RESEARCHThe State of AI Search, Q3 2026: 110 B2B SaaS brands measured across four AI models ↗The State of AI Search, Q3 2026 ↗
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One question, four ways in

Every team has a reason. Each one has an answer.

01 · SeenModern DiscoveryIs AI recommending your competitors instead of you?See how often your brand is AI's first recommendation, who's winning instead, and what to change to compete.See Who AI Recommends 02 · TrustedModern GravityCan you trust the numbers AI gives your executives?Ask complex business questions. Get answers calculated from approved metrics, independently checked, and backed by an audit trail. Your AI's analysis sits beside them, labeled not certified.Explore Verified Answers 03 · ExperiencedModern FrictionWhat's driving customers away, and what is it costing you?Find the customer problems putting revenue at risk, trace their causes, and prioritize what to fix.Find the Revenue at Risk 04 · UnderstoodModern FoundationYour business is complex. Does your AI understand it?We define and govern the business meaning and operating context your AI needs to deliver answers your business can use.Explore the Foundation Diagnostic

One free read covers all four. Written for your leadership team, from a live scan of your brand, with the math shown.

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01At a glance

The Truth Layer, at a glance.

3Core products
6AI surfaces measured
60K+AI checks completed
300+Brands measured

AI checks count completed Discovery measurement runs across supported AI surfaces (ChatGPT, Gemini, Claude, Perplexity, Google AI Mode, Google AI Overviews). Brands count distinct companies with measured AI results, demo data excluded. Counts as of September 2026 and refresh with each pipeline run.

+ Structured Services. Focused enterprise engagements when the problem extends beyond a standalone product.

02The proof

Read it before you trust it.

Every score should be traceable to the run that produced it.

Methodology is versioned and published.

Read Discovery methodology →

Example · free quick read · 2026-10-03
brand · Google's top beauty brand in our Q2 study
AI picked it first · 0% of searches
AI mentioned it · 25% of searches
asked · "organic makeup brands comparison"
AI recommended instead · INIKA Organic, RMS Beauty
2 of 6 AI surfaces sampled · brand not named

Measured across the AI surfaces buyers use: ChatGPT · Gemini · Claude · Perplexity · Google AI Mode · Google AI Overviews

Receipt
metric
Recommendation Rate
definition
versioned, published
run
model, surface, timestamp
evidence
the answer that produced it
03Built by an operator

We built Modern AI from the buyer's side of the table.

5
Major enterprisesCarter's · NCR · Citrix · TracFone · Verizon
$250M
Profitability impactattributed to AI-powered commercial analytics
$7B
Business scaleanalytics and FP&A supporting growth from about $1.5B to $7B in revenue
2×
Delivery throughputfrom an operating-model redesign

So when we talk about governed data, AI adoption, legacy systems, executive trust, operating models, and getting technology into production, we are not describing problems we studied from the outside.

We were responsible for them.

CDO Magazine 2025 Top 25 Atlanta Data Leaders.

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Start with one problem.

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Reply within one business day · one scope · written quote.

The problem is rarely where you think it is.

04In practice

Alpha engagements · companies not named

National moving and storage company

Seen, but not chosen.

AI knew the brand and mentioned it often. When buyers asked which company to pick, AI recommended a competitor. The brand won when buyers compared directly, and lost where buyers start.

The team revised its AI-visibility strategy based on the findings.

Regional garage door company

Recommended, but not found.

Local buyers asking AI for a garage door company were sent to the national brand with a similar name, and to a same-named company in another state. The company's own website was not cited.

Prescribed: make it unmistakable to AI which company serves which market.

Global IT staffing company

Known by name, missing from the shortlist.

AI could describe the company when asked about it directly. When a buyer asked which firm to hire, AI rarely named it and pointed to other providers.

Prescribed: build the signals AI uses when it chooses a provider, then measure again.

05Start small

You don't have to bet on us.

Start with one problem.

No platform migration.
No transformation program.
No multi-year bet required to prove the value.

Pro: month to month at $599 · Enterprise: one scope · Gravity: one vault

Give Modern AI one problem worth solving.

See the evidence.
See the methodology.
See the answer.

Then decide whether we earned the next one.

One problem. One scope. Proof first.

06Enterprise trust

Built for enterprise scrutiny.

  1. /0.1Gravity: your dataWith Gravity, your data stays in your environment. The Gravity vault holds your certified definitions, not your records, and your transaction and unit-level data is never retained by Modern AI after setup.
  2. /0.2Friction: data flowA data engineering partner anonymizes Customer 1 to 1 data inside your environment, removing names, emails, payment details, and raw content, and delivers it to Modern AI's Friction environment.
  3. /0.3Discovery: what we needDiscovery measures public AI answers. To start, it needs your brand or domain, not access to your systems.
  4. /0.4AuditabilityEvery Gravity answer carries a receipt: the definition used, the checks run, and the verification result. Every Discovery score traces to the run that produced it.

View Security & Trust →

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Give us one problem.

Not your platform.
Not your transformation roadmap.

One problem worth getting right.

We'll show you what Modern AI sees, how we got there, and the evidence behind it.

Then you decide if we've earned the next one.

Enterprise: Reply within one business day · one scope · written quote. No pitch deck required.

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Three products. Structured Services. One Truth Layer. Discovery (live). Gravity (GA), with Agentic BI built on it. Friction (GA). Modern Foundation (Structured Services).