Your AI agent WorkingJemma will write every message in your voice.Head of Outreach
Personalization

Personalization that goes beyond first names

Astel builds a rich profile for every investor (thesis, portfolio patterns, recent posts, red flags) and weaves that context into every message so it lands like a founder-to-partner note.

  • Investor dossier: One page with everything: thesis, checks, portfolio, activity, quirks.
  • Thesis-aligned pitch: Reframe your one-liner per partner so it speaks to what they invest in.
  • Recent-signal hooks: Reference their latest post, panel, or portfolio move, automatically.
  • Voice-preserving: Personalization in your voice, not generic AI slop.
  1. 1
    Pick an investor

    Load the target partner or fund.

  2. 2
    See the profile

    Astel compiles a real dossier, not a LinkedIn scrape.

  3. 3
    Send the perfect message

    AI-drafted, thesis-aligned, and unmistakably tailored.

Have a sniper approach when targeting investors

Message them with hyper-personalised content that we generate within 1 minute. Typically, for one person, that takes 30 minutes of research. Use this to increase your conversion on hyper-targeted investor outreach.

Interactive demo

Try it yourself

A hands-on walkthrough of personalization. Click through it at your own pace, no sign-up required.

Real personalization, not '{firstName}' mail merge

Investors can smell a template in the first line. Real personalization means the message could only have been written to this partner, because it references their thesis, their portfolio, their recent posts, and it frames your company through the lens of what they invest in. That's what Astel writes.

A rich profile behind every message

For every investor on your list, Astel compiles a living dossier that goes far beyond a LinkedIn scrape:

  • Investment thesis in the partner's own words, pulled from their writing
  • Every portfolio company, tagged by stage, sector, and business model
  • Recent public activity: posts, podcasts, panels, conferences
  • Check-size and ownership patterns from public deal data
  • Red flags: portfolio conflicts, funds they've left, deals they've passed on publicly
  • Warmth signals: mutual connections and prior interactions

Ready to raise smarter?