--- title: "Rivian Scales Privacy and AI Governance Reviews 4x | Clearly AI" description: "See how Rivian's privacy team turns Jira tickets into privacy and AI governance reviews, cutting review time 90% and quadrupling capacity without new headcount." canonical: https://clearly-ai.com/customer-stories/rivian --- # How Rivian scaled privacy and AI governance reviews 4x without adding headcount _Customer story · Privacy and AI governance_ - **90%** Reduction in review turnaround time - **4x** Increase in review capacity - **0** New headcount added _Rivian's privacy and AI governance team uses Clearly AI to turn new Jira intake tickets into privacy and AI risk reviews, cutting review turnaround time by 90% and quadrupling capacity with the team it already has._ ### Story summary Rivian’s privacy and AI governance team needed to keep up with a growing number of product reviews without increasing headcount. Clearly AI helped them reduce review time by 90 percent and quadruple their capacity while improving consistency and developer engagement. ### About the customer Rivian is an electric vehicle manufacturer building connected trucks, SUVs, and delivery vans. Their privacy team supports global product launches, expanding data flows, and evolving regulatory expectations. ## Scaling privacy and AI governance at Rivian Rivian builds all-electric trucks, SUVs, and delivery vans designed for exploration and built with intelligence. These vehicles generate tens of thousands of data signals every second. That volume of data creates major responsibilities for the privacy and AI governance team, who must ensure every feature and system complies with evolving regulations and meets the company’s own high standards for responsible data use. As Rivian prepared to launch new vehicles, expand into new regions, and introduce more AI-powered features, the privacy team faced a volume problem. Reviews were increasing fast, but headcount wasn’t. “We can see even more reviews coming,” said Jim Gregoire, Head of Privacy and AI Governance at Rivian. “But we can’t get more headcount.” ## Managing high review volume without more headcount Rivian’s vehicles produce tens of thousands of data signals every second. Each new product or feature goes through a review process to assess privacy and AI risks. Their manual processes couldn’t scale to meet demand. The privacy team was spending too much time reading feature documentation, identifying data flows, and following up with engineers. > “It feels like all the work is on us, when we could cut our effort in half if we didn’t have to constantly chase developers.” > > **Jim Gregoire**, Head of Privacy and AI Governance Leadership expected speed without sacrificing depth. Developers wanted fewer blockers. And the privacy team knew they needed a different approach if they were going to stay ahead. But quality mattered as much as speed. A generic AI tool wasn’t going to cut it. They needed something that could reliably produce outputs tailored to Rivian’s terminology, risk posture, and expectations. ## Why Rivian chose Clearly AI Rivian discovered Clearly AI at a privacy conference and began a three-month proof of concept. The goal was to assess whether automation could reduce overhead without sacrificing accuracy. The results: - 90% reduction in review turnaround time - 4x increase in review capacity - Improved output consistency and quality ![Rivian's results after a 3-month proof of concept: average review completion time fell 90%, and average reviews completed per month rose 4x.](/case-study/rivian-results-calendar-days.png) “This was a bit of a godsend,” said Gregoire. “It allowed us to condense what would otherwise take weeks or sometimes months into a matter of days, if not hours.” For Rivian, Clearly AI felt like another privacy analyst on the team who already knew the regulations, understood the company’s approach, and delivered tailored, reliable outputs the first time. Clearly AI was a new team member who didn't require this customary training. Clearly AI integrates directly with Rivian’s JIRA-based intake process. When a new ticket comes in, Clearly AI automatically ingests the context, evaluates risk, and generates summaries and recommendations. ![Illustrative Clearly AI workflow: new Jira tickets trigger targeted reviews against architecture standards, required controls and data sensitivity rules, which produce a readiness summary, control gaps, and findings with suggested remediation.](/case-study/rivian-workflow-diagram.svg) What makes it different is how well it adapts to Rivian’s internal standards. The language, the risk framing, and the export format match what the team would write by hand. > “It pulls the tickets in, works its magic, analyzes the inbound, looks at the documentation, comes up with the risks, prepares the recommendations. It’s awesome.” > > **Jim Gregoire**, Head of Privacy and AI Governance ## Supporting growth without growing the privacy team With Clearly AI in place, Rivian has cut review completion time by 90% and increased team capacity by a factor of four. Reviews are faster, developers are less burdened, and documentation quality is consistently high, starting from the first draft. Privacy and AI governance now operate on the same pipeline, using the same risk evaluation framework. > “Clearly is by far the leader in this space. They understood exactly what we were going through. They knew the regulations, the compliance obligations, and they built something that worked the way we needed it to.” > > **Jim Gregoire**, Head of Privacy and AI Governance Rivian’s privacy team can now support growth without increasing team size. Reviews are handled faster, and engineers get clearer recommendations. Internal trust in the process has gone up as a result. And as the team continues to explore scaling options, they’re thinking about how a tool like Clearly AI could power broader collaboration across teams. _Results described herein reflect Rivian's experience. Individual results may vary._ _FAQ_ ## Answers to your top questions ### How did Rivian scale privacy reviews without adding headcount? By starting each review from the intake ticket instead of from scratch. Clearly AI integrates with Rivian's Jira-based intake, so when a new ticket comes in it ingests the context, evaluates risk, and generates summaries and recommendations. Rivian cut review turnaround time by 90% and quadrupled review capacity without increasing team size. [Read more about how security intake works](/platform/security-intake). ### Can Clearly AI run privacy impact assessments from Jira tickets? Yes. Clearly AI starts reviews from Jira, GitHub, ServiceNow, Azure DevOps, and Linear, and gathers context from the linked tickets, design docs, and documentation. At Rivian, reviews start automatically when a new intake ticket arrives. See privacy impact assessments and [all integrations](/integrations). ### Can privacy and AI governance reviews run on the same platform? Yes. At Rivian, privacy and AI governance now operate on the same pipeline, using the same risk evaluation framework. Clearly AI runs privacy impact assessments, AI risk reviews, vendor risk assessments, and threat models on one platform under one license. [See AI risk reviews](/solutions/ai-agentic-security). ### Is Clearly AI only for product security teams? No. Clearly AI is a continuous threat modeling platform, and privacy, GRC, and vendor risk teams use the same platform for their reviews. Rivian's privacy and AI governance team is one example. [See the platform overview](/platform). ### Will the output match our team's own terminology and standards? Yes, it's configured to. At Rivian, the language, the risk framing, and the export format match what the team would write by hand. Reviews run against your own policies and templates, and every finding links back to its source so reviewers can check it. [Learn more about quality and accuracy](/platform/quality). ### How did Rivian evaluate Clearly AI? With a three-month proof of concept. The goal was to assess whether automation could reduce overhead without sacrificing accuracy. The proof of concept delivered a 90% reduction in review turnaround time, a 4x increase in review capacity, and improved output consistency and quality. ## More customer stories - [How Ericsson Enterprise Wireless Solutions cut review times by up to 80%](https://clearly-ai.com/customer-stories/ericsson) - [How HID Global reviews 300+ products for the Radio Equipment Directive with the team it already has](https://clearly-ai.com/customer-stories/hid-global) ## For teams facing similar challenges Rivian is one of many teams using Clearly AI to keep up with growing privacy and security demands. As companies ship faster, the pressure on review teams keeps rising. Clearly AI was built for this. We faced the same challenge at Amazon, so we deeply understand the pain points. We designed a platform that fits into how your team already works. If your team is trying to scale without burning out, we’d be happy to show you how Clearly AI can help. - [Contact Enterprise Sales](https://clearly-ai.com/demo) - [Read more customer stories](https://clearly-ai.com/customer-stories/rivian#more-stories) ## Learn more - [Secure everything that ships](https://clearly-ai.com) - [We built the tool we wished we had](https://clearly-ai.com/about-us) - [One platform. From intake to remediation.](https://clearly-ai.com/platform) - [Know everything that needs a review. Skip the 300-question form.](https://clearly-ai.com/platform/security-intake) - [Ask only what matters. 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