How Vanta’s GTM team saves thousands of hours annually with Dust

Industries: B2B SaaS
Technology
Company Size: 1001+
Departments: Marketing
Sales
Executive
Company-Wide AI Adoption

Key Highlights

Seven AI platforms evaluated; Dust chosen for its balance of ease, extensibility, and partnership-level support.
~400 hours saved per week on QBR prep, translating to thousands of hours reclaimed annually across GTM.
Dust is now used broadly at Vanta, even beyond the GTM organization.

Vanta’s mission is to help businesses earn and prove trust. To hold itself to that same standard internally and keep pace with rapid growth, the company set out to make its go-to-market motion more intelligent, automated, and reliable.

Leading that effort are Danny Baralt, Business Systems AI Solutions Lead for GTM, and Shashank Khanna, Founder in Residence of GTM Innovation. Together, they’ve built Vanta’s GTM AI strategy around three core pillars:

Eliminate busywork for customer-facing reps
Scale the best performers across the organization
Enable agents to work together in real-time within existing tools, or what Vanta calls ‘Agent interplay.’

To turn that framework into reality, the team needed an AI platform that was flexible enough for individual builders yet powerful enough for enterprise scale.

Challenge

The main challenge Vanta’s GTM organization was looking to solve was access to its own expertise. Each function (GRC, finance, product, and marketing) housed critical insights about the business and their customers, but those insights lived in silos, making it difficult for teams to bring the full Vanta perspective together.

As a result, anything that required cross-functional knowledge demanded significant manual effort. Preparing for customer meetings or quarterly business reviews often meant hours spent pulling data from dashboards, assembling charts, and pasting insights into slides. Multiply that across hundreds of reps, and the hidden cost of that prep time was enormous.

Vanta needed a way to connect those sources of expertise and make them accessible across teams. The ideal solution would orchestrate data and context across multiple functions, while empowering team members—including non-technical operators—to build and use AI autonomously.

As Danny recalls, “I needed something simple enough that anyone could build with it in half an hour, but powerful enough that I could scale it programmatically when it took off.”

Solution

After vetting seven different AI platforms, the team found that most were either too shallow for enterprise use or too technical for widespread adoption. Dust struck the right balance of being self-serve for individual builders and extensible for ops and engineering. Once Dust was in place, the real shift began. Instead of treating AI as a standalone tool, Vanta used it as connective tissue across teams and built its system in three layers:

Layer 1: Domain agents built by experts

Each GTM function began by building Dust agents that captured its unique knowledge and workflows. For example:

The GRC team created an agent for compliance frameworks.
Finance built one for usage insights and revenue signals.
Product and EPD Ops developed a “Voice of Customer” agent to surface client feedback.

These agents were then exposed as APIs, turning functional expertise into reusable building blocks that any team can call on demand.

Layer 2: Cross-team orchestration

Once those foundational agents were in place, GTM built automations that pulled them together into a unified flow. One of the most visible examples is automated QBR prep. Instead of manually gathering data from dashboards and slides, the automation uses Dust to call relevant agents, including:

Finance for usage metrics
GRC for compliance updates
Voice of Customer for feedback signals

The result: a pre-built deck, speaker notes, and context-rich summary generated in minutes. According to Danny:

“It used to take hours. Now, with Dust, slides contain insights we would have missed before.”

When a team updates its agent, every connected workflow instantly improves, creating a system that evolves on its own.

Layer 3: Agents embedded in daily work

The same architecture powers real-time workflows inside Slack. The GRC SME agent now answers security and compliance questions directly in-channel, with a quick human review before responses go out. This approach meant GRC specialists no longer had to answer the same questions over and over. Once an answer was captured by an agent, it could be reused indefinitely. This final layer makes AI a visible, interactive part of the work at Vanta. Agents no longer sit in the background. Instead, they operate alongside employees, enhancing accuracy and speed across every internal and customer-facing touchpoint.

Together, these three layers created a connected network of agents: a living system that scales Vanta’s knowledge instead of locking it away.

Results

With Dust, Vanta streamlined their most critical workflows and completely reshaped how the GTM teams worked with each other. Specifically, they saw:

Time savings, and a smarter way to work

The time savings were immediate and measurable. Automating QBR prep alone reclaimed around two hours per week per rep. Between 200 reps, this is around 400 hours saved per week, or thousands of collective hours a year.

And the quality of output improved in parallel. Reps now go into meetings with data-rich, narrative-ready decks that reflect the latest insights from every corner of the company.

Compounding adoption across Vanta

Today, Dust adoption at Vanta exceeds the size of the GTM organization itself—a clear signal that AI has moved from niche experiment to company-wide muscle.

Through weekly trainings, open office hours, and one-on-one sessions, adoption continued to accelerate. “Just as an example, we recently hosted a Dust training for the whole organization and over 180 people showed up,” Shashank says. “There’s a real appetite to learn and experiment.”

Importantly, it’s not just engineers who are building. Non-technical employees are actively creating and refining agents too, turning experimentation into everyday habit.

A shift in mindset toward AI

The human response has been as striking as the metrics. Internal channels are filled with feedback like “Wow, this is awesome.” Employees who once felt intimidated by AI now see it as part of their daily workflow. Even Shashank, who was once a skeptic, has completely changed his attitude toward Dust:

“My background is in AI and deeply technical. So when I got to Vanta and heard about Dust, I was convinced it wasn’t going to work. But now I’m a full believer. I’ve been converted.”

From doing the work to building the agents that do it

Dust gave Vanta the flexibility to start small and scale fast, the APIs to connect teams, and the partnership to keep momentum. “Dust’s support has genuinely augmented my ability to use the product,” Danny says. “They’ve become an extension of the team and have helped us keep the momentum going at Vanta.”

But the real shift was cultural. Employees stopped asking what AI could do for them and started asking what they could build with it. Dust’s blend of accessibility and depth turned curiosity into capability—and capability into culture. “We used to do the work,” Shashank says. “Now we build the agents that do it.”

Interested in learning more about how Dust can help your team? Visit our solutions page or reach out to our sales team.