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Multi-step, configurable AI pipelines that run research, analysis, and content generation across accounts at scale. Build once, run across your portfolio. Workflows automate multi-step AI tasks. Instead of manually researching an account, then generating a competitive analysis, then drafting emails, then producing a meeting brief - a workflow runs the entire sequence as a single automated pipeline with consistent quality.

Key capabilities

  • Multi-step pipeline builder with LLM generation, tool calls, conditionals, and branching
  • Batch execution across accounts
  • Context recipes for reusable research configurations
  • Frameworks for reusable workflow templates
  • Workflow history and tracking
  • Model selection per step - choose the right LLM for each task

Who it’s for

RoleHow they use it
RevOps teams & sales operationsBuild workflows once and run them at scale across many accounts
Account executivesTrigger pre-built workflows for specific tasks (e.g., “generate a meeting brief”)
Sales leadersEnsure consistent output quality across the team

When to use workflows vs. the AI Assistant

TaskUse AssistantUse Workflow
One-off research questionYesNo
Meeting brief for one accountEither worksYes, for repeatable process
Research report for 50 accountsNoYes
Exploring an account interactivelyYesNo
Standardised competitive analysisNoYes
Territory-wide change summaryNoYes
Rule of thumb: If you’ll do the same task more than 3 times, build a workflow. If it’s a one-off exploration, use the assistant.

Effective workflow patterns

Meeting preparation pipeline

1

Pull account data

Pull strategic priorities and recent news (tool call)
2

Identify attendees

Identify meeting attendees from contacts (tool call)
3

Generate talking points

Generate talking points aligned to company goals (LLM generation)
4

Draft discovery questions

Draft discovery questions based on account context (LLM generation)
5

Produce meeting brief

Compile a one-page meeting brief (LLM generation)
Output: A meeting-ready document per account. Run in batch for a week’s worth of meetings.

Territory health review

1

Check for changes

For each account in segment: check for Intelligence changes since last review (tool call)
2

Flag accounts

Flag accounts with significant changes (conditional)
3

Generate summaries

Generate a change summary for flagged accounts (LLM generation)
4

Compile report

Compile a territory health report (LLM generation)
Output: A territory-level report highlighting which accounts need attention and why.

Account research and engagement plan

1

Run Intelligence review

Run comprehensive Intelligence review (tool call)
2

Identify competitive landscape

Identify competitive landscape (tool call + LLM generation)
3

Map stakeholders

Map stakeholders and recommend contacts (LLM generation)
4

Generate value alignment

Generate value alignment analysis (LLM generation)
5

Draft engagement plan

Draft engagement plan with recommended sequence (LLM generation)
6

Generate outreach emails

Generate 3 personalised outreach emails (LLM generation)
Output: A complete engagement package per account.

Tips for effective workflows

1

Start with pre-built workflows

Run them as-is to understand the pattern, then customise.
2

Use context recipes

Don’t reinvent how Intelligence data is gathered for each workflow. Recipes standardise this.
3

Test on a small sample first

Before running a workflow across 200 accounts, validate the output on 3–5 accounts.
4

Review output quality

Workflows produce consistent output, but consistency doesn’t guarantee quality. Review and iterate.
5

Chain workflows

A territory review workflow can identify accounts that need attention; an engagement plan workflow can generate plans for those accounts.

Monitoring and troubleshooting

  • Workflow history shows the status of every run: completed, failed, or in progress.
  • Step-level detail shows which step failed and why.
  • Retry is available for failed runs.
  • Output inspection shows the generated content at each step.