Natalia Khamraeva

Natalia Khamraeva's public voice over these months traces a single arc: turning fifteen years of personal frustration as a working auditor into a company built to remove that frustration for others. In the podcast on All Colors of Communication, she is explicit about the origin story, describing how nearly fifteen years in corporate auditing left her with accumulated frustrations about inefficient and tedious tasks, and how AI opened possibilities for her to finally address them ¹⁰. That biographical fact matters less as history than as a lens: almost everything she says publicly afterward reads as a founder still solving the problems she lived through, not an outsider imposing software on a profession she doesn't understand.

The clearest recurring theme is that Auditstage is not just shipping code but trying to change how audit firms actually work day to day. She frames the company's promise to clients directly: "we do not only ship code, but also help with the adoption of our software in the field by doing something that none of our competitors do" . The concrete mechanism she describes is the Audit Champion, a person embedded with each firm who has "at least four years of audit experience" so they can do real audit work while onboarding auditors and clients . This is a consistent thread across her posts: technology alone does not solve the problem, adoption inside a conservative, reputation-driven profession is treated as equally hard and equally important.

She is candid about the pressure of building something ambitious in public. Looking back sixty weeks after Auditstage's initial funding announcement, she recalls "feeling mostly one thing: pressure to prove that the crazy vision in my head could actually become reality" . That same post marks a shift in ambition, from having "built deterministic engines for virtually every aspect of financial auditing" to raising a €2M Seed round to turn those engines "into a complex sequence of AI agents" and ship what she calls "the most complete auditing software that has ever existed" . The progression she narrates is from foundational, rules-based engineering toward AI-agent architecture, and she credits investor Jürgen Ingels specifically for entrepreneurial guidance during that stretch .

On the seriousness of the domain, she repeatedly insists that audit software cannot be built casually. She makes this point almost as a rebuttal to generic SaaS thinking: building for "professionals who protect the quality of their work with their reputation every single day, is not something you do with a bit of overnight coding experience" . Her image of "272.000 hours of combined experience in software development and financial auditing" sitting in one room is her way of arguing that domain depth, not just engineering speed, is the real moat . This same seriousness shows up in hiring: she highlights bringing on people with deep enterprise and audit backgrounds, noting new engineering manager Kaustav Das is "also a former PwC colleague," treating that shared professional lineage as a meaningful signal rather than a coincidence .

Her stated position on AI in auditing is more nuanced than boosterism. In the podcast recorded with the Institute, she frames the real risk not as auditors avoiding AI but as auditors trusting it uncritically. She recounts the closing dilemma from that recording, that the bigger danger is "the auditor who blindly trusts AI," a conclusion she reached jointly with her co-panelist, and explicitly says that's "exactly the one thing we're" building against . This positions Auditstage's engineering philosophy, and her personal stance, as skepticism-first: AI should extend audit judgment, not replace the auditor's scrutiny. Her webinar work reinforces this practical, audience-first approach, where she describes the core challenge as making AI "practical for a room full of auditors with completely different levels of experience" , suggesting she sees education and calibration, not just capability, as the bottleneck to adoption.

Running underneath the product and AI commentary is a persistent emphasis on people and collaboration as the actual mechanism of company-building. She describes a phase of "hitting the road together, talking to the market, meeting people, listening, and learning" and draws a sharp distinction between supporters who "simply cheer from the sidelines" and those who "get in the trenches" by arranging meetings, challenging thinking, and opening doors . Her definition of "building a company together" is explicitly this latter, effortful kind of support . Combined with her account of shifting from auditor to founder, and her expectation that her own role will move toward sales as the company scales ¹⁰, the overall takeaway is of someone treating founder identity as inherently transitional. She frames her job not as a fixed skill set but as whatever the company's current phase demands, whether that is writing software, running webinars for regulators, recruiting former colleagues, or eventually selling.