1 credit

Recruiter Outreach Message

One message to one person, built around a specific role and something you have actually done. LinkedIn notes are held to the platform's 300-character limit, and the recipient's name never leaves our servers.

  • 1 credit per run
  • 20 free credits at signup
  • One free run every day
Free to start

20 credits when you sign up - 20 outreach messages

Nothing to install and no subscription. A verified account starts with 20 credits, five more for completing your profile, and re-running an identical input costs nothing at all - we recognise it and charge you nothing.

Draft my messageOr try a free tool, no signup

The run needs an account because it spends credits, and the credits are what pay for the AI call. The keyword extractor beside it needs no account and never will - it makes no external call, so it costs us nothing to run.

credit a run
1
runs on the signup grant
20
kinds of message
3
recipient names sent to the model
0
What a run needs

Who you are writing to, and what you have to offer them

Four short answers. The recipient's name is optional, and if you give it, it is the one thing on this page that never leaves our servers.

What you give it

  1. Which kind of message: LinkedIn connection note, Referral request, Intro email.
  2. The role you are writing about.
  3. A couple of lines about yourself, or your profile resume.
  4. Optionally the recipient's first name.
1 credita run

New accounts start with 20 credits and five more for completing a profile, so your first runs are covered. Re-running the same input is free - we recognise it and charge nothing.

I agree that the text I have entered is sent, with names and contact details removed, to an AI model hosted outside India, to generate this result.

The guarantee

The recipient's name never reaches the AI provider

If you tell us who you are writing to, that name is not in the request we send onward. The prompt carries the token [RECIPIENT] and the real name is substituted back in on our own servers, after the draft comes back.

This matters because of what a cold message is: a named third party who has not consented to anything being sent to a model outside India. Redacting your own details and then forwarding theirs would be a strange kind of privacy.

A LinkedIn connection note is also held to a hard 300 characters - LinkedIn's limit, not ours. We check the draft against it after the name goes back in, and ask for a shorter one if it overruns. On the rare draft that is still over, we show the count in red rather than quietly cutting a sentence in half.

Sample output · invented data

A real first message, before you spend a credit

Example output on invented data. Nothing here is a real resume, person or company. Everything inside the window is the component the dashboard renders - not a screenshot, and not a trimmed version of it.

LinkedIn connection note287 / 300 charactersto Meera
Hi Meera - I saw the Senior Backend Engineer opening on the payments platform. I spent the last four years on settlement infrastructure and cut a nightly batch from four hours to forty minutes by moving reconciliation onto Kafka. Happy to send specifics if it is useful.

Meera's name was never sent to our AI provider. The draft was generated against a [RECIPIENT] placeholder and the name was substituted back in on our own servers.

There is no score. A cold message either gives the reader a reason to reply in the first line or it does not, and scoring that out of ten would be inventing precision.

End of the sample report. Everything below this line is the page's own copy - what we do with your text, and the questions people ask before pasting one in.

Draft mine

Not ready for an account? Extract keywords from a job description is free forever and needs no signup - it makes no external call, so it costs us nothing to run.

Try it free

What happens to your data

Your text is redacted before it reaches any AI model: name, email, phone, address and date of birth are replaced with tokens first. The model reads your document and writes the explanations; it never chooses a number - every score is arithmetic over a fixed rubric in our own code. One input to that arithmetic is the model's reading of which skills you evidence, so we store your result and re-running the same input returns it rather than a fresh one. We never invent a figure your own material does not contain.

Credits are a licence to use these tools - not money, not transferable. Full detail in our privacy policy and AI policy.

How this works

About Recruiter Outreach DM

What it checks, what it deliberately does not, and how to read the output.

Three channels, because they are three different messages

A LinkedIn connection note has a hard 300-character limit set by LinkedIn, so it has room for one specific fact and an ask. A referral request goes to somebody who already works there and has to ask without assuming they owe you anything. An intro email needs a subject line, because an email without one does not get opened.

Nothing is pre-selected. Guessing on your behalf would quietly hand you a 300-character note when you meant to send an email, and the draft is not interchangeable between the three.

The recipient's name never reaches the AI provider

If you tell us who you are writing to, that name is not in the request we send onward. The prompt carries a [RECIPIENT] token, and the real name is substituted back in on our own infrastructure once the draft returns.

This matters because of what a cold message is. The person you are writing to is a named third party who has not agreed to anything being sent to a model outside India. Redacting your own contact details and then forwarding theirs would be a strange sort of privacy, so we do not.

One recipient, and no bulk version - ever

There is no field for a second name, no CSV upload and no campaign mode, and there will not be. A tool that drafts one message to one named person about one specific role is outreach. The same tool pointed at a list is a spam engine, and the difference between them lives entirely in the interface.

The message quality depends on this too. What makes a cold message get a reply is that it obviously could not have been sent to anybody else - one real result, one named role. That property is destroyed by scale, so building for scale would break the thing that makes it work.

What this tool will not do

It will not find recruiters for you. There is no contact database here, no email lookup and no scraping. You bring the person; the tool writes the message.

It will not exaggerate your background. Everything the message says about you comes from the couple of lines you write or from your profile resume, and where there is nothing to say, the draft says less rather than more.

It will not send anything. The output is text you read, edit and send yourself, from your own account, which is also the only version of this that is honest.

FAQ

Questions people actually ask

The ones that come up before somebody uploads anything.

Is the recipient's name sent to an AI provider?

No. The draft is generated against a [RECIPIENT] placeholder, and the real name is substituted back in on our own servers after the response returns. The person you are writing to is a named third party who has not consented to anything being sent to a model outside India, so forwarding their name while redacting yours would be a strange kind of privacy.

Can I generate messages for a list of recruiters?

No, and this will not change. There is one recipient field, no upload and no campaign mode. A tool that writes one message to one named person about one specific role is outreach; the same tool pointed at a list is a spam engine, and the difference is entirely in the interface. It would also make the output worse, because what earns a reply is that the message obviously could not have been sent to anyone else.

Why does the LinkedIn note have a character limit?

Because LinkedIn does. Connection notes are capped at 300 characters, so a longer draft would simply be rejected by the site you are pasting it into. We count the draft after the recipient's name goes back in, and ask for a shorter one if it overruns; if a draft is still over after that, the count turns red and tells you rather than cutting a sentence in half on your behalf. The limit is a useful constraint anyway: 300 characters has room for exactly one specific fact and one clear ask, which is what a good cold note contains.

What should I put in the background field?

One or two specific things you have done, not a summary of your career. "Six years on payment systems, rebuilt a settlement service and cut the nightly batch from four hours to forty minutes" is far more useful than "experienced backend engineer with a passion for scalable systems". Everything the message claims about you is drawn from this, so specificity here is what makes the draft worth sending.

Will the message look automated?

That depends mostly on your input, which is the honest answer. The draft avoids the usual tells - it does not open by praising the company, and it does not describe you in adjectives. But a message built from a vague background will read as vague. Give it one real result and it will produce something that could only have been sent by you.

Next, try one of these

More from Resume & Profile, or browse the full catalogue.

2 credits

AI Resume Analyser

Readiness Score out of 100, every deduction explained

ResumeOpen
Free

ATS Resume Checker

See exactly what a parser reads from your file

ResumeOpen
3 credits

JD ↔ Resume Match

Tailor your resume to one specific job description

ResumeOpen
Paid serviceResume Review from ₹299Read nextGuides on resumes, interviews and offers
When a tool is not enough

Get a human to rebuild it

Every automated check has a ceiling: it can tell you a bullet has no number in it, but it cannot decide which of your projects is worth two lines and which is worth six. A Revquix resume review is written by a person who hires for your target role.

Resume Review from ₹299