Agents Overview
Overview
HockeyStack Agents are AI-powered automations that transform natural language instructions into reliable, repeatable workflows. Instead of manually analyzing data or building complex integrations, you describe what you want in plain English—and the system handles the rest.
Users write a "contract" (natural language instructions), and HockeyStack's AI translates it into a structured, enterprise-grade automation that runs on schedule, on-demand, or in response to events.
The Three Core Components
1. Agent Contract (What You Write)
The contract is your plain English description of what the agent should do. Think of it as giving instructions to a new team member.
Example Contract:
For each company in my target account list:
Fetch their recent website activity and engagement data
Analyze their behavior and assign a score from 1–100
Generate a one-paragraph summary explaining the score
Save the score and summary to the company record
No coding required. The system validates your instructions and highlights any ambiguities before execution.
2. AI Engine
Behind the scenes, HockeyStack converts your contract into a Domain-Specific Language (DSL) — a structured, machine-readable format designed specifically for go-to-market automation.
Why this matters:
Reliability — Workflows execute predictably
Transparency — Every step can be audited and debugged
Scalability — Process thousands of records without manual effort
The DSL supports four step types:
Step Type
Purpose
Example
inject
Add data or constants to the workflow
Load your target account list
for_each
Loop through records
Process each company in a segment
if/else
Make conditional decisions
If score > 80, mark as high priority
agent
Run AI with tools and structured output
Analyze engagement and generate insights
3. Nex-LM
Agents then turn user-generated, natural language Contracts into a multi-agent system to execute.
Nex-LM is an AI model purpose-built for GTM workflows, understanding buyer journeys, buying committees, attribution, scoring, deal stages, and more.
It turns Agent Contracts into multi-step agent outcomes.
Built-In Intelligence
AI-Powered Agent Steps
Each agent step can:
Receive data from previous workflow steps
Autonomously call tools to query HockeyStack data
Return structured output that fits a defined schema
Example:
An agent analyzing a company may fetch visits, evaluate trends, pull associated deals, and then return a scored recommendation.
Example Tools Agents Use
Each agent can use a variety of tools depending on the Agent Contract, including fetching record details, metadata, records, analyzing patterns and buyer journeys, sending data to destinations and more.
Enterprise-Grade Execution
Durable Workflows
HockeyStack ensures:
No lost work — workflows resume after failures
Long-running support — multi-hour jobs supported
Deduplication — prevents accidental double runs
Full audit trails — every execution logged
Flexible Triggers
Trigger Type
Use Case
Scheduled
Daily scoring, weekly digests
Manual
One-off analysis or action
Structured, Trustworthy Output
Chat AI output: "The score is probably around 75 or so…"
Agent output: { score: 75,
reasoning: "High engagement...",
nextSteps: ["Schedule demo"] }
This makes the output safe and compatible for CRMs, automation, and downstream tools.
Interfaces
Each agent can use chat, slack, and email as interfaces. Agents that are built for next best steps or tasks can use Rep Cockpit as their interface.
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