Launched this week
MailAdept by mailwarm
AI Agents & Email deliverability experts on your team
370 followers
AI Agents & Email deliverability experts on your team
370 followers
Email deliverability on autopilot. A subscription-based, AI-native email deliverability service where AI agents and human experts work as an extension of your team to audit your infrastructure, fix issues, monitor email health daily, and improve inbox placement with weekly reporting.
Deliverability genuinely needs an owner, the framing makes sense :) But picking up Curious Kitty's thread: the answers here list what you monitor (DKIM, blacklists, metrics), not how you know the placement number is real.
Gmail and Outlook never tell you if a real recipient hit Primary, Promotions or Spam. So placement usually comes from seed lists, the least representative inboxes there are: they never open, reply, or rescue you from spam. You can read "95% inbox" on the panel and still land in Promotions for the humans who matter.
So: what's actually behind the daily signal, seed panels, Postmaster, real engagement telemetry? And when the panel says green but the leads say spam (like Anas described above), which do you trust?
Congrats on the launch! ;)
Deliverability being nobody's job is the hidden killer. Every founder I've talked to who runs cold email eventually finds out that "we have SPF and DKIM configured" doesn't mean their emails are landing anywhere useful.
Real setup for what it's worth, running 3 warmed domains, 9 mailboxes, mid-launch prep. What I keep learning the hard way:
1) Warmup networks warm you up to other warmup networks. Auth clean, Mail-Tester 10/10, no blacklists, 57% Gmail inbox on first real test. The warmup graph and the real Gmail graph are not the same graph, and no dashboard tells you that.
2) The metrics that predict inbox placement don't show up until they're already broken. By the time reputation drops, you've already sent to a batch you'd like back.
3) The move that changed the most for me was reducing volume even after warmup looked "done." Sending fewer, better-targeted emails from a warm domain outperforms sending more from a "fully warmed" one.
Honest question, what's your take on the tradeoff between adding a deliverability service like MailAdept vs. just sending less volume? I'm trying to figure out if the fix I've been reaching for (throttle everything) is a real fix or a compensation for infrastructure I should be paying someone else to own.
Mailwarm
Hi Product Hunt,
After getting experience from @Mailwarm, the warmup deliverability tool. @mailX by mailwarm the free email deliverability toolkit for humans and AI agents to check and fix your deliverability.
We decided to launch @MailAdept by mailwarm the email deliverability agency, so we can use all our experience to make sure you land in the inbox. Coming from the software industry we worked on service and pricing to adapt to the target and made it subscription based.
So basically for a flat monthly subscription you get our expert deliverability expert on your team :)
I hope you will like it
We live in an interesting world. I wonder how long it will be before this turns into a battle between AI agents writing and sending emails and AI agents setting increasingly strict inbound filters - with absolutely no human involved in the process. Or are we already there?
Mailwarm
@julia_shtogren It does feel like we're heading in that direction...
In many ways, we're already seeing the early stages, AI is helping create and send emails, while mailbox providers are using increasingly sophisticated machine learning to decide what reaches the inbox.
That said, deliverability is still ultimately about earning trust. No matter how smart the AI gets, good sending practices and relevant emails will always matter ;)
@naimz Yeah, I think a thoughtful approach is always valuable :) And I'm curious - what fields of life will humans of the future keep for themselves? It's quite unsettling to see how eagerly people disconnect from any process. A lot of "automation for automation's sake" is happening right now. But I think it will evolve into something more reasonable - more specific use cases that actually work.
Mailwarm
@julia_shtogren I agree. I think we're still in the phase where everyone is trying to automate everything because it's suddenly possible.
Over time, I suspect we'll become much more selective. The best use cases will be the ones where AI handles repetitive work, while humans focus on judgment, relationships, and decisions that require context. That's very much the philosophy behind MailAdept we use AI to scale monitoring and analysis, but we keep humans in the loop where experience and nuance matter.
How does the pricing actually scale as the list grows, and does the weekly reporting give concrete next steps or just charts?
Curious how this works with custom transactional sending setups, especially if we already have our own DKIM/SPF records in place from years ago. Would the audit just confirm whats working or actually help us rethink the whole infrastructure setup?
How does the AI actually decide when to escalate something to a human expert versus handling it on its own?