Turn data into pipeline, automatically
Clay-powered enrichment, AI agents & GTM automation
We combine Clay's data enrichment with AI agents and proven GTM strategy to help B2B SaaS teams build smarter, faster outbound motions — at scale. Unlike standalone agent tools, every workflow is built inside the revenue infrastructure that governs your GTM motion.
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Data providers layered
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Leads/week generated
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SDR time saved per prospect
Sound familiar?
Why standalone tools aren't enough
Manual prospecting eating up hours of your team's week
Generic outreach getting ignored by target accounts
Data sitting in silos across tools that never gets activated
Not enough headcount to personalize at scale
AI agents running autonomously with no connection to your CRM or lifecycle
No attribution on outbound enrichment spend — can't prove ROI
The difference
AI agents built inside revenue infrastructure
Most agentic GTM tools run as a standalone automation layer — disconnected from your CRM, lifecycle stages, and attribution. We build AI agents inside the revenue system that governs your GTM motion. Every autonomous action is tracked, attributed, and measured against pipeline.
Architecture
How the Clay GTM engine works
Data flows in from multiple providers, gets enriched and scored by Clay, then triggers actions across your GTM stack.
Data Sources
Clay GTM Engine
Enrichment & Automation
Actions
In action
Real-time enrichment at scale
Every record gets enriched with firmographic, technographic, and intent data — then routed to the right sequence automatically.
| Company | Contact | Tech Stack | Intent | Score | |
|---|---|---|---|---|---|
| Vertex Systems | S. Chen, VP Mktg | s.chen@vertex.io | HubSpot, Gong | High | 92 |
| Meridian Cloud | M. Webb, RevOps | m.webb@meridian.co | Salesforce, Outreach | Warm | 78 |
| Axiom Revenue | J. Park, CMO | j.park@axiom.io | HubSpot, Clay | Warm | 71 |
| Prism Analytics | R. Diaz, VP Sales | r.diaz@prism.dev | Salesforce, Gong | High | 88 |
| Nova GTM | K. Liu, Head DG | k.liu@novagtm.com | HubSpot, 6sense | Surging | 96 |
Signal to action
From buying signal to pipeline in minutes
Clay captures intent signals, enriches the data, and triggers personalized sequences — automatically.
Signals
Clay Processing
Actions
Signals
Clay Processing
Actions
Capabilities
What we build with Clay
Waterfall Enrichment
Layer multiple data providers to maximize coverage — verified emails, direct dials, tech stack, funding, hiring signals, and more.
AI-Personalized Outreach
Generate personalized messaging at scale using enriched data points — no more generic templates.
TAM Enrichment
Enrich your total addressable market with firmographic, technographic, and intent data to find the highest-value prospects.
Automated Pipeline Generation
Connect Clay to your CRM and sequencing tools to automatically create contacts, trigger sequences, and route leads.
AI Agents for GTM
Deploy task-specific AI agents that autonomously research accounts, qualify prospects, and trigger personalized outreach — governed by your lifecycle model and CRM architecture.
FAQ
Frequently asked questions
Agentic GTM refers to the use of AI agents — autonomous software programs that can research, reason, and take action — within go-to-market workflows. Instead of manually researching prospects, writing outreach, and routing leads, AI agents handle these tasks autonomously based on defined rules and signals. Effective agentic GTM connects these agents to CRM architecture, lifecycle stages, and attribution — so autonomous actions are governed by your revenue infrastructure, not running in isolation.
AI agents for outbound prospecting autonomously research target accounts using tools like Clay and Claygent, enrich contact data from multiple providers, score and qualify prospects against your ICP criteria, and trigger personalized multi-channel sequences. The best implementations connect agent outputs directly to CRM lifecycle stages and attribution models — ensuring every autonomous action is tracked and measured against pipeline.
Traditional workflow automation follows pre-defined if-then rules — if a form is submitted, then send an email. AI agents can reason, research, and make decisions autonomously within defined guardrails. For example, an AI agent can research a target account, determine the best messaging angle based on recent news and tech stack, draft personalized outreach, and route the contact to the right sequence — tasks that would take a human SDR 15–30 minutes per prospect.
Most agentic GTM platforms deploy AI agents as a standalone automation layer disconnected from your CRM and revenue infrastructure. Formulytic builds AI agents inside the revenue system — connected to your lifecycle model, attribution framework, and CRM architecture from day one. This means autonomous prospecting, enrichment, and outreach are governed by the same system that measures your pipeline, ensuring data quality, attribution accuracy, and lifecycle integrity.
We typically build agentic GTM workflows using Clay (including Claygent for autonomous research), n8n for workflow orchestration, and your existing CRM (HubSpot, Salesforce, or Marketo) as the system of record. The specific tooling depends on your stack, but the principle is consistent: agents are platform-agnostic and governed by your revenue infrastructure.
Automate your pipeline generation
Book a strategy call to see how Clay-powered enrichment and AI agents can transform your outbound motion.