A message can fail a hundred ways.
One wrong line and you've left a trail of half-read pitches in a guest's DMs. The opportunity is done before the draft even made sense.
We booked guests from these companies, one researched pitch at a time.
If you can spot an AI-generated pitch, why would you assume your dream guest can't? Hadef is for hosts of interview-style B2B shows. It finds the angle nobody has asked your guest about, at scale.
Hadef puts research, context, and the first draft in one place so your team can focus on the conversation.
One wrong line and you've left a trail of half-read pitches in a guest's DMs. The opportunity is done before the draft even made sense.
Keeping an AI co-pilot current on every podcast, article, LinkedIn post, and Substack your guest ships is tedious. Finicky. Usually stale the day you use it.
You want a pitch with nuance. LLMs without the right APIs can't reach voice-only transcripts, hit context limits, and stall on the searches that actually matter.
It is easier than ever to write a pitch and harder than ever to land one, because every host's inbox is full of pitches that read the same. You paste a LinkedIn URL. Hadef AI reads your show as closely as it reads your guest, then finds the one overlap nobody else has pitched. What you send is specific enough to be un-ignorable.
Speak it, type it, drop a link. Five minutes once, then Hadef surfaces your context every time you sit down to pitch the next guest.
You paste a LinkedIn URL. Hadef AI does the first two. The third is yours. Each one earns the next.
Start from a verified public source.
Hadef ingests your guest's public record, including full transcripts from episodes that were never publicly transcribed. Your pitch can open with a line they said to an audience of two hundred. That is homework no general model can pull from training data.
Start from a verified line, then make it your own.
Which starts with a thread your guest has been pulling on that nobody else has picked up.
You don't want to seem salesy. Hadef drafts the first sentence around a real overlap: something the guest has just said in public, a gap in your show's recent arc, a timing trigger that makes the conversation feel inevitable now. The reader opens the message, and the archive door doesn't close on you. Vendors write the other kind of email.
Hey guest name, noticed your interview in publication where you said hook quote. Would love to dig deeper…
The pitch lands in your LinkedIn composer in your voice, with verified titles and risk-audited questions, so the guests who say yes leave willing to recommend you. You hit send, and the pipeline holds who you pitched, when they replied, and which angles convert.
Every tier runs the same research and the same QA. What changes is the number of pitches and what you can plug it into.
All plans include the Show Brain, golden-thread pitches, multi-channel send, and the QA layer. Cancel any time. Annual plans save 20%.
Every pitch passes a QA layer that verifies the quote against the source URL and flags anything that doesn't check out. You see the verification before you send.
Other tools tell you they keep humans in the loop. We tell you exactly where: at send.
This is what happens when the pitch is built around what your guest has actually said.
