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A scientist finishes a run on the plate reader, exports a CSV, drops it into a shared folder, updates a tracker in Excel, pastes a summary into the ELN, and pings a colleague on Slack to confirm the batch ID is right. Nothing in that chain is unusual. It is how a lot of modern labs still move work forward.

Each step takes only a few minutes. Add them up across instruments, samples, approvals, and reporting cycles, and you get a coordination tax that slows experiments, decisions, and the path from bench work to real-world use. Labs are under pressure to move faster. Much of their digital work is still split across disconnected tools and manual handoffs.

Today we are sharing a milestone that helps us address that gap at scale. Scispot has raised an $8 million USD Series A, led by Avenue Growth Partners, a Washington, DC-based investment firm. The round supports our work building the operating layer modern labs need: one place where permissions, audit trails, sample lineage, approvals, and human review work together as experiments run.

What labs told us before we raised

We did not set out to build another point tool. We started from a pattern we kept seeing in biotech, diagnostics, pharma, genomics, CRO and CDMO shops, bioproduction, biobanking, and testing labs.

Teams had instruments that worked. They had ELNs, LIMS modules, spreadsheets, dashboards, and reporting pipelines that mostly worked too. What did not work was the glue between them. Context got lost between systems. Sample lineage lived in one place, instrument runs in another, approvals in a third. When something needed review, someone had to reconstruct the story by hand.

Regulated and sample-heavy labs feel this most acutely. Speed cannot come at the expense of traceability or control. Scientists and operators need to know who did what, when, and on which sample - without spending half their week proving it. That is the problem Scispot was built to solve.

We heard it from QC leads preparing for audits, from process development teams scaling cell therapy workflows, and from diagnostics labs processing high sample volumes under tight turnaround windows. The science was not the bottleneck. The handoffs were.

One operating layer, not another silo

Scispot gives labs one operating layer for digital lab work. Permissions, audit trails, sample lineage, approvals, and human review are built in - not bolted on after the fact. The platform captures context as work happens, traces each step, automates routine digital coordination, and turns lab activity into structured, traceable data that teams and AI agents can use.

That matters because the work itself is complex. A high-throughput lab might juggle hundreds of instrument types, thousands of experiments per month, and millions of samples across workflows that span intake, processing, analysis, review, and reporting. When each transition is manual, errors compound and decisions wait on someone finding the right file or the right row in the right sheet.

When the operating layer is connected, the same work flows differently. An instrument run links to the sample it came from. A result update triggers the next approval step. A report pulls from live data instead of a stale export. Scientists stay in control of judgment, validation, and sign-off - while routine digital work runs in the background.

Today more than 100 labs use Scispot across the life sciences stack. The platform supports 250+ instrument types, 1,000+ experiments per month, and millions of samples in production environments. Those numbers reflect real operational load, not a pilot footprint. They also reflect a team that has spent years close to lab operators, not abstracting science into generic software categories.

Why this round, and why now

Series A is a scale milestone, not a starting gun. Scispot has been in market with customers who depend on the platform for daily work. This round lets us grow product, engineering, AI, implementation, and customer success with the same discipline those teams already expect from us in the lab.

We will add high-skill roles across Canada, with our roots in Kitchener-Waterloo, Ontario, while supporting life sciences customers across North America and globally. Canadian-developed life sciences infrastructure can compete on the world stage when it is built for how labs actually run - not how slide decks imagine they run.

Avenue Growth Partners led the round because they see the same structural shift we do. As Brian Goldsmith, Founding Partner at Avenue Growth Partners, put it: "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."

Lab context is the hard problem for AI in life sciences

AI is moving deeper into life sciences. Model builders, hyperscalers, and AI infrastructure providers have solved important pieces of the stack. But for labs, the hard problem is not only compute or model access. It is access to real-world lab context with built-in controls: sample lineage, instrument runs, protocol state, approvals, data provenance, exceptions, and human review.

Without that context layer, AI stays generic. With it, agents can support real work - finding the right batch, flagging an out-of-spec trend, preparing a report draft - while scientists retain control of data and workflows.

That is why we invested early in an API-first architecture and why we shipped an MCP server that lets AI clients act inside the workspace instead of outside it. The operating layer is not a wrapper around exports. It is where execution, permissions, and provenance already live.

Scispot provides a model-agnostic context layer for labs without forcing teams to lose control of their data or processes. That is the same design principle behind our API-first platform and our MCP server: extend what labs already trust, do not bypass it. AI should meet labs where execution already happens.

The long-term vision: the self-driving lab

Our long-term vision is the self-driving lab: a environment where routine coordination, data capture, analysis, and reporting run automatically on an operating layer built for traceability, human review, and control.

That does not mean removing scientists from the loop. It means removing the repetitive stitching - the exports, re-entries, status checks, and manual reconciliations - that keeps smart people doing work computers should handle. Judgment, review, validation, and sign-off stay human. The operating layer handles the connective tissue.

We are already seeing pieces of that vision in production. Labs automate intake and routing. Teams generate reports from live structured data instead of copy-paste assembly. Operators trace a sample from receipt through instrument runs and approvals in one system. Each deployment teaches us what to harden next.

As Guru Singh, our founder and CEO, said when we announced the round: "Future labs will not run on people stitching together instruments, spreadsheets, reports, and approval steps. They will run on an operating layer that connects every sample, instrument run, workflow, result, approval, and decision as the work happens. Scispot has built that layer, so scientists stay in control while routine digital work runs in the background."

Built in Canada, trusted by labs worldwide

Scispot is headquartered in Kitchener-Waterloo, Ontario. We are proud to build global life sciences infrastructure from Canada - software developed here, used by teams working on medicines, diagnostics, genomics, biomanufacturing, and scientific testing around the world.

This Series A helps us invest in the people and product depth those teams deserve: faster implementations, richer instrument connectivity, smarter automation, and customer success that understands regulated environments. We are hiring across product, engineering, AI, and customer-facing roles. If you want to work on software that sits at the intersection of science, operations, and AI - with a team that ships for real labs - we would like to hear from you.

What comes next

If you run a lab that is outgrowing spreadsheets and disconnected tools, or if you are rethinking how traceability and speed can coexist, this is the work we wake up to every day. The Series A accelerates it. It does not change the mission: give life sciences teams one operating layer so they can move faster without giving up control.

Book a demo to see how Scispot connects samples, instruments, workflows, and data in your environment. If you are a current customer, thank you - this milestone is yours as much as ours. If you are new to Scispot, we look forward to showing you what a connected lab feels like.‍

Learn more about Avenue Growth Partners at avenuegp.com.