This BenchSci company profile covers the company's valuation, revenue, funding rounds, investors and history. BenchSci works in artificial intelligence, with a focus on life sciences research software. It was founded in 2015 and is headquartered in Toronto, Ontario, Canada. Every figure links to a public source, and anything the company hasn't disclosed is marked as such.
Revenue
| Metric | Value | As of | Source |
|---|---|---|---|
| Total funding | About C$218 million (US$170 million) | May 2023 | BetaKit |
Funding history
| Date | Round | Amount | Valuation | Investors | Source |
|---|---|---|---|---|---|
| May 2023 | Series D | C$95M (about US$70M), all equity and all primary | Not disclosed (CEO declined to say) | Generation Investment Management (lead); Inovia Capital, TCV, Golden Ventures, F-Prime Capital | BetaKit |
BenchSci timeline
Key dates from the sources on this page, oldest first. Metric snapshots are listed after the funding events.
- 2015 — BenchSci is founded in Toronto by Liran Belenzon (CEO), with co-founders.
- May 2023 — Series D: C$95M (about US$70M), all equity and all primary, valuing the company at Not disclosed (CEO declined to say). Investors: Generation Investment Management (lead); Inovia Capital, TCV, Golden Ventures, F-Prime Capital.
- May 2023 — Total funding: About C$218 million (US$170 million).
Investors
Overview
BenchSci builds AI software for pharmaceutical and biotech research teams. Its platform helps scientists plan experiments more effectively by analysing huge amounts of published research and experimental data, for example to find which reagents and antibodies have worked for similar experiments, or to map the biological evidence connecting a target to a disease. The aim is to cut wasted experiments and speed up the path from early research to new medicines.
BenchSci was founded in Toronto in 2015. Liran Belenzon, a co-founder, is CEO. The company grew out of a simple observation: a large share of laboratory experiments fail or have to be repeated, often because researchers chose the wrong materials or missed evidence already in the scientific literature.
Why it matters
Drug development is slow and extraordinarily expensive. Much of the cost comes from failures: experiments that don't work and drug candidates that fail in later trials. Even modest improvements in early research decisions can save large amounts of time and money across a pharmaceutical company's pipeline.
The challenge is that the relevant knowledge is scattered across millions of papers, patents, databases and internal records, written in specialised language. That's a natural fit for machine learning systems that can read, extract and connect information at a scale no team of humans could manage.
Funding history
BenchSci's backers include some of Toronto's best-known venture firms and large international investors.
May 2023, Series D: C$95 million, about US$70 million, led by Generation Investment Management, with existing investors Inovia Capital, TCV, Golden Ventures and F-Prime Capital. The round was all equity and all primary, meaning all the money went to the company rather than to existing shareholders. It brought BenchSci's total funding to about C$218 million (US$170 million).
CEO Liran Belenzon declined to disclose the valuation, saying only that the company was "very happy" with the terms. Raising a primary round in May 2023, one of the toughest periods for venture funding in years, was itself a signal of investor confidence.
The investor list blends Canadian early-stage firms (Golden Ventures, Inovia), a large US growth investor (TCV), a life-sciences-focused investor connected to Fidelity (F-Prime) and a sustainability-focused investor (Generation). Generation also led AlayaCare's Series D, showing its interest in Canadian health-related technology.
Revenue: what's public
BenchSci hasn't published its revenue or valuation, and we haven't found reliable company-reported figures. It sells enterprise software subscriptions to pharmaceutical and biotech companies. Contracts with large pharmaceutical companies can be substantial, but the customer base is concentrated among a relatively small number of very large buyers, which is typical of software for drug discovery.
Competitive landscape
AI in drug discovery is a busy field. Some companies use AI to design new drug molecules themselves and develop their own pipelines. Others, like BenchSci, sell software and data platforms that help existing research organizations work better. Large pharmaceutical companies also build internal AI capabilities, and general-purpose AI models are increasingly used to read scientific literature. BenchSci's advantages are its focus on experimental planning and evidence, its years of curated biological data, and its relationships with large pharmaceutical customers.
A software model has a different risk profile from drug discovery itself. It doesn't depend on any single drug succeeding in clinical trials, and revenue can be recurring. On the other hand, it depends on research budgets and on persuading cautious scientific organizations to change how they work.
Selling to pharmaceutical companies
Enterprise sales in pharma are notoriously slow. Purchases often require approval from scientific, IT, security, legal and procurement teams, plus validation that the software produces reliable results. Pilots with specific research groups are common before company-wide deals. Once a platform is embedded in scientists' daily work, though, it tends to be sticky, and expansion across departments can drive strong net revenue retention.
What to watch next
Watch for new large pharmaceutical customers or expanded agreements, product launches that use the latest AI models, partnerships with research institutions, and any new funding or acquisition activity. Broader trends matter too: pharmaceutical R&D budgets and the industry's appetite for AI tools both shape demand. As generative AI becomes more capable at reading scientific literature, BenchSci's ability to show results beyond what general tools can do will be important.
Toronto's AI and life sciences strengths
BenchSci draws on two of Toronto's strengths: a deep AI research community and a large life sciences sector anchored by universities and research hospitals. It's one of several Toronto companies, alongside Cohere, that show how the city's AI talent is being applied commercially. Our guide to venture capital in Toronto covers the investors active in this space.
Key facts at a glance
BenchSci is a Toronto company founded in 2015 that makes AI software for pharmaceutical and biotech research. Its CEO is co-founder Liran Belenzon. In May 2023 it raised a C$95 million (US$70 million) Series D led by Generation Investment Management, with Inovia Capital, TCV, Golden Ventures and F-Prime Capital, bringing total funding to about C$218 million. It didn't disclose its valuation.
How research teams evaluate AI tools
Scientific organizations are cautious buyers, for good reason: a tool that points researchers in the wrong direction can waste months. When pharmaceutical and biotech teams evaluate AI research platforms, they typically look at:
- Traceability: can every suggestion be traced back to the paper, dataset or experiment it came from?
- Coverage: does the platform include the literature, data types and biological areas the team works in?
- Accuracy on known cases: does it reproduce answers the team already knows to be correct?
- Integration: does it connect with internal data and existing research tools?
- Security: how is confidential research data handled?
Vendors that can show measurable time or cost savings in a pilot usually move to broader deployment much faster than those relying on demonstrations alone.
Ask for references from research groups working on similar biology.
What this means if you're…
Selling to BenchSci: an AI company serving regulated enterprise customers buys machine learning infrastructure, data licensing, security and compliance certifications, and enterprise sales support.
A research organization: evaluate AI research tools with a pilot on a real project, measure time saved and experiments avoided, and check how results are sourced and validated.
A health or AI founder: BenchSci's investor mix shows the value of combining local early-stage backers with specialist and international growth investors as you scale.
Latest developments (October 2026)
BenchSci has cut staff twice as it reorganises around AI. In August 2025 it eliminated about 83 jobs, including a fifth of its engineering team, while adopting Google's generative AI tools, and in May 2026 it laid off roughly another 30% of staff, about 68 people, as it moved to AI agents, according to The Logic. The company has signed deals with Thermo Fisher Scientific, Merck and Sanofi. It has not announced new funding since its 2023 Series D.
Sources
Every figure on this page comes from the public sources below. Where sources disagreed, we used the company's own announcement or a primary news report. Private-company data changes; check the date beside each figure.
Frequently asked questions
What does BenchSci do?
BenchSci is a artificial intelligence / life sciences research software company headquartered in Toronto, Ontario, Canada. It was founded in 2015.
What is BenchSci's valuation?
BenchSci has not publicly disclosed a valuation in the sources we track.
How much revenue does BenchSci make?
BenchSci is a private company and has not publicly disclosed its revenue. Figures on third-party sites are usually modelled estimates rather than numbers reported by the company.
What was BenchSci's latest funding round?
The most recent financing we have verified is a series d in May 2023: C$95M (about US$70M), all equity and all primary, at a valuation of Not disclosed (CEO declined to say). Source: BetaKit.
Who are BenchSci's investors?
Investors named in public announcements include Generation Investment Management, Inovia Capital, TCV, Golden Ventures and F-Prime Capital.
Who founded BenchSci?
BenchSci was founded in 2015 by Liran Belenzon (CEO), with co-founders.
Is BenchSci a public company?
No. BenchSci is a private company (private, venture backed), so its shares are not traded on a stock exchange and it isn't required to publish its financial results.
Where is BenchSci headquartered?
BenchSci is headquartered in Toronto, Ontario, Canada. See our guide to raising money in Canada for context on the Toronto startup ecosystem.