Conversational Intelligence Platform

AI tells your audience who you are. Before you do.

People now make up their mind inside an AI conversation, before visiting any website or reaching out to anyone. ArtaSense measures what AI says in those conversations, grounded in your data and for your audience.

Grounded in your data Multi-turn journeys Ideal Audience Profile Competitive branching Commercial roadmap
Inside the AI conversation
Best analytics platform for a product-led SaaS team, anything beyond the obvious picks?
Three strong picks: Amplitude, Mixpanel, and PostHog. Amplitude leads on depth, Mixpanel on ease of setup, PostHog on open-source flexibility.
Any worth considering for enterprise scale?
Amplitude is the clearest enterprise fit: dedicated CSM, SLA tiers, and deep cohort analysis. Mixpanel has improved but still skews mid-market.
ArtaSense Intelligence
▾ Invisible to AI[Your brand] appeared in 0 of 5 decision journeys run in this category. AI cited the same three sources every time.
Invisible across 47 conversation paths tested · Priority: Critical
Millions of these happen every day. None show up in your analytics.
The shift

The conversation starts before you're in the room

Before any website visit, first conversation, or final decision, AI has already framed the category, introduced your competitors, and shaped your audience's mind.

That happens millions of times a day, and it leaves no trace in any existing measurement system.

The old journey
Searches Google
Visits websites and reads reviews
Asks friends, peers, or advisors
Contacts the organization
Makes a decision
now
The AI journey
Asks ChatGPT, Claude, Perplexity
AI explains the category and options
AI compares alternatives, answers objections
AI recommends a shortlist
Decides. Often before your organization is involved.
The engine

How ArtaSense runs the decision journey

Four layers, grounded in real audience signals and your actual market. They feed multi-turn conversation agents across every major AI engine.

01

Who your audience really is

Audience signals from trusted panel and survey partners anchor every journey in real segments, not invented personas.

Audience Intelligence
02

How many of them exist where

Population modeling projects segments across cities, regions, and demographics, so every AI gap is weighted by real market size.

Population Modeling
03

What they actually ask

Grounded in your real audience data and category language, so every conversation reflects how people in your market actually think and decide.

Market Reality
04

How AI responds to them

Multi-turn conversation agents run across ChatGPT, Perplexity, Claude, Gemini, and DeepSeek. They ask, react, compare, and decide, capturing every place you win or lose.

Conversation Engine
What you get

From diagnosis to commercial action

Not a visibility score. A map of where AI helps and hurts your organization, and exactly what to do about it next.

Diagnosis

Where you win, where you lose, and why. Per segment, per geography, per AI engine. Including the drop-off points, framing weaknesses, and source citations driving each outcome.

Prioritization

Every gap weighted by audience size, segment value, and likely impact, so you know which journeys are worth fixing and which to deprioritize.

Roadmap

Specific actions: content, page updates, structured data, local pages, partner content, paid plays. Ranked by impact and mapped to the decision journeys they improve.

Why ArtaSense

Calibrated, not asserted

Anyone can prompt a language model to act like your audience. The result is a stereotype with a demographic label. ArtaSense personas are grounded in real audience segment data, not invented characters. No score is produced without being calibrated against ground truth you already trust, and validated on data the engine was never tuned against. That discipline, not the underlying model, is what makes the results defensible.
Common questions

Frequently asked

How is ArtaSense different from AI visibility tools?

AI visibility tools tell you if your brand appeared in a prompt. ArtaSense runs full multi-turn decision journeys, the way people actually research, and tells you how your organization is described, when alternatives are recommended instead, which sources shape those answers, and what to change.

How do you make AI simulations accurate?

Conversation agents are grounded in real audience segment data, not invented personas. Every output is calibrated against ground truth you already trust and validated on data the engine was never tuned against.

Which AI engines do you test?

ChatGPT, Perplexity, Claude, Gemini, and DeepSeek, with coverage expanding as adoption shifts.

What kinds of organizations use ArtaSense?

Brands that want to understand how AI represents them, research and measurement firms extending their methodology into AI, agencies offering AI intelligence to clients, and sales and revenue intelligence firms helping clients see what AI said about them before any conversation reached a rep. If your audience uses AI to research, compare, or decide, ArtaSense applies.

Where we are

ArtaSense works with a focused set of organizations where the measurement problem is real. We are deliberate about who we take on. If what you've read here describes your problem, reach out.