fromHello vs Dittofeed
Dittofeed and fromHello are both open-source, self-hostable customer-engagement platforms — the same email, SMS, push, journeys, and segments, the same your-data-your-infrastructure ownership. So the usual open-source-versus-closed argument doesn't apply here; on ownership, they're peers. The difference is who operates it. Dittofeed gives you the platform and expects you to run it — you bring the growth strategist, the lifecycle marketer, the analyst, the copywriter. fromHello brings the platform and the team: eight AI specialists who set strategy, build the journeys, write the copy, and ship experiments. Dittofeed is open source you operate. fromHello is open source that operates itself.
Updated 1 Jul 2026
you want a mature, generally-available open-source engagement platform today, and you already have the growth expertise to run it yourself.
you want the same open-source ownership, plus eight AI specialists who actually run growth — so a small team doesn't have to be the growth team too.
Same ownership. One brings the team.
Dittofeed pricing, license, and capabilities reflect their public information as of 2026 — check the Dittofeed repository and dittofeed.com for current details. fromHello is in early access; rows describe the platform on GitHub today and the hosted product at general availability.
Open source you operate, or open source that operates itself.
Dittofeed and fromHello agree on the thing most tools won't give you: open source, self-hostable, your data on your infrastructure. If that's your line in the sand, both clear it — so this isn't the open-versus-closed argument the other comparisons are. On ownership, they're peers.
The difference is what happens after you deploy. Dittofeed hands you an open-source engagement platform, and you operate it — someone still decides what to test, builds the journeys, writes the emails, and reads the cohorts. fromHello runs that work: the Growth Lead sets the North Star, the Lifecycle Marketer builds the onboarding journey, the Copywriter writes every message in your voice, the analyst reads the numbers. They propose; you approve, edit, or auto-ship.
Open source like Dittofeed; run by a team like nothing else. That's the line — not open versus closed, which you can have either way, but a platform you run versus a platform that runs itself.
Where Dittofeed wins
We share Dittofeed's whole premise — open source, self-hostable, your data — so this isn't a teardown. For a lot of teams, Dittofeed is the right open-source choice today.
- It's generally available and proven as an open-source project — you can self-host and run it in production right now. fromHello's platform is on GitHub, but the hosted product and the agents are still in early access.
- It's lean and developer-first: a clean self-host story with no agent layer to learn if you don't want one.
- Its licensing is permissive (MIT), which can be easier to embed and modify inside a closed commercial product than fromHello's AGPL.
- Its managed cloud is live and inexpensive — from around $75/mo — if you'd rather not self-host at all.
Both free to self-host. One brings the team.
Neither charges you to self-host — clone the repo, bring a server, own the stack. Dittofeed's managed cloud is generally available from around $75/mo; fromHello's hosted version arrives at GA. So the price difference was never the platform — it's what runs it. Dittofeed is the engine and you supply the drivers; fromHello includes the eight specialists who drive.
fromHello — self-host free, hosted pricing at GA; the eight agents are included.
Dittofeed — self-host free; managed cloud from ~$75/mo. You operate it.
What teams ask before they move
Yes — and that's the point. Both are open-source, self-hostable, and keep your data on your infrastructure. On ownership they're peers, so the open-versus-closed argument doesn't separate them. What separates them is the team: fromHello adds eight AI specialists who run the platform; Dittofeed expects you to.
Put your growth teamon autopilot.
Early access opens gradually, so the team tunes to real use cases. Small teams with big ambitions go first.
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