Zeer
TarsTars
Buying intent
8 tracked signals | Top 6 topics are below | Marketing is carrying most of it.
Attention by team
LinkedIn activity, by teamWhere Tars's own people are actually spending their attention, by team, by topic. Bands run Low to High against the busiest pairing on this page, and each cell also shows how much of that team's own activity it represents.
Topics being researched
30-day windowEvery tracked topic, ranked by volume, not by our guess at what matters. Confidence is the classifier's own certainty that a signal belongs where we've filed it.
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Need intent for a specific topic or industry?
We track the full taxonomy across every account in the graph — including themes not shown on this page.
Who's active at Tars
verified title on fileTitles, seniority and topic straight from each person's own activity, with a LinkedIn link so you can check any of them yourself.
Primary products / business lines
LinkedIn company profileTars empowers businesses to build AI agents that automate internal tasks and enhance customer experiences—without any coding. Our intuitive platform allows non-technical users to create AI-powered agents that streamline workflows, boost efficiency, and drive meaningful customer interactions. With Tars, anyone can design and deploy AI agents that handle customer inquiries, process internal request
Top accounts researching Tars
names withheld on the public pageThese are companies whose own people brought up Tars unprompted, not accounts we guessed might be interested. We can't yet tell an implementation partner from a genuine buyer here, names unlock along with the buyer profile below.
1,154 companies · 3,008 people are researching Discovery Call
Tars's own team shows 2 signals on this topic. No one outside Tars has been seen researching the company by name yet — so this is the market it sits in, not a list of its buyers.
- Negotiation9,499 cos · 32,049 people
- App Store2,438 cos · 7,284 people
Buyer profile
company size · seniorityCompany size and how senior the people involved are, the two things that decide whether this is a real deal. Competitor overlap isn't computed yet for this account.
Buying committee functions
Employee job titles (LinkedIn)Customer Success — 1 person; Engineering — 1 person; Marketing — 1 person
What's been said
public posts by Tars's teamNo public post naming Tars has surfaced in the past year, so this is what Tars's own team is posting about publicly — their topics, in their words.
A VP of Customer Success once told me on a call: "If the bot sucks, people will try it once and abandon." Then she said something most AI companies will never quote back to you: "If I can open a case or email somebody and get a better response, I will continue to do that." Both of those customers - the one who abandoned and the one who quietly went to email - count as "deflected" in her old chatbot's dashboard. That's the problem with deflection rate. It measures one thing: of the people who reached support, how many didn't reach a human. No CSAT. No resolution. No "did the customer actually get their answer." This is why "90% deflection" is the most misleading number in AI customer support right now. Your bot can hit it while your support team quietly absorbs every failure through a different channel. The metric you should be measuring instead is in the full video - I have added the link in the comments.
May 2026