AI Agent Stack
Custom AI Agents Deployed Inside Your Existing Workflows
We build and deploy AI agents that handle prospect research, lead scoring, copy generation, competitive intelligence, and pipeline analysis — all running inside your CRM, sequencer, and communication tools.
AI is the most powerful multiplier of revenue team productivity available today. But most teams are only scratching the surface — using ChatGPT as a generic writing tool instead of deploying AI agents that integrate directly into their workflows, access their actual data, and run continuously without human intervention. When AI is properly deployed into your GTM stack, a single rep can accomplish what previously took three, compounding your team's output exponentially.
The Problem
Every revenue team knows AI can help them. But most teams are stuck at the copy-paste stage — reps manually pasting prospect names into ChatGPT, getting generic output, and spending more time prompting than they save. There's no systematic AI integration, no connection to their actual data, and no way to scale it.
Meanwhile, the tasks that consume the most time are exactly the ones AI excels at: researching prospects, analyzing deal data, writing personalized outreach, monitoring competitors, and scoring leads. These are pattern-recognition and data-synthesis problems that AI handles in seconds — if it's properly deployed and connected to your systems.
- —Reps manually copy-pasting into ChatGPT with no structured workflow
- —AI outputs disconnected from CRM data, sequences, and deal records
- —Hours spent on prospect research that AI could do in seconds
- —No competitive intelligence system — teams learn about competitor moves from prospects
- —Lead scoring based on gut feel instead of data-driven AI analysis
- —Generic outreach because personalization at scale seems impossible
What We Build
Prospect Research Agents (Claude AI)
We deploy Claude AI agents that automatically research every prospect before outreach. The agent pulls company news, recent funding rounds, tech stack data, hiring patterns, leadership changes, and published content — then synthesizes it into a structured research brief with recommended talking points. This runs automatically in your enrichment pipeline: when a new lead enters Clay or your CRM, the research agent fires, and the results populate directly into CRM fields and sequence personalization tokens. Your reps get a full prospect dossier without lifting a finger.
AI Lead Scoring (OpenAI)
We build custom lead scoring models using OpenAI that evaluate every lead against your ideal customer profile. The model analyzes firmographic fit (company size, industry, tech stack), behavioral signals (website engagement, email interaction, content consumption), and contextual data (funding stage, hiring velocity, market signals). Unlike static point-based scoring, the AI model learns from your closed-won and closed-lost data to continuously improve prediction accuracy. Scores update in real-time inside HubSpot or Salesforce, so your team always knows which leads deserve attention first.
Competitive Intelligence Agents (Perplexity)
We deploy Perplexity-powered research agents that continuously monitor your competitive landscape. These agents track competitor product launches, pricing changes, leadership hires, funding announcements, and customer reviews — then surface relevant alerts to your team via Slack and CRM notifications. When a competitor raises a Series B, your team knows before the next sales call. When a competitor changes pricing, your reps have updated battlecards within hours. The intelligence feeds directly into your deal records so reps have context when competitors come up in conversations.
AI Copy Generation Agents (Claude AI)
We build Claude-powered agents that generate personalized outreach at scale — cold emails, LinkedIn connection requests, follow-up sequences, meeting prep summaries, and proposal drafts. Each piece of copy is generated using the prospect's actual data: their company context, role, recent activity, and engagement history. The agents operate inside your outbound pipeline: Clay enrichment data feeds into Claude, Claude generates personalized copy, and the copy flows directly into Salesloft or Outreach sequences. Your reps review and send rather than write from scratch.
Pipeline Intelligence Agents
We deploy AI agents that analyze your pipeline data and surface actionable insights. These agents flag at-risk deals based on engagement patterns (no activity in 14 days, stakeholder ghosting, competitor mentioned), identify stalled opportunities that need intervention, and predict close probability based on historical deal characteristics. The insights appear as Slack alerts, CRM dashboard widgets, and weekly pipeline intelligence reports — giving managers visibility they've never had before.
N8N Deployment Infrastructure
Every AI agent is deployed via N8N workflows that connect them to your production systems. This means agents aren't standalone experiments — they're production infrastructure that runs reliably, handles errors gracefully, logs every action, and integrates directly into your CRM, sequencer, and communication tools. We build monitoring, alerting, and fallback logic so you know when agents run, what they produce, and if anything needs attention.
How It Integrates With Your Stack
AI agents are only valuable if they connect to the tools your team uses every day. That's why every agent we build plugs directly into your existing infrastructure.
Research outputs populate custom fields in Salesforce or HubSpot. Lead scores update CRM properties in real-time. Competitive intelligence triggers Slack alerts in your sales channel. Generated copy flows into Salesloft or Outreach sequence steps. Pipeline insights surface in CRM dashboards and weekly Slack digests.
Your reps don't interact with AI directly. They interact with their CRM, their sequencer, and their Slack — and the AI makes those tools dramatically more useful. The intelligence is embedded into the workflow, not layered on as another tab to check.
Agents can also trigger actions: update deal stages, create follow-up tasks, send notifications to managers, enrich records with new data, and route leads based on scoring thresholds. The system is proactive, not passive.
What You Get
Typical Results
80%
Reduction in prospect research time
2x
Increase in personalized outreach volume
35%
Improvement in lead scoring accuracy
Related Services
Ready to Deploy AI Agents in Your Revenue Stack?
Book a 30-minute call. We'll identify the highest-impact AI agent opportunities in your current workflow and show you exactly how we'd deploy them.