Sri Iyer, CTO and Co-founder of Kovr.ai – Interview Series

Sri Iyer, CTO and Co-founder of Kovr.ai, is an accomplished technology leader with extensive experience driving innovation in artificial intelligence, data analytics, quantum computing, and automation. Before founding Kovr.ai, he held senior roles at Amazon, Guidehouse, PwC, and Raytheon, where he led teams developing next-generation solutions across both public and private sectors. With over a decade of experience across emerging technologies and numerous industry certifications, Iyer has built a reputation for helping organizations leverage disruptive tools to solve complex business and security challenges.

Kovr.ai is redefining cyber compliance through an AI-native platform designed for cloud and hybrid environments. The company automates complex regulatory frameworks such as FedRAMP and CMMC using real-time, code-driven intelligence, allowing enterprises to achieve authorization to operate (ATO) in as little as 15 minutes. By replacing traditional manual consulting and inflexible compliance tools, Kovr.ai provides a scalable, adaptive approach to risk management—empowering highly regulated organizations to stay secure, compliant, and ready for continuous change.

Before co-founding Kovr.ai, you held leadership roles at AWS, PwC, and various federal-focused startups. What personal or professional experiences led you to realize there was a better way to tackle federal IT compliance—and ultimately inspired you to launch Kovr.ai?

I’ve experienced federal IT compliance challenges from both sides – first as a system owner building large-scale platforms for the Department of Defense, and later while leading cloud and AI initiatives at AWS. In one case, a system I helped build took years to develop, only to be held up in compliance for even longer. That frustration was a turning point.

At AWS, I led teams that supported services going through FedRAMP and similar compliance processes. Despite Amazon’s extensive resources, obtaining services authorization in new regions can still take up to three years. Even at that scale, the best internal solutions were essentially glorified spreadsheets – tools like Quip or Google Docs – to track and manage the process. The inefficiency was staggering, and I saw firsthand that most agencies were facing the same problem.

For years, I believed there had to be a better way, but the complexity of mapping thousands of controls across codebases and documentation made true automation feel out of reach. That changed when I led the AI/ML solutions architecture team at AWS. Watching how generative AI could transform manual workflows was eye-opening. Suddenly, what seemed impossible – reducing the compliance workload instead of just shifting it into a different tool – looked feasible.

After some experimentation and R&D, my now co-founder and I realized we could build a platform that not only tracks compliance but also meaningfully accelerates it. That insight was the genesis of Kovr.ai, a way to leverage AI to reduce, not just manage, the burden of federal IT compliance.

Many tech startups struggle with the complexity, cost, and pace of federal compliance requirements. What were some of the biggest obstacles you encountered early on—and how did Kovr.ai successfully navigate or overcome those challenges to build a viable solution?

Kovr.ai encountered several major obstacles early on in addressing federal compliance for tech startups, including:

• Complexity and Manual Processes: Startups often found federal compliance overwhelming due to the sheer number of controls (e.g., NIST 800-53 has over 1200 controls) and the manual, spreadsheet-driven processes typically used. This made compliance slow, error-prone, and resource-intensive.
• Slow Feedback and Iteration: Traditional compliance processes required long cycles of back-and-forth between teams and consultants, delaying progress and making it hard for startups to know where they stood or what to fix next.
• High Cost and Resource Burden: Startups, with limited time and money, struggled to prioritize compliance over their core product roadmaps, often delaying government work for years.

We overcame these obstacles by using automation, flexible inputs, rapid iteration, and deep workflow integration to make compliance more accessible for startups. The platform automatically scans documentation, code, and cloud environments to map them to compliance controls and provide instant gap assessments. It supports artifacts in any format, reducing barriers to entry, and emphasizes quick user feedback to ensure real-world relevance. By embedding compliance checks into development pipelines, Kovr.ai helps teams integrate compliance seamlessly without major disruptions.

How has the shift toward machine-readable compliance formats like OSCAL [Open Security Controls Assessment Language] changed how both vendors and agencies approach security?

OSCAL has the potential to make compliance more automated and efficient, but its impact is currently limited by the pace of adoption among both vendors and agencies. As more parties use OSCAL, the benefits of automation and standardization in compliance processes are expected to grow. Kovr.ai is built natively on OSCAL, enabling it to transmit and process compliance information in this format, but broader benefits will only be realized as more stakeholders adopt OSCAL-based workflows.

You describe Kovr.ai as a “compliance copilot.” Walk us through what that looks like in practice—from documentation to audit readiness. What’s happening behind the scenes that makes this process faster or easier?

Behind the scenes, Kovr.ai leverages AI and automation to eliminate manual work, provide instant feedback, and keep compliance documentation up to date,making the entire process, from documentation to audit readiness, much faster and easier for users.

Users can bring in whatever compliance artifacts they already have, in any format—documents, code, cloud environment data, architecture diagrams, etc. From there, Kovr.ai automatically scans every line of every document, codebase, and environment, and then maps all this information to relevant security controls, such as those in NIST 800-53. This is done using AI models that build a comprehensive knowledge graph of the user’s compliance landscape.

Then our system evaluates each control, identifies gaps, and generates actionable recommendations for remediation. Users can address these gaps by updating their environment or documentation and re-uploading to Kovr.ai, which then provides instant feedback on whether the issues are resolved. The great news is that this process can be repeated as often as needed, allowing users to iteratively improve their compliance posture with rapid, automated feedback, therebyeliminating the traditional back-and-forth delays between teams and consultants.

Kovr.ai can also generate all required compliance documentation, including government templates, like FedRAMP SSPs, using the information in the knowledge graph.

Lastly, the platform keeps all compliance information up to date and can package it for auditors. Increasingly, auditors can even access Kovr.ai directly to review and query compliance data, streamlining the audit process.

Startups often face a difficult tradeoff: move fast and break things, or slow down to meet compliance. How did you approach this tradeoff while building Kovr.ai—and what advice would you give other innovators trying to scale into regulated markets?

Kovr.ai was built with compliance and security in mind from the outset, incorporating features such as air-gapped systems, strong authentication, and encryption to support regulated environments. We also integrated automated compliance checks directly into our DevOps pipeline, enabling early issue detection and avoiding lengthy reviews and focused on rapid prototyping and integration based on user feedback, ensuring the product met user needs while remaining compliant. Automation further reduced manual overhead, enabling fast and secure development at scale.

For innovators, it’s crucial to embed compliance and security into your product from the start, especially for regulated markets. Integrate automated compliance checks into your DevOps pipeline to catch issues early and bring in human compliance experts when needed. While compliance may slow feature development, it ultimately saves time by avoiding costly rework.

You’ve spoken about the need to modernize federal procurement. What parts of the current system feel most outdated—and what practical changes would make it easier for early-stage companies to compete?

The federal procurement system often feels outdated, with slow acquisition cycles, funding that prioritizes operations over innovation, and complex purchasing mechanisms that make it hard for startups to break in. To support early-stage companies, practical reforms include allocating more flexible, innovation-focused funding, lowering acquisition thresholds for quicker, smaller purchases, expanding access to procurement vehicles like DOD’s Tradewinds, and creating streamlined, “app-store”-like platforms to simplify how agencies discover and buy new technologies.

Looking back, what foundational decisions—around architecture, go-to-market strategy, or hiring—proved most important in getting Kovr.ai to where it is today?

The most important foundational decisions for Kovr.ai were rapid prototyping and iteration, a user-driven product vision, flexible production strategies, building a feedback community, and maintaining a strong focus on customer needs. These choices enabled us to build a solution that truly addressed the challenges of federal compliance.

As CTO, how do you strike the right balance between innovating rapidly and maintaining airtight compliance? Are there any frameworks or internal practices you’ve adopted to keep both priorities on track?

I balance innovation and compliance by embedding compliance into every stage of development, leveraging automation, maintaining flexible production environments, and staying closely connected to user needs and expert guidance. These practices ensure that both priorities – rapid innovation and airtight compliance – are consistently met.

Looking ahead, where do you see Kovr.ai expanding next—whether into state and local government, other regulated industries like finance and energy, or even international markets?

The team will continue to advance the Kovr.ai technology for continuous and automated compliance management, expanding in several directions beyond its current focus on federal government compliance. This includes expansion into state and local government, other regulated industries like, finance, energy, and healthcare, and international markets.

Thank you for the great interview, readers who wish to learn more should visit Kovr.ai.