Activate company-level signal tracking. Runs signals via the Saber CLI if available; without it, outputs a research playbook and suggests alternative tracking methods.
Generate 12–15 structured, weighted research signals from a structured ICP, ready to activate in Saber. Each signal includes answer type, weight, and interpretation rules for automatic scoring.
Deep research on a single company — signals, hiring, news, tech stack, and LinkedIn presence. Uses the Saber CLI for signal data and any available MCP tools for broader research.
End-to-end guided workflow — take one prospect domain, run your saved research signals, find named contacts on the buying committee, and write a hyper-personalised cold email and LinkedIn DM grounded in the signal answers. First run defines the source-company ICP, contact-search targets, and ≤5 weighted signals (saved to disk); every subsequent run reuses them. Use when you want full SDR research-and-write for a single prospect, not write-outreach in isolation.
End-to-end guided workflow — build a Saber company list, run research signals across every company in parallel, find named contacts, and export a combined CSV to the desktop. Walks the user through each stage with confirmations and a credit-discipline guard. Use when you want one signed-off CSV instead of running build-account-list, create-company-signals, and build-contact-list separately.
Build a target account list and run company signals against it. Works with the Saber CLI, Apollo, HubSpot, or any available prospecting tool — with a manual fallback.
Set up native scoring — create a profile, translate signal templates into rules, and bulk-assign a list so fit and urgency scores compute automatically. Bridges the weighted model from generate-signals into the platform.
Cluster historical ad-hoc signal questions into reusable signal templates so they can be referenced by scoring rules. One-shot migration tool — most orgs run it once before configuring scoring on legacy data.