Deploy AI revenue agents that research prospects, personalize outreach, follow up across channels, and book meetings using your inbox, contacts, docs, and calendar.
I've spent the last decade studying the line between engagement and spam across social networks.
The insight is simple... more engagement, less spam. Less engagement, more spam.
Here's the problem...
Everyone added "personalization." First name, company name, hiring signals, funding rounds. When everyone uses the same signals in the same fixed workflows, it's spam again.
The signal is dead the moment it's commoditized.
But when you share something genuinely useful about a prospect's market -- what their competitors are doing, how their landscape is shifting, what's working for their peers -- they engage naturally.
It's not a pitch. It's information they actually want.
Thinking models made this possible... Each agent spends 200K tokens researching a batch of prospects at a time -- a real research window.
It starts from a lookalike audience -- what are their peers doing, who are their competitors, what's shifting in their market. From that base, the agent autonomously decides which signal actually matters for each specific person.
The agent picks the angle.. not a fixed workflow, not a rule someone wrote.
With Cockpit.. You're the manager... Your AI agents become your highest quality team.
Give your agents a few example companies, and they go to work:
Research prospects and their competitors across the web
Decide which signal matters most for each prospect
Write outreach built around that narrative — not a template
Generate a unique proposal doc for each prospect
Track engagement (scroll depth, time on page), adapt follow-ups
Book meetings on your calendar
Imagine if one user manages 10 agents... what a team of 10 can do — across every channel, around the clock?
Since launching mid-December 2025:
102,000+ contacts researched and engaged
41,000+ personalized docs generated for those contacts
37,000+ autonomous agent conversations across email and LinkedIn (more channels coming soon)
1.7B tokens consumed — agents doing sustained autonomous work
73% average scroll depth on personalized docs
Built for deliverability... Automated email warmup, anti-spam protection, compliance guardrails, and infrastructure deployed on your company's domain — not a shared sending pool.
We use Cockpit to grow Cockpit. Our agents book our meetings. That's the credibility test — if it doesn't work for us, we have no business selling it to you.
The point about signal commoditization really resonates. As a developer, I get so many outreach messages that all follow the same template: "Hey [name], I saw your work on [project], we should chat." It's obvious when someone just plugged my GitHub profile into a tool.
The 200K token research per batch is an interesting approach. If the agent actually reads what a prospect's company does, understands their tech stack, and surfaces something genuinely relevant, that's a completely different experience from the typical cold email.
Curious: as an indie builder, is this something that scales down for small teams or solo founders? Most AI SDR tools seem built for mid-market sales teams with big pipelines. Would love to see how a one-person team could use this to do smarter outreach without it feeling spammy.
This usually looks good early, but changes once it runs at scale. Outreach quality tends to drop as volume increases, especially across channels. How this actually performs there, in terms of actual responses not just output.
The multi-channel follow-up piece is where I’d want to see more detail. When the agent is sequencing across inbox, LinkedIn, and calendar autonomously, what does the interrupt/pause model look like? Like if a prospect responds in one channel mid-sequence, how quickly does it halt the parallel threads? I’ve seen a lot of outreach automation burn leads because two touchpoints crossed each other within hours.
This resonates — we run agents for outreach too. When the model picks its own angle, can we peek at the research outline before it crafts the email so we can align the storytelling with our positioning?
I am curios to know what kind of results were your existing users able to achieve with Cockpit AI? The idea sounds good but want to know how it translates in to real world?
About Cockpit AI on Product Hunt
“Run revenue agents across every channel”
Cockpit AI launched on Product Hunt on March 27th, 2026 and earned 238 upvotes and 31 comments, placing #5 on the daily leaderboard. Deploy AI revenue agents that research prospects, personalize outreach, follow up across channels, and book meetings using your inbox, contacts, docs, and calendar.
Cockpit AI was featured in Artificial Intelligence (466.2k followers) on Product Hunt. Together, these topics include over 86.7k products, making this a competitive space to launch in.
Who hunted Cockpit AI?
Cockpit AI was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Cockpit AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
Hey Product Hunt!
I'm Ravi, founder of Cockpit AI.
I've spent the last decade studying the line between engagement and spam across social networks.
The insight is simple... more engagement, less spam. Less engagement, more spam.
Here's the problem...
Everyone added "personalization." First name, company name, hiring signals, funding rounds. When everyone uses the same signals in the same fixed workflows, it's spam again.
The signal is dead the moment it's commoditized.
But when you share something genuinely useful about a prospect's market -- what their competitors are doing, how their landscape is shifting, what's working for their peers -- they engage naturally.
It's not a pitch. It's information they actually want.
Thinking models made this possible... Each agent spends 200K tokens researching a batch of prospects at a time -- a real research window.
It starts from a lookalike audience -- what are their peers doing, who are their competitors, what's shifting in their market. From that base, the agent autonomously decides which signal actually matters for each specific person.
The agent picks the angle.. not a fixed workflow, not a rule someone wrote.
With Cockpit.. You're the manager... Your AI agents become your highest quality team.
Give your agents a few example companies, and they go to work:
Research prospects and their competitors across the web
Decide which signal matters most for each prospect
Write outreach built around that narrative — not a template
Generate a unique proposal doc for each prospect
Track engagement (scroll depth, time on page), adapt follow-ups
Book meetings on your calendar
Imagine if one user manages 10 agents... what a team of 10 can do — across every channel, around the clock?
Since launching mid-December 2025:
102,000+ contacts researched and engaged
41,000+ personalized docs generated for those contacts
37,000+ autonomous agent conversations across email and LinkedIn (more channels coming soon)
1.7B tokens consumed — agents doing sustained autonomous work
73% average scroll depth on personalized docs
Built for deliverability... Automated email warmup, anti-spam protection, compliance guardrails, and infrastructure deployed on your company's domain — not a shared sending pool.
We use Cockpit to grow Cockpit. Our agents book our meetings. That's the credibility test — if it doesn't work for us, we have no business selling it to you.
Would love your feedback!