Outreach Intelligence – white-labelled sales intelligence

Category: Client SaaS (white-labelled) Status: Live, active Time window: April 2026 → ongoing (last major push August 2026) Live URL: private (client-facing dashboard)

Purpose

Scrape → enrich → score → render → persist pipeline that surfaces sales-actionable leads to the client CEO on a schedule she controls.

Who it is for

The client's sales lead (CEO / targeter) – one operator, one dashboard, one weekly reading rhythm.

Stack

• Frontend: Next.js dashboard (App Router)
• Backend: Trigger.dev v4 orchestration
• LLM / AI: Claude for enrichment analysis (never in scoring); Langfuse cost tags per pipeline run
• Data: Supabase (per-client schema)
• Delivery: in-dashboard views + rendered HTML briefs

My contribution

Shaped the intelligence workflow, designed the content architecture, implemented the data collection and integration and the APIs behind the client dashboard, and carried the product through deployment and iteration.

Notable capabilities

• Weekly signal review dashboard with tier chips and priority ordering
• HTML brief rendering (per-lead one-pagers) for client CEO to skim before her outreach block
• Cost-tagged Trigger.dev runs so per-week spend is attributable to the client's product tag in the fleet dashboard
• White-labelled UX – client's brand, not Stratas'

Outcome

Live and used by the client CEO on a weekly cadence. The pipeline pattern (scrape → enrich → score → render → persist) became the template applied to preservation, market-intel-industrial, market-intel-precursor, and relocation-market-intel.

Evidence

• Repo: private
• Pattern: same as Preservation but Next.js/TS instead of Python; different sector; different cadence

Skills demonstrated

nextjs, trigger-dev-v4, supabase, langfuse-per-run-tagging, client-white-labeling, pipeline-orchestration, weekly-signal-delivery