AI personalization
AI personalization that reads like you spent ten minutes on each profile
ReachPods’s AI reads each prospect’s headline, about section, latest post and company, then writes the invitation note, message, email or comment for that one person, in their language, within the channel’s limits, with your template as a safety net.
Lena Fischer
Head of Growth · Loopwise
AI read
- • Post: onboarding 14 → 3 days
- • Team of 45, Series A
- • Writes in German & English
- • Hiring 2 SDRs
Your template
Hi {{first_name}}, {{ai.icebreaker}} We help SaaS teams book more meetings…
Written for Lena
Hi Lena, cutting onboarding from 14 to 3 days is the kind of number most growth teams only promise. With two SDRs joining, we help teams like Loopwise book more meetings across LinkedIn and email…
- message types it writes
- 8
- reusable AI variables
- {{ai.*}}
- language from the profile
- Auto
- monthly AI budget limit
- $ cap
Overview
Personalisation that scales without sounding like a robot
Everyone knows Hi {{first_name}}, I came across your profile isn’t personalisation. Real personalisation is mentioning the post they wrote on Tuesday, the expansion their company announced, the thing in their about section that nobody else noticed. It works, and it takes ten minutes a lead, which is why almost nobody does it.
ReachPods does that research for you. When a step is about to run, the AI gets a snapshot of the lead: headline, current role, about section, recent activity, company industry and size, plus anything you imported. It also knows what you do: your company context, how you introduce yourself and the tone you prefer. Then it writes the message for the exact channel and step it’s in, aware of what earlier steps already said.
If anything goes wrong (the model times out, the profile is empty, the monthly budget is reached), the step quietly falls back to your template. The sequence never stalls because of AI.
AI variables
Define an AI variable once, use it in every template
Sometimes you want your own words with one AI-written line in the middle. AI variables do exactly that. Create a variable, say icebreaker, with a prompt such as “In under 10 words, name something specific {{first_name}} recently did”. Then use {{ai.icebreaker}} in any invitation, message, email or WhatsApp template.
Each variable is generated once per lead and step, then reused for retries and reviews, so you never pay twice for the same line. Add a fallback with a pipe, {{ai.icebreaker|your work}}, and leads with thin profiles still get a sentence that reads naturally.
Prompts can use any lead field, including {{about}}, {{industry}} and {{company_size}}, which are filled automatically when the profile is visited or synced.
- Workspace-wide reusable variables
- Generated once per lead, then reused
- Fallback text for thin profiles
- Prompts can reference any lead field
AI variable · {{ai.icebreaker}}
Template
Write one sentence referencing their most recent post or a concrete company fact. Max 25 words. No flattery.Rendered for Marco Rossi
Hi Marco, Stackly shipping its EU data residency last month must have opened a lot of doors. We help…Smart comments
Comments that add something, not “Great post!”
Comment steps on LinkedIn and Instagram can use smart comments. The AI is given the prospect’s latest post and the comments already on it, and asked for one or two sentences that react to something specific: agree with a concrete point, add a thought, or ask a curious question.
Smart comments are told never to pitch, never to mention a meeting and never to repeat what others already said. The result is a comment people actually reply to, from an account they’ll recognise when your invitation arrives a few days later.
- Reads the post and existing comments
- No pitching, no meeting asks
- One or two sentences
- Works on LinkedIn and Instagram
Comment on Lena’s post
Template
Post: “We cut onboarding from 14 days to 3. Here’s what we removed…” · 38 commentsAI comment · adds a question
The part about deleting the kickoff call is underrated. Did activation hold up once the call was gone?Guardrails
Previews, review and a budget you control
Every channel has a hard length: 300 characters for a LinkedIn invitation note, a few hundred for DMs, more for emails and InMails. The AI writes to that limit, and the limit is enforced, so a note is never cut off mid-word.
Preview any AI step for any lead before launching, and regenerate it until you like the direction. Want a human to approve every message? Turn on review for a step, and AI messages wait in a queue where you can edit, approve or skip them before they go out.
Set a monthly AI budget for the workspace. When it’s reached, steps fall back to your templates and no more AI calls are made until next month. You choose the tone (friendly, professional, casual or direct), the language (or auto, the prospect’s own language) and, if you want, the model.
- Channel-aware length limits
- Preview and regenerate per lead
- Optional human review queue
- Monthly spending cap with template fallback
- Tone, language and model settings
AI
Guardrails
Require approval before sending
Fall back to template on failure
Monthly AI budget
$12.80 used
- $40
Tone
- Friendly, concise
Language
- Match the lead
How it works
AI personalization: how it works in four steps
- 1
Describe your offer
Add your company context and how you introduce yourself. This is the most important input for relevant messages.
- 2
Turn on AI for a step
Enable AI on a message, invitation, email or comment step and add instructions, or add AI variables to a template.
- 3
Preview on real leads
Generate previews for a few leads, regenerate until the tone is right, and set a monthly budget.
- 4
Launch
Each lead gets its own message at send time, with your template as the automatic fallback.
Who it’s for
AI personalization: who it’s for
High-ticket B2B
Where every meeting is worth thousands, a message that references their latest post is worth every cent of AI cost.
Multilingual markets
Prospects in France, Germany and Spain each receive a message in their own language from the same campaign.
Teams with brand rules
Turn on review for the first step so a manager approves AI messages before they go out, then relax it once trust is built.
FAQ
AI personalization: questions and answers
Something else on your mind? Get started and try it on your own accounts.
Which AI model is used?
A strong default model is used out of the box, with automatic fallbacks if it is unavailable. You can choose a different model in the workspace AI settings.
What does the AI know about each lead?
Their LinkedIn headline, role, about section, recent activity and company details when available, plus every field you imported and the earlier messages in the same sequence.
What if a profile has almost no information?
The AI is told to stay generic rather than invent details, and AI variables can carry a fallback value. If generation fails, your template is sent instead.
Can I approve messages before they are sent?
Yes. Enable review on a step and AI messages wait for approval, editing or skipping.
How much does it cost?
AI generation uses your workspace’s monthly AI budget. Set the cap yourself; when it is reached, steps fall back to templates until the next month.
Does it write in other languages?
Yes. Pick a fixed language or “auto”, which writes in the language of the prospect’s profile.
Platform
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