When ArmorCode's Chief Product Officer Mark Lambert took questions on the exhibition floor at RSA Conference 2025, he kept returning to one word: governance. Not scanning. Not automation. Governance.
It's an unusual pitch in a security market that loves to sell speed and detection, but it hints at where his company thinks the real problem lives. On April 28, ArmorCode launched Anya—what it's billing as an agentic AI "virtual security champion" for application and product security teams, entering a market where competitors like Cycode and Legit Security were announcing similar solutions around the same time. The timing wasn't arbitrary. Security organizations are, by most accounts, drowning. Findings pile up faster than analysts can triage them, specialized talent remains scarce, and the dashboard fatigue is real.
Anya's promise is deceptively simple: stop making security leaders hunt through interfaces to correlate data from hundreds of scanning tools. Instead, give them a conversational teammate that already understands the context.
Whether that's a genuine shift or just a friendlier front-end remains an open question.
What It Actually Does
Strip away the marketing language and Anya is a natural language interface sitting atop ArmorCode's Application Security Posture Management platform. The system ingests cross-correlated findings from 285 integrations at launch—a figure that reportedly climbed to 320 by Black Hat USA in August 2025 and hit 350 by March of this year.
The architecture combines large language models with retrieval-augmented generation, allowing it to learn within the boundaries of a customer's private data. It's designed to deliver persona-aware responses: a CISO asking about board-level risk gets a different view than an AppSec lead hunting down a specific vulnerability cluster or a developer trying to figure out what to fix before lunch.
But Anya doesn't just answer questions. Through support for Model Context Protocol, it can take autonomous action—spinning up Jira tickets, updating workflows, firing off alert communications, orchestrating remediation across teams.
"Dashboards still have a place," Lambert said during that RSAC interview, though his tone suggested he doesn't expect them to hold that place much longer. He described Anya as a "governance layer over the scanners," something that can surface root causes and next steps without manual digging.
Perhaps more importantly, it's meant to do so in seconds rather than hours. That speed claim is central to ArmorCode's pitch, though it's also the kind of promise that needs proving in messy production environments.
The Governance Play
ArmorCode's strategic positioning hinges on staying independent. Rather than building yet another scanner—the market hardly needs more of those—it aggregates findings from code analysis, application testing, cloud infrastructure, containers, and more. Then it layers intelligence on top: deduplication across those integrations, prioritization by severity and fixability, ownership assignment based on team structure.
The company has shared customer testimonials that speak to this approach. NetApp, an early access customer, pointed to "targeted and instructive remediation activities" enabled by ArmorCode's AI capabilities, adding that the team is "exploring agentic AI capabilities to further reduce MTTR."
S&P Global emphasized speed. "With Anya, anyone on the team can get answers in seconds," a spokesperson noted, calling out the platform's role as an independent governance layer—there's that word again.
The Motley Fool's security team was blunter about the use case: "AI for AppSec is compelling because it can quickly determine if a vulnerability is both genuine and truly risky." Translation: not every finding matters, and figuring out which ones do takes time security teams don't have.
Scale as a Feature
The numbers ArmorCode cites have ballooned since launch. At general availability last April, the platform had processed 25 billion findings and was supporting 3,500 security engineers across 175,000 developers. By August, that jumped to 40 billion findings. The most recent company data, released March 3, puts annual processing at over 200 billion findings.
Whether those figures represent genuine scale or clever accounting is hard to say from the outside, but the trajectory matters for one reason: an agentic system is only as useful as the breadth and freshness of the data it can access. The 350 native integrations span vulnerability scanners, SAST/DAST tools, container security platforms, cloud posture management systems, ticketing platforms, and CI/CD pipelines.
ArmorCode has been collecting industry validation along the way. IDC named it a Leader in its MarketScape for ASPM in September, citing Anya's role as a generative AI assistant. CRN recognized the company as a 2025 Stellar Startup in November.
The AI Governance Expansion
Anya wasn't the end of ArmorCode's AI story—it was the opening move. On March 3, as part of its cumulative strategic funding efforts, the company introduced AI Exposure Management. The solution is designed to discover, track, and govern AI usage across the enterprise.
The timing aligns with a problem many security teams are only beginning to grapple with: shadow AI. AIEM inventories AI models, agents, and MCP servers scattered across an organization, then converts those signals into governed decisions with board-ready evidence trails. It's the kind of visibility that becomes urgent once executives realize they have no idea how many generative AI tools employees are actually using—a challenge ArmorCode is addressing alongside other vendors in the emerging AI governance space.
Gartner offered some context in August, forecasting that 40 percent of enterprise applications would feature task-specific AI agents by the end of 2026, up from less than 5 percent in 2025. If that prediction holds, the governance challenge grows exponentially.
"Anya is changing the game for how security and development teams interact with their security posture," said ArmorCode CEO Nikhil Gupta. The company has indicated it's expanding Anya through what it calls the "Anya Agentic Framework" to enable autonomous multi-step workflows with broader MCP support—though details remain thin.
A Crowded Field
ArmorCode isn't alone in this bet. Cycode announced "Agentic AI Teammates" on April 23, five days before Anya's general availability—agents for change impact analysis, natural language scanning, exploitability assessment, remediation. Legit Security rolled out AI-enhanced ASPM capabilities on April 29. Apiiro launched its AutoFix Agent in October, followed by a Guardian Agent to govern AI-generated code. JFrog introduced agent-based remediation capabilities in September.
The distinction ArmorCode draws is in positioning Anya as a unified conversational layer across the entire ASPM platform, not a collection of task-specific agents. Whether that resonates with enterprise buyers will depend on execution—how well Anya handles the messy realities of security operations at scale, correlates findings from disparate tools, understands organizational nuance, and actually reduces mean time to remediation rather than just adding another interface to the pile.
The company's rapid growth in findings processed and integrations supported suggests early traction. Independent reviews, however, remain scarce. For now, ArmorCode is making the case that governance, not just automation, is what security teams need from their AI.
Which may be right. Or it may be a savvy way to differentiate in a market where everyone's building agents and calling them transformative. Time, and customer retention rates, will tell.
