How Unilever uses IPRally to streamline patent intelligence and bring R&D closer to IP
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Weekly competitor monitoring review assisted by IPRally AI classifiers
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AI classification workflow replaces manual patent alert review
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Attorneys handle patentability searches independently with ease
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Faster access to insights that previously took too long to produce
A team that never stops expanding what's possible
Unilever's global patent team manages a portfolio of 2,400 live patent families, comprising over 16,000 live patent applications. When the team first adopted IPRally, the focus was on improving search quality for chemical patent work. Today, the platform underpins a significantly broader range of workflows, from patentability and opposition searches to automated competitor monitoring that reaches deep into Unilever's R&D organisation.
This evolution reflects how Unilever is preparing for the AI age, by embedding AI-enabled capabilities into the daily work of specialist teams in a purposeful and practical way. For the patent team, IPRally has made patent intelligence easier to access, easier to explore and more directly useful to the scientists and attorneys shaping Unilever’s innovation pipeline.
Kate Buddle, a patent information analyst who has used IPRally since the early days, and Liz Oates, a European patent attorney who now also leads the PIA team, both reflect on how much the scope of use has evolved. "We were testing it to see what IPRally could give us that we couldn't get from somewhere else," Kate recalls. "The AI searching was quite poor on the other tools we were testing, so that's why we started."
The more we trust IPRally, the more we'll use it for higher-stakes work.
From search tool to classification and intelligence engine
A centrepiece of Unilever's IPRally usage is a weekly patent monitoring workflow that Kate built to help R&D scientists stay on top of competitor activity without wading through hundreds of unfiltered results.
Every week, the latest published patent applications are imported into IPRally and run through classifiers that Kate developed for classification across nine subject areas. Once classified and quality-checked, the records are shared directly with R&D users as a tagged collection, where scientists can filter by their area of interest, add further tags and use Ask AI to interrogate the results further.
"Before we had this, the scientists would get an email with the weekly alerts and each person would look through everything themselves," Kate explains. "Now they can come in and just view the records tagged to their area. It has grown from there and now they're using that data in their competitor analysis."
The R&D scientists involved are now active IPRally users, working with the platform for tagging and competitive insights. This matters because AI-enabled science depends on more than powerful models. It also depends on getting the right information to the right people at the right moment. By bringing patent intelligence closer to R&D, the workflow helps scientists make sense of complex external signals more quickly and apply them to discovery, product development and stronger intellectual property.
Searching, collaboration and what comes next
A key shift over the past three years is how readily Unilever's patent attorneys now turn to IPRally for patentability and novelty work. "We used to do all the patentability searches ourselves as analysts," says Kate. "Now we encourage the attorneys to go in themselves. They can just put in a few claims and get results out." The recently introduced Novelty Agent has accelerated this further. "The first time I used it, it produced a novelty chart in around ten minutes," says Liz. "That was a genuine wow moment."
Underpinning all of this is a close working relationship with the IPRally team, one where feedback is actively sought, new features are tested collaboratively, and support is on hand when the team needs it. As Liz puts it: "I've been really pleasantly surprised by how we work together. When you're working to deadlines and exploring new features, that kind of support is really valuable."
Both are watching smart tags and Analyst AI closely as the team looks toward landscaping and portfolio analysis. "The easier it is to do something, the more likely you are to do it," Liz says. "A lot of the new functionality opens up workflows we'd like to do. The more we trust IPRally, the more we'll use it for higher-stakes work."
As Unilever continues to combine scientific expertise, data and AI-enabled tools across its innovation ecosystem, partnerships like this can help strengthen the foundations for faster, more informed and more confident decision-making in R&D and IP.