Mimos Is Betting That AI Search Optimization Is the Next SEO, and It Might Be Right

The Macro: Search Just Forked, and Most Companies Missed It

I have been watching the AI search conversation go from theoretical to urgent in about six months. 800 million people now use ChatGPT every week. Perplexity is growing fast. Google’s own AI Overviews are eating traditional blue links from the inside. The old SEO playbook, keywords in headers, backlinks from guest posts, schema markup, still works for traditional search. But a growing slice of traffic never touches a search results page at all. People ask a question, get an answer, and move on. The website they would have clicked on two years ago never loads.

This is not a hypothetical problem anymore. It is a revenue problem. If you run a financial advisory firm and someone asks ChatGPT “what should I look for in a wealth manager,” your firm either shows up in that answer or it does not. There is no page two. There is no “below the fold.” The AI either cites you or it cites your competitor. That binary outcome is fundamentally different from traditional search, where ranking fifth still gets you clicks.

The market for AI search optimization barely exists as a category yet, which is exactly when the interesting companies tend to show up. Traditional SEO agencies are still figuring out whether this is real. The tools built for conventional search, Ahrefs, Semrush, Moz, do not track AI citations. There is a genuine gap between what businesses need and what the existing tooling provides.

The companies trying to fill that gap right now are mostly early stage and mostly focused on content optimization. Otterly.ai does AI search monitoring. Profound tracks brand mentions across LLMs. But the full-stack approach, where you identify the gaps, generate the content, and handle compliance, is still wide open.

The Micro: Two Friends from Sixth Grade, One Very Specific Problem

Mimos helps regulated companies get cited in AI search engines. The platform identifies visibility gaps in AI responses, generates compliance-friendly content with the right disclosures baked in, and deploys it directly to client websites. The focus on regulated industries is a deliberate choice. Financial services, healthcare, proptech, and legal firms cannot just throw blog posts at the wall. Their content needs specific disclaimers, careful sourcing, and approval workflows that generic content tools ignore completely.

Rohit Sirosh is the CEO and co-founder. He previously led high-throughput storage infrastructure on Azure at a major cloud provider, where he worked on training workloads for large language models. Michael Korovkin is the CTO and co-founder. He directed AI integration across more than a billion voice assistant devices and later architected AI agents at Coinbase. They have been collaborating on technical projects since sixth grade, which is either charming or alarming depending on your feelings about co-founder dynamics. They came through Y Combinator’s Summer 2025 batch.

The product landed five paying customers within a month of launch, with an active pipeline across health, investing, proptech, and marketing. Early data shows 2x higher AI citation rates compared to baseline content, which is the kind of metric that matters if it holds up at scale.

What I find compelling about the approach is how specific it is. Mimos is not trying to be an AI search tool for everyone. It is building for companies that need compliance guardrails around their content, which means law firms, financial advisors, and health systems. Those are industries where generic AI-generated blog posts are not just unhelpful but potentially dangerous from a regulatory standpoint. The compliance layer is the moat. Any content tool can generate a blog post about retirement planning. Very few can generate one that includes the right SEC disclaimers and gets approved by a compliance team without three rounds of revisions.

The go-to-market motion is currently focused on plaintiff law firms, with the product pitched as an AI growth platform that combines competitive intelligence, targeted advertising across search platforms, AI search visibility, and automated intake triage. The full-stack deployment takes about a week. They claim a compounding 12 percent weekly improvement rate through automated optimization, which is a bold number to put on a website.

The Verdict

I think Mimos is early to a market that is about to get very crowded. AI search optimization will be a real category within a year, and the companies that build for it now will have a head start when demand spikes. The regulated-industry focus is smart because it creates a natural barrier against generic competitors.

The question I would want answered at 30 days is how defensible the compliance layer really is. If Profound or Otterly.ai or a traditional SEO platform adds regulated-content templates, does Mimos still have a wedge? At 60 days, I would want to see whether the 2x citation rate holds across different AI models, because ChatGPT, Perplexity, and Gemini all weight sources differently. At 90 days, retention. Are those five paying customers renewing, or is this a one-time optimization that does not require ongoing tooling?

The law firm angle is a strong beachhead. Legal marketing is expensive, competitive, and increasingly AI-driven. If Mimos can own that niche, expanding into adjacent regulated verticals becomes a much easier conversation. I would not bet against two co-founders who have been building together for over a decade, especially when the market is this obviously underserved.