Hot Leads Agent

  • Published on Aug 24, 2026
  • 3 minute(s) read
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RevSure Hot Lead Agent is a configurable GTM agent built in RevSure’s no-code Agent Builder. It continuously identifies leads that match your ICP and flags the ones that are “heating up” based on full-funnel engagement and intent signals—then pushes actionable alerts to the right owners so teams can reduce speed-to-lead and respond while intent is highest.

What you get

  • A daily (or real-time) stream of hot leads that match your ICP

  • A structured lead packet for each lead:

    • key identity fields (name, company, title, email when available)

    • engagement/journey summary

    • inferred pain points and signals (via enrichment)

    • recommended next-best actions

  • Notifications delivered to Slack channels and/or owners as alerts

  • A final output list (for review, reporting, routing, or downstream activation)

How it works (node-by-node)

RevSure Hot Lead Agent follows a structured workflow in the Agent Builder: define inputs → choose triggers → stitch context → enrich → analyze → notify → output. RevSure’s Agent Builder is designed for multi-step enrichment, flexible triggers (manual/scheduled/real-time), and delivering outputs to the systems where teams work.

1) User Input Node: Define your ICP lead set

Start by defining the leads you want the agent to monitor. This can include:

  • Title / seniority

  • Region / geo

  • Propensity or lead score

  • Segment / industry

  • Any custom attributes you maintain in RevSure or upstream systems

Goal: establish a precise target pool so alerts are high-signal, not noisy.

2) Trigger Node: Decide when it runs

Choose how the agent should activate:

  • Manual: run on-demand for testing or one-off pushes

  • Scheduled cadence: daily/weekly at a set time

  • Real-time events: trigger on signals like web visitors or key engagement events (where enabled)

RevSure Agent Builder supports manual, scheduled, and webhook/event-driven triggers to control when agents take action.

3) RevSure Context Node: Identify leads + stitch full-funnel context

This node is where the agent “understands” what’s happening.

  • It identifies the leads from your input criteria

  • It stitches full-funnel context across your connected data sources to reconstruct the lead’s journey (touches, engagement, progression, and relevant intent/activity signals)

Outcome: each lead is enriched with internal journey context, not just static fields.

4) Enrichment Node: Add external signals (e.g., LinkedIn)

Next, the agent enriches those leads with external intelligence such as:

  • likely pain points

  • company/role signals

  • hot topics and contextual cues

  • recent changes (where available)

This layer complements internal context so your team gets “why now” plus “why them,” not just “who.” RevSure describes multi-step enrichment and connecting third-party sources as a core Agent Builder capability.

5) AI Node: Summarize + generate actionable analysis

The AI node takes the internal context + external enrichment and produces a structured output using a prompt you control. Common outputs include:

  • engagement summary (what happened, when, and what changed)

  • inferred pain points and buying signals

  • next-best actions (email/call/sequence guidance)

  • key basics (name, company, email, title) plus any custom fields you need

Tip: keep the AI output structured (bullets or JSON-like sections) so it’s easy to scan in Slack and easy to export downstream.

6) Notifications Node: Deliver alerts to owners (Slack + routing)

The notifications node sends alerts:

  • to relevant Slack channels (e.g., SDR team, region channels)

  • to account owners / lead owners (where mapped)

  • on a daily cadence (or real-time when enabled)

Goal: reduce speed-to-first-touch by notifying teams at the moment leads show meaningful activity/intent.

7) Output Node: Final list for reporting or activation

Finally, the output node produces:

  • a list of leads processed in that run

  • the analyzed data points for each lead (summaries, signals, next actions)

This output can be used for:

  • daily review dashboards

  • routing logic

  • exporting into outreach tools

  • tracking lift (response time, meeting rate, pipeline influence)

Flowchart illustrating the process of lead prioritization and contact enrichment using AI.

Agent Builder Flow

Configuration guide

Step 1: Choose the ICP filter

Start narrow. Examples:

  • “Director+ in North America at companies 200–2,000 employees”

  • “Security leaders in EMEA with high propensity”

  • “Product marketing titles in SaaS, Tier 1 target accounts”

Step 2: Pick the trigger mode

  • If you’re rolling out: start with daily scheduled

  • If you’re mature on signals + routing: enable real-time events

Step 3: Define what “hot” means for your team

Even if your model computes hotness automatically, you should align internally on:

  • what signals count (web activity, content engagement, intent surge, etc.)

  • what threshold triggers an alert

  • what you want in the alert (context vs instruction)

Step 4: Write your AI prompt

A strong default structure:

Required sections

  1. Lead basics (name, company, title, email)

  2. “Why this lead is hot now” (top 3 reasons)

  3. Journey summary (last X days + key spikes)

  4. Pain points / themes (from enrichment)

  5. Next best actions (2–3 steps, specific)

Step 5: Configure Slack delivery

  • Channel(s) by region/segment

  • Mention/DM to owner (optional)

  • Daily digest vs per-lead alerts

Example outputs

Example Slack alert (digest style)

Hot Leads — Today

  1. Jane Doe — VP Security, Acme

    • Why now: pricing page visits + webinar attendance + high intent surge

    • Journey: 3 touchpoints in 7 days; spike yesterday

    • Next actions: send 3-line email about X, route to SDR Y