The same operating layer matters more as AI moves deeper into life sciences.

For model builders, hyperscalers, and AI infrastructure providers, the hard problem in life sciences goes beyond compute and model access. AI systems need real lab context with controls built in: sample lineage, instrument runs, protocol state, approvals, data provenance, exceptions, and human review.

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

Redefining the Future Lab Workflow

Future labs should not depend on people stitching together instruments, spreadsheets, reports, and approval steps. They need an operating layer that connects every sample, instrument run, workflow, result, approval, and decision as the work happens.

That is what we have built with Scispot.

Scientists stay in control while routine digital work runs in the background.

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.

“The life sciences AI stack needs more than compute and models. 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.”

— Brian Goldsmith, Founding Partner at Avenue Growth Partners

The Long-Term Vision: The Self-Driving Lab

Our 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 still make the calls. They keep control over judgment, review, validation, and sign-off. The digital work around the science becomes more automatic.

Growth and Global Impact

We are proud to build Scispot in Canada, with our roots in Kitchener-Waterloo.

This is Canadian-developed life sciences software for labs around the world. This round helps us grow our product, engineering, AI, implementation, and customer success teams, with a focus on adding high-skill roles across Canada while supporting life sciences customers across North America and globally.

We are grateful to our customers, team, investors, and partners who helped us reach this point.

This round helps us support more teams working on medicines, diagnostics, genomics, biomanufacturing, and scientific testing.

Modern labs need more than another place to store data. They need an operating layer that coordinates the work of the lab as it happens.

That is what we are building at Scispot.