Use case
Use case3 min readBy The Data Workers Team

LP and investor reporting data, run by agents

Quarterly LP reports pull from fund accounting, portfolio and CRM data assembled in spreadsheets under deadline. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. Quarterly LP reports pull from fund accounting, portfolio and CRM data assembled in spreadsheets under deadline.
  • •What changes. Agents keep reporting inputs reconciled through the quarter and assemble the data pack with lineage.
  • •What stays with your people. Published investor figures: LPs rely on them.
  • •The result. Quarter-end reporting is a review, not a rebuild.

The problem today

Quarterly LP reports pull from fund accounting, portfolio and CRM data assembled in spreadsheets under deadline.

What changes with Data Workers

Agents keep reporting inputs reconciled through the quarter and assemble the data pack with lineage.

The workflow: Connectors agent (get_connector_status) → Quality Monitoring agent (run_quality_check) → Pipeline Building agent (generate_pipeline) → Data Context & Catalog agent (trace_cross_platform_lineage).
Fig. 1:The workflow: Connectors agent (get_connector_status) → Quality Monitoring agent (run_quality_check) → Pipeline Building agent (generate_pipeline) → Data Context & Catalog agent (trace_cross_platform_lineage).

The workflow, step by step

  1. 1.The Connectors agent calls get_connector_status and lands fund accounting and CRM data.
  2. 2.The Quality Monitoring agent calls run_quality_check and ties performance to the books.
  3. 3.The Pipeline Building agent calls generate_pipeline and assembles the data pack.
  4. 4.The Data Context & Catalog agent calls trace_cross_platform_lineage and documents every figure.

The impact metrics we move

  • •Data pack assembled: from about 2 weeks to 8 h
  • •Performance tie-out: from about a week to under 1 h
  • •Figure traced: from about a day to seconds
Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.
Fig. 2:Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.

What goes on autopilot

  • •Reporting inputs reconcile through the quarter, so no quarter-end scramble.
  • •Every figure has lineage, so investor questions are answered fast.

Where your people stay in charge

Published investor figures always go to a named approver, because LPs rely on them. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. One fund's quarterly pack.
  • •First week. Agents run at L1, observing only, and show the fixes they would have made, with receipts.
  • •By week two. The routine work above runs on its own; anything sensitive stays with a named approver.
  • •At day 30. We review the impact metrics against your baseline:
  • •Data pack assembled: from about 2 weeks to 8 h
  • •Performance tie-out: from about a week to under 1 h
  • •Figure traced: from about a day to seconds
  • •Cost. Start with a pilot ($7,500 one-time, credited in full against the first year). Scale is from $1,000 a month and Enterprise from $3,000 a month, billed annually, with unlimited seats, no usage meter and no markup on model spend. See pricing.

Related: The financial services hub · The full team playbook

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