About Modern AI
Modern AI builds the infrastructure that makes AI trustworthy for the organizations that depend on it. Three products. Structured Services. One operating thesis.
The Operating Model
Modern AI is a build-first company. Before we contract an outside service, we ask whether we can build a proprietary system in an hour of parallel agent work. We usually can. That discipline compounds into products competitors cannot replicate by hiring.
The company runs on an agentic operating system: specialized AI teams working in parallel, each scoped to a domain and producing handoff-ready output. The result is department-grade work at a fraction of the overhead. The infrastructure that produces it is the company.
When we say "ask Claude first, we show you where it is wrong," we mean it. That posture is only possible because we operate on the same principle internally. Modern AI is the honest broker because our own operating model is the proof of concept.
Before contracting an outside service, the first question is whether we can build a proprietary system in an hour of parallel agent work. Most of the time, we can. This keeps the moat inside the product.
Modern AI is built on an agentic operating system: specialized AI teams working in parallel, each with a defined scope and a clear handoff. The output is department-grade. The infrastructure that produces it is the company.
We say the quiet part out loud: ask Claude first. We show you where it is wrong. That posture is only possible because our own operating model is the proof of concept.
Every external surface speaks to outcomes, not implementation. The mechanism is the moat. The output is the product.
The Thesis
Every company in 2026 is navigating the same question: where can I trust what AI tells me, and where is it quietly wrong? Modern AI is the infrastructure that answers that question with a receipt.
AI is becoming the interface between companies, customers, employees, and decisions. That creates three truth problems. Modern Discovery tells you whether external AI recommends your brand. Modern Gravity makes the answers your organization acts on defensible. Modern Friction shows what customers actually experience before it hits your renewal number. Structured Services, delivered through the Modern Foundation methodology, fix the data, governance, and operating layer underneath when the problem is bigger than a product.
The Portfolio
Does AI recommend your brand, or a competitor? Measures Recommendation Rate across ChatGPT, Gemini, Claude, Perplexity, Google AI Mode, and Google AI Overviews, diagnoses the gaps, prescribes the action, and verifies the lift.
Learn moreAI answers you can defend. Grounds business questions in certified metrics, business context, and reproducible receipts. Agentic BI is the decision layer built on Gravity.
Learn morePer-customer CX visibility at the Customer 1 to 1 level. See where customers leak before the renewal cycle surfaces it, correlated with the revenue at risk.
Learn moreModern Foundation™ · Structured Services
Structured engagements for enterprise data, AI readiness, governance, implementation, and operating-model problems. Diagnostic, Build, Operationalize. Each ends with something your team owns and operates.
See Structured ServicesResearch
Modern AI published the Q2 2026 State of AI Search Report covering 110 brands across ChatGPT, Gemini, Claude, and Perplexity. The data is real: 10,000+ AI model checks, ranked AI Shortlist Scores, and the two-year collapse in SEO-to-AI overlap documented with independent measurements.
This is the interim authority anchor for what we measure and why. The full Truth Gap Report is the parallel research program.
Read the Q2 reportKey findings
Most tools measure mentions. Discovery measures how often AI names you first.
110 brands measured. AI Shortlist Scores across the four AI models in the study.
25 + 25 static brand tables. Canonical data surface.
Recommendation Rate differs by up to 40 points across AI surfaces for the same brand.
Matt Kott, Founder
The Founder
Modern AI was founded by Matt Kott, a two-decade enterprise data and AI operator. Before founding the company, he was VP of Global Data and Analytics at Carter's, the company's most senior data and analytics executive, and VP of Advanced Analytics at NCR, where he headed the function. Earlier data leadership roles span Citrix, Tracfone, and Verizon. He built the data platforms and analytics organizations that multi-billion-dollar businesses run on.
The rest of the company is intentionally agentic. One operator directs specialized AI teams working in parallel, each scoped to a domain with a clear handoff. That is the operating thesis. The products are the proof.
CDO Magazine
Named to CDO Magazine's 2025 Top 25 Atlanta Data Leaders list.
Evanta
Boardroom participant, Modern Data Governance: Maturity and Trust. November 20, 2025.
Tableau Customer Stories
Featured operator case study on a multi-year data and analytics transformation at Carter's.
Proof posture
300+ brands measured.
We measure brands, not "work with" them. 60,000+ AI model checks across the AI surfaces measured, as of September 2026. Brands are distinct companies with measured AI results, demo data excluded. Discovery is live. Gravity and Friction are GA.
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See where AI recommends your brand today, no card required. 200+ brands measured. Your score in under 60 seconds.
Three products. Structured Services. One Truth Layer. Discovery (live). Gravity (GA), with Agentic BI built on it. Friction (GA). Modern Foundation (Structured Services).