How causaLens caught missed R&D projects — and saved weeks
causaLens is a UK-based AI company building an AI workforce for enterprises — Digital Workers that automate complex, high-value business workflows. Like many R&D-intensive tech companies, they invest heavily in engineering and research, and file R&D tax relief claims every year.
Company
VC-backed AI SaaS company, building Digital Workers to automate enterprise workflows
Team Size
~30 engineers, researchers and data scientists
Region
United Kingdom
Challenge
Annual R&D claims required weeks of manual reconstruction — digging through Jira, GitHub, and Google Drive, plus interviewing engineers — with some projects being missed entirely
Solution
Taxnova connected to causaLens's engineering and documentation systems to automatically identify, evidence, and structure R&D activity
Result
Hours saved (~80% reduction in overall prep effort), more projects identified than the team could recall manually, and evidence-linked documentation ready for advisor review
The Challenge
Steven, Director of Research at causaLens, had been managing R&D tax claims for three years. Each year, the process consumed weeks of his time — digging through Jira tickets, GitHub commits, Google Drive folders, and interviewing team members to reconstruct what the engineering team had actually worked on.
The core problem: startups don't document as they go. By the time tax season arrives, key details are scattered or forgotten.
"I was a bit sceptical at first. I knew it was hard to get all of that information with how little documentation startups tend to do"
The Solution
Taxnova connected directly to causaLens's existing tools — Jira, GitHub, and Google Drive — to automatically identify qualifying R&D projects and calculate time allocations.
Three Things That Made the Difference
1
Automated project identification
"Most of the value added was in the project identification. I didn't have to go through all of the Google Drive to identify the projects. A lot of the projects I didn't work on myself, so I would have had to either get other people in or they would have been missed."
2
Time allocation: weeks → hours
"The time allocation was the point where I spent a lot of time last year. This year, I've spent a couple of hours on it, so that was good – very good for me."
3
A systematic, evidence-backed approach to time tracking
"We have a very systematic approach as opposed to previous years. That's one point in and of itself — the systematic approach, which is great. Having lots of evidence at hand is also extremely useful."
The Verdict
Steven started sceptical — he knew how little documentation startups actually keep. But after a historical pilot and a full production run:
"I was surprised — the report was very comprehensive. I thought it was actually excellent"
Most importantly, the time saved lets Steven focus on actual R&D work — not paperwork. When asked about the reduction in effort:
"That's already closing in on 80% of the work"
The Takeaway
By connecting to the tools where R&D actually happens, Taxnova helped causaLens:
Cut time allocation work from weeks to a couple of hours
Surface projects that would have been missed manually
Build a systematic, evidence-backed claim — not one based on memory
Work smoothly alongside their existing tax advisor
"It's becoming better and better with every iteration"
Ready to see similar results for your company?