Investor solicitation with organization targeting

type.inbound
and (
  // subject contains recipient's org name
  any(recipients.to,
      strings.icontains(subject.subject, .email.domain.sld)
      and regex.imatch(.email.domain.sld, '.{2,}')
  )
  or
  // body extracts org name matching recipient domain
  any(regex.extract(body.current_thread.text,
                    '(?P<org>[a-zA-Z]{2,20})\s(?:recently\s)?came to our attention'
      ),
      any(recipients.to,
          strings.icontains(.email.domain.domain, ..named_groups["org"])
      )
  )
)
and any(headers.reply_to,
        .email.domain.root_domain != sender.email.domain.root_domain
)
// greeting uses recipient's email local_part
and any(recipients.to,
        (
          strings.icontains(body.current_thread.text,
                            strings.concat("Dear ", .email.local_part)
          )
          or any(regex.extract(.email.local_part, '^(?P<first>[^._]+)'),
                 strings.icontains(body.current_thread.text,
                                   strings.concat("Dear ",
                                                  .named_groups["first"]
                                   )
                 )
          )
        )
)
// financial/investment cold outreach language
and (
  2 of (
    strings.icontains(body.current_thread.text, "alternative investments"),
    strings.icontains(body.current_thread.text, "raising capital"),
    strings.icontains(body.current_thread.text, "came to our attention"),
    strings.icontains(body.current_thread.text, "private markets"),
    strings.icontains(body.current_thread.text, "fundraising"),
    strings.icontains(body.current_thread.text, "investment opportunities"),
    strings.icontains(body.current_thread.text, "introductory"),
    strings.icontains(body.current_thread.text, "commitment size"),
    strings.icontains(body.current_thread.text, "ultra-high-net-worth"),
    strings.icontains(body.current_thread.text, "deployed capital"),
    strings.icontains(body.current_thread.text, "value creation"),
    strings.icontains(body.current_thread.text, "capital planning")
  )
  or (
    any(ml.nlu_classifier(body.current_thread.text).topics,
        .name == "Financial Communications"
    )
    and any(ml.nlu_classifier(body.current_thread.text).topics,
            .name == "Out of Band Pivot"
    )
    and any(ml.nlu_classifier(body.current_thread.text).topics,
            .name == "B2B Cold Outreach"
    )
  )
)