Veeva picks up agentic MLR tech in Copli acquisition

The automated tool is aimed at dramatically reducing manual MLR labor.

solli
24th June 2026

Veeva Systems’ latest acquisition is centered on clearing out a notorious bottleneck in pharma marketing. 

The company, which provides cloud-based software and consulting services to life sciences clients, announced Tuesday that it has acquired Copli, a Danish developer of artificial intelligence-powered technology automating the medical, legal and regulatory (MLR) review process. 

Copli’s tech has now been rebranded as Veeva Falcon MLR. Its agentic AI reviews promotional and medical materials for compliance with approved label info and regional regulations. 

The tool is aimed at slashing the amount of time dedicated to manual MLR reviews so human experts can devote more effort to more complex strategic work; according to Veeva, the AI could potentially reduce manual MLR labor by at least 70% within five years. 

The buyout is the second this year for Veeva. In March, the company acquired another tech maker: Ostro, with its AI-powered chat tool providing patients and clinicians with information drawn from pharma clients’ MLR-approved resources. 

solli’s Final Thoughts 

MLR review is often described as the biggest bottleneck in pharma media and marketing. As regulatory requirements become stricter and more complex in the U.S. and beyond, the process can add weeks or even months to a campaign launch timeline, potentially derailing even the most carefully crafted media plan. 

The agentic AI boom may be key to clearing the slowdown. Automating the tedious, time-consuming tasks of compliance review could not only shorten launch timelines—allowing for more reactive, dynamic media plans—but also free up teams to focus more on other campaign components, like creative iteration and personalization. 

Of course, those efficiencies will only materialize if AI tools are carefully trained and closely monitored, with full transparency and auditability around the agents’ every decision throughout the MLR review process.

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