Reinventing non-clinical reporting at Enveda with Benchling’s Deep Research Agent

The slowest part of scientific work often isn’t the science. It’s everything that comes after.

At Enveda, a single non-clinical report used to take weeks to complete. Not because experiments were unfinished, but because starting the report itself required time, coordination, and energy that teams rarely had. The result was a familiar R&D problem: valuable data sitting in Benchling, waiting to be turned into something reviewable. 

Today with Benchling AI, Enveda can turn a less complex experiment into a drafted non-clinical report in about a day, and a combination of more complex experiments into one drafted non-clinical report in about a week. Scientists contribute directly, data stays secure, and reporting isn’t a bottleneck. 

The challenge: Report writing takes longer than the science itself

According to Amy Myers, Senior Laboratory Process Manager and Benchling super user at Enveda, the friction around reporting was their primary issue.

Before Deep Research, Enveda teams had two options for report writing, but neither felt scalable. They could write reports from scratch, which was cumbersome and labor-intensive. Or they could export data from Benchling into external AI tools. Data had to be pulled, stored, and reformatted. Teams in the US and India had to coordinate across tools, and security concerns made the process uncomfortable.

The solution: Reporting on Benchling data with Deep Research

Enveda adopted the Deep Research Agent to generate non-clinical reports directly from experiments in Benchling. “It’s nice that Deep Research leverages our experimental records we already have,” Amy said. “No exporting or importing, it’s all already there.”

Because Deep Research can organize experiments across teams, projects, and geographies, it will bring Enveda’s US and India teams into a single reporting workflow. References, data, and citations live in one place. That shift alone will remove weeks of overhead.

Key benefits: Simple report first drafts, 400% faster

• Simple first drafts generated in one work day, rather than a week: Deep Research cut down drafting time for report authors, allowing them to generate first drafts faster.

• Direct scientist review: Scientists who run the experiments or other stakeholders at the company can now contribute directly to the reports and review the output themselves. 

• Improved report quality and consistency: Deep Research produces standardized reports, even when experiments vary widely in format and templates ensure consistency.

How Enveda implemented Deep Research in practice

Enveda treated Deep Research as a process, not a plug-and-play feature. Amy started with Benchling’s base non-clinical report template from the Deep Research help pages. From there, she layered in AI instructions Enveda had developed from prior tools and iterated with user feedback until the output matched what teams needed.

Amy championed adoption through monthly meetings, Slack updates, and hands-on training. While 10–15 people were trained, only a few active users were needed to prove value and spark interest across teams.

That approach worked, and training sessions generated excitement around reporting and Benchling AI. Other groups have already approached Amy with ideas for new report types and metric-driven use cases planned for Q1.

A new baseline for reporting at Enveda

Deep Research didn’t just make Enveda faster. It changed who owns reporting and how it fits into scientific work. Reports no longer sit at the end of a project. They can be generated when experiments are relevant. Scientists stay closer to their data. Teams collaborate across regions without exporting files or losing context.

Deep Research removes friction from essential work so teams can focus on what matters most. For Enveda, that means turning science into decisions faster, without compromising quality or trust.

Request a demo and learn more about Benchling AI and the Deep Research Agent. 

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