Signal-Stack.
AI-powered pre-call sales intelligence — and a LinkedIn network analyzer — both running on Cloudflare's edge.
- Status Production · live
- Stage Founder · Operator
- Product 1 Pre-call Intelligence
- Product 2 LinkedIn Network Analyzer
- Runtime Cloudflare edge — Workers · Pages · D1
- AI Claude API · org-customizable prompts
The brief should reflect
the relationship.
Signal-Stack is a B2B sales-intelligence platform built around a single proposition: the rep should walk into every meeting with a brief that actually reflects the relationship — not a CRM summary, not a LinkedIn scrape, an honest synthesis of what's been said and signaled across every channel.
It does this by reading the last 90 days of calls, the last 60 days of email, and any signals available in Salesforce, HubSpot, LinkedIn, and Clay. The synthesis runs through Claude using an org-customizable prompt template, and the resulting brief lands as email or in Slack the morning of every meeting on the calendar.
A brief that reflects the relationship.
Not a CRM summary.
Product thesis
Pre-call intelligence.
And a network analyzer.
Pre-call Intelligence — the flagship product. Cron-driven morning briefs for every meeting on your calendar. Pulls Gong call history, Gmail threads, LinkedIn profile signals, and CRM context. Outputs a structured pre-call brief with meeting-type classification (full / cold / personal / gmail), deal health, stakeholder map, competitive context, and predicted next steps.
LinkedIn Network Analyzer (Prospect) — collaborative workspaces for sales teams. Each team member uploads their LinkedIn connection export; the platform computes mutual-connection overlaps, maps ICP-matching contacts, and finds shortest-path warm intros to target prospects through shared connections. Includes account coverage analysis and an outreach console with auto-fill templates.
Edge-native.
End to end.
Five decisions
worth flagging.
- Edge-first. The entire stack runs on Cloudflare — Workers, Pages, D1, KV. No origin servers, no Docker, no Kubernetes. Cold start measured in single-digit ms.
- Encryption at rest. Every connector credential (Gong API key, Salesforce OAuth token, etc.) is AES-GCM encrypted before storing in D1. Decryption is fail-closed.
- CASA Tier 2 readiness. Independent peer review by OpenAI, all P0/P1 findings closed, security headers + CSRF + rate limiting throughout.
- Brief synthesis pipeline. Six-stage flow — contact classification → Gong hydration → Gmail analysis → parallel enrichment → signal computation → Claude synthesis. Each stage independently testable.
- Privacy-by-design. Gmail scope minimized to brief generation only. Restricted-contact list. Erasure log. CCPA + GDPR data-subject request flow.
The operator side
of the advisory.
Signal-Stack is the operator counterpart to the advisory work — the place where the theses on agentic measurement, vector-based audience matching, and edge-native B2B software get tested against paying customers and real data.
It's also the home of the adcp.signal-stack.io subdomain — the production demo of the AdCP Signals Adaptor, a separate open-source reference implementation contributed back to the working group.