The best AI reply app depends on whether your problem is volume or stakes

“What’s the best AI reply app” is a question with four different right answers, and the person asking usually only wants one of them.

I went through the category properly, partly because I build in it. Subtext is mine, it shows up in the fourth group below, and you should weigh everything I say about it accordingly. The other three groups I have no stake in at all, which is most of this article.

The useful thing I found is that these tools barely compete with each other. A sales sequencer and a tone checker both get filed under “AI reply app” and they are not alternatives in any meaningful sense. One is trying to move a pipeline. The other is trying to stop you sending something at 11pm that you cannot take back.

So the first question is not which app. It is which of these two problems you have: too many messages, or one message that matters too much.

The four categories

Email triage is for volume. Superhuman, Shortwave, Agentys. The unit of work is the inbox, and success is getting to zero faster.

Outbound sequencing is for pipeline. Reply.io, GoExtrovert, Skywork AI. The unit of work is the campaign, and success is a booked meeting.

Support and DM automation is for coverage. Instant Reply, Vellum. The unit of work is the queue, and success is that nobody waits.

Relational calibration is for stakes. This is the one I work on. The unit of work is a single message, and success is that it lands the way you meant it.

Notice that only the last one cares what any individual message says. The first three are logistics.

Email triage: Superhuman, Shortwave, Agentys

If your problem is four hundred emails and a Tuesday, this is your row.

Superhuman is built around a latency promise: no interaction should take longer than about 100 milliseconds. Keyboard shortcuts, split inboxes, fast triage. Its AI drafting comes through Grammarly, since both now sit under the same parent company after the Superhuman rebrand. It optimises how fast you can process mail yourself, rather than handing the processing off. Somewhere around $30 to $40 a month depending on plan.

Shortwave goes the other way. It is Gmail only, and it leans on an assistant that can search years of archive in plain language, summarise long threads, and run saved workflows. Where Superhuman makes you faster, Shortwave tries to read the thread for you. Roughly $14 to $24 a month.

Agentys solves the part that stops most people switching, which is that you have to switch. It works inside Gmail, Outlook and Microsoft 365 as they already are, generating draft replies in your own trained voice inside the inbox you already use. About $17 a month.

The honest split: Superhuman if you like keyboards, Shortwave if you want the machine to do the comprehension, Agentys if the migration is the blocker.

Outbound: Reply.io, GoExtrovert, Skywork

If your problem is pipeline, none of the above helps and neither does anything in the last two sections.

Reply.io runs autonomous outbound agents that research a prospect, sequence across email, LinkedIn, SMS and calls, sort the replies that come back, and put meetings on a calendar.

GoExtrovert replaces the fixed sequence with something that watches for signals, tracking prospect posts and generating suggested comments and messages in your voice, with a human approving before anything sends. That review step is the point: it is what keeps a LinkedIn account from looking automated.

Skywork AI does research before drafting, reading documentation, filings and market material, then producing formatted cited documents rather than plain text. It is aimed at formal proposals more than at cold email.

Support and DMs: Instant Reply, Vellum

If your problem is a queue that never empties, this row.

Instant Reply is built for social commerce, so Instagram, Messenger and WhatsApp Business. Two details stood out. It transcribes inbound voice notes, which the company says are around 30% of WhatsApp inbound, and it runs several AI providers behind a failover so an outage somewhere upstream does not take the queue down. That second one is unglamorous and probably the reason people keep it.

Vellum is an open source personal workspace that spans desktop, mobile, voice, Slack, Telegram and email, keeping memory across all of them so a follow-up three weeks later still knows what was said.

Why general chatbots struggle with the fourth category

The first three categories are well served by general models, because the job is throughput and a competent generic sentence is fine. The fourth is where it gets awkward, and it is worth being specific about why rather than hand-waving at it.

A general model writes the most probable next thing. For a status update that is exactly right. For a message where you are trying to hold a boundary without sounding cold, the most probable next thing is a wordy, over-apologetic, slightly performative paragraph, because that is what the internet is full of.

Three failure modes show up repeatedly. Models make implicit things explicit, so the thing you deliberately left unsaid gets said. They smooth the rhythm out, so the result is coherent and characterless. And when the topic is conflict, they over-explain and over-apologise by default.

There is a second problem, which is effort. Getting a general chatbot to write a difficult personal message well means describing the relationship, the history, the tone you want and the thing you are afraid it will sound like. That is a lot of typing at the exact moment you are least able to think clearly. I wrote about the research on that at more length in what AI actually knows about the tone of your messages and in the piece on AI message rewriters.

The fourth category, where I am not neutral

This is my product, so read the next few paragraphs as an argument rather than a review.

Subtext starts from your draft rather than from a prompt. You paste what you already wrote, or a screenshot of the whole thread, or a voice note where you talk it out. It reads the exchange, not just your line, then tells you how the draft is likely to land and which words are doing it, before it offers to change anything. There is a “safe to send” score, which is a real percentage rather than a label, and a short explanation of what could be misread when it comes back low.

For messages that matter it stops and asks what you actually want to get across, rather than guessing between holding a boundary and smoothing things over, because those produce genuinely different messages. Adjustments are one tap rather than a prompt: warmer, shorter, more casual, add humour, add confidence. And you get a few directions side by side instead of one answer, which is a faster way to find out what you meant than describing it in advance.

It works in fourteen languages, natively rather than translated. It never sends anything for you, which is deliberate. And the privacy posture matches the content: nothing trains a model, conversations delete themselves after five days unless you pin them, and deleting something removes it immediately.

When not to use it. If your problem is four hundred emails, go back to the first section. If your problem is pipeline, second section. If your problem is a support queue, third. Subtext is built for one message at a time, which is the correct tool for exactly one of the four problems on this page and the wrong tool for the other three.

A note on where these numbers came from

Worth saying plainly, because it changes how much weight to put on the rest.

Almost everything in the first three sections comes from vendor documentation, vendor blogs and comparison sites that run affiliate programmes. That is not the same as testing. Prices move, and several of the figures above appear only in the vendor’s own material. The 30% voice note figure is Instant Reply’s own. The latency promise is Superhuman’s own. I have flagged them as such rather than laundering them into facts.

I have not run these tools head to head, and I would not trust anyone who claims they have across all four categories, because the categories do not share a success metric. There is no benchmark on which a sales sequencer and a tone checker can both score.

Which one

If you are drowning in email, Superhuman or Shortwave, or Agentys if you refuse to leave your current inbox.

If you are running outbound, Reply.io for multi-channel sequences, GoExtrovert if LinkedIn is the channel and you want a human approving each one.

If you are running a DM queue, Instant Reply for social commerce, Vellum if you need memory across channels.

If the thing keeping you up is a single message to a person who matters, that is the category I build for, and I would rather say that plainly than pretend I arrived at it neutrally.

The mistake I would most want to save you from is picking from the wrong row. A tone checker will not clear your inbox, and a sequencer has no opinion about whether your message sounds cold. They answer to the same name and solve unrelated problems.

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Think I have miscategorised a tool, or know one that belongs in a row it is missing from? Tell me on LinkedIn.

Samet Durgun is the co-founder of Subtext, an app that catches the emotional tone of your messages and rewrites them in your own voice. He’s based in Berlin.

Sources

Prices and features checked August 2026. Where a figure comes from a vendor rather than an independent test, the text says so.

1. Superhuman, product and pricing pages. superhuman.com
2. Shortwave, product and pricing pages. shortwave.com
3. Agentys, product pages and the Superhuman comparison written by Agentys. agentys.io
4. Grammarly, “Grammarly Rebrands Company as Superhuman.” grammarly.com
5. Reply.io, Jason AI product pages. reply.io
6. Skywork AI, message generator guide, published by Skywork. skywork.ai
7. Instant Reply, AI customer support comparison, published by Instant Reply. instantreply.co
8. Vellum, best AI tools for lead capture, published by Vellum. vellum.ai
9. Subtext, official site. subtext.it
10. Subtext, terms, privacy and your account. subtext.it