Migma AI - AI runs your email marketing. Better with every send.
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Migma creates full campaigns before you ask. It understands your goals and events, creates every email, personalizes and localizes it, and renders consistently across inboxes. It handles sending, preferences and compliance, then learns what drives revenue.
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LETS GOOOOO!
@yahia_bakour3 yoo, please watch your APIs, we may burn your servers.
@yahia_bakour3 Yahiaaaa 🤗
the "learns what drives revenue" part is the interesting bit to me - how does it attribute revenue back to a specific email when someone gets touched by 3-4 emails in a sequence before converting? that's usually where email attribution gets messy even for humans doing it manually.
@omri_ben_shoham1 You're right, when someone gets 3-4 emails before buying, giving one email the credit is guesswork. So we don't force it onto a single email.
We track which emails a person actually clicked, and spread the credit across those, leaning toward the ones they engaged with most. Opens we mostly ignore since Apple Mail fakes a lot of them.
The part we really trust is the pattern across lots of sends, not one person's path. If the day-3 email with one subject line keeps showing up before people buy, and another version doesn't, that tells us something real even when any single journey is messy.
That's the math no one has time to do by hand.
Best way to judge it is to see it live. Would love for you to try it.
How does Migma handle email deliverability and domain reputation when sending campaigns from a connected custom domain?
@shahriardgm Great question 🙌
When you connect your own domain, Migma handles setup and warmup for you, so it ramps up gradually and lands in the inbox instead of spam, meeting all the checks that actually help conversion along the way.
If you don't have a domain yet, you can send straight from Migma with a shared address, no setup needed. Or you can buy a new domain right inside Migma at an affordable price.
Come connect yours and try a send, would love to hear how it lands for you 📬
Congrats on the launch! Migma’s focus on the full email workflow, from planning to rendering and compliance, feels much more practical than just another AI copy generator. I’m especially curious about how the system learns from approvals, edits, and skipped sends over time. How quickly does it adapt to a brand’s tone and sending judgment?
@glebarios Thanks so much, this means a lot 🙏
Brand tone comes from what you feed it (your assets, guidelines, past campaigns) and it keeps refining that as you approve, edit, or skip sends, so the more you use it the closer it tracks how you actually write and what you're okay shipping.
Performance also feeds straight back in: opens, clicks, what worked, what didn't, all shaping the next campaign automatically.
Come try a few campaigns and you'll feel it get sharper send over send 📬
The auto-generated campaigns idea is genuinely cool, but I'd love to see a side-by-side preview showing how each email renders across Gmail, Outlook and Apple Mail before I hit approve. Would save me from those surprise layout breaks on Outlook especially.
@nihaln20560 Love this, and good news, we already have it 🙌 Preflight shows client previews (Gmail, Outlook, Apple Mail, dark mode, and more) before you approve, so you catch any Outlook weirdness before it goes out, not after.
Come check it out for free.
One thing that would really help me is a side-by-side preview of how the email looks across different clients like Gmail, Outlook, and Apple Mail before I hit approve. It would save me from those surprise layout breaks that always seem to pop up after sending.
@yiitqx9x Our engine already renders every email to match across clients properly, so the base is solid before anything else kicks in.
On top of that, Preflight lets you preview it on real devices and clients before you approve, so you catch anything before it ships.
Try it here for free: https://migma.ai/email-html-spam-checker
Direct emission is the ambitious version of this, so I'm curious what catches a bad token. When we tried it we ended up with a validate-and-retry loop, and roughly 1 in 12 generations needed a second pass, which is fine for a background job and painful when someone is sitting there waiting. Are you constraining the decode with a grammar, or letting it write freely and repairing after?
@dipankar_sarkar The model writes Zinn directly instead of HTML, that's what keeps it fast and consistent across clients.
Come try it see how its super fast
The line that stands out to me is that your first campaign should never be as good as your last. That learning loop is the real moat here, even more than the rendering work everyone is asking about.
My angle is the awkward one for it: I run email to a small, high-value B2B list in healthcare, a few hundred serious buyers rather than a consumer list. There a tone-deaf automated send costs a relationship I cannot re-earn, and the revenue signal comes back slow and sparse.
So, Adam, does the learning loop need consumer volume to work, or can it improve on thin data, where the win is one right email a month rather than a tuned high-frequency cadence?
@clemente_lopez1 No. Volume makes the loop faster, but it is not required.
For a small, high-value list, the useful signals start before opens or purchases: what you approve, edit, reject, who you choose to send to, and when you decide not to send.
Migma should become more conservative in that setting, not more autonomous. It prepares the campaign, learns your judgment, and you keep approval before anything goes out.
The goal is not more sends.
It is one email a month that sounds like you, lands at the right moment, and does not burn a relationship.
@adam_lab treating my edits and my skips as the training signal is the part that lands, because on a list this small those are the only signals I generate in a month anyway. Opens and clicks are too sparse to learn from.
The one that would decide it for me is the skip. If Migma reads a no-send as a real signal and not as missing data, it is learning my judgment instead of just my approvals. Does a repeated skip on a certain kind of prospect actually pull the model back, or does it only learn from what I let through?
Congrats on the launch - really cool idea and looks to be a very smooth product. I have to ask, if clients have all their contacts and operations inside another CRM (think Zoho or GoHighLevel) that currently send their campaigns, how does it work? My clients would be keen to keep their core CRM systems running without having to duplicate data into a specialized email tool.
@danielboardman Thanks, really appreciate that 🙌
Your clients can keep Zoho, GoHighLevel, or their current CRM as the core system. Contacts are imported or synced into Migma through native integrations, connected ESPs, or API/webhooks, depending on the setup.
So there’s no need to move the rest of their operations. Migma handles the campaign workflow, while the CRM stays the main source of truth.
Would love for you to try it with one of your client setups and tell us how the workflow feels.
How much does it actually learn between sends? Like if a campaign flops, does it adjust the next one right away or does it need a few cycles to figure out what works?
@talhakhalidmtk Nice question! Migma already has quality and deliverability standards built in from day one. On top of that, there's a layer that checks how your past campaigns performed, and it keeps getting sharper the more you send.
Fewer sends means less for it to learn from, so the real gains show up once you're sending consistently and it locks into your brand and audience.
Come give it a try 📬