Data Store

Once a Pipeline has pulled and cleaned your data, it has to go somewhere agents can actually use it. That somewhere is the Data Store — the platform’s structured, queryable storage. It’s a set of tables with schemas, rows, and SQL access that pipelines write to and agents read from and write back to.

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What Is the Data Store?

The Data Store is the shared data substrate for the whole platform. Where File Explorer holds raw documents, the Data Store holds structured rows — general ledger entries, reconciliations, client records, tax returns. It’s stateful: the data persists between runs, so an agent can pick up exactly where the last one left off.

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How to Access the Data Store

Click Data Store in the left navigation, under the Adopt Primitives group. This opens the tables view. Three tabs sit at the top: All Tables (the list), Relationships (how tables link to each other), and Overview.

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Inside the Tables List

Each table appears as a card showing its name, status, a plain-language description, and its size. The tables are the working data of an accounting practice — for example: Notice that some descriptions note the table is “read by the Close Tasks UI” or “read by the Reconciliations UI” — that’s a Data Store table feeding a Dashboard agent’s surface directly.

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Exploring a Table

Click any table to open its detail view. A row of tabs gives you everything about that table. The Schema tab is where you see a table’s structure — every column with its type and whether it’s nullable, a primary key, or unique.

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What the Data Store Is For

The Data Store does four distinct jobs, and it helps to keep them straight:

• Landing pipeline output — the structured result of every pipeline run.
• Capturing agent output — results an agent produces, persisted for later steps or reporting.
• Agent-to-agent handoff — an intermediate store where one agent parks data for another to pick up and continue.
• Feeding UIs — tables can be read directly by an agent’s end-user surface, like the Close Tasks or Reconciliations dashboards.

Everything in the Data Store is scoped by the Workstream it belongs to — the schema is shared across clients, but the rows are isolated.

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Why the Data Store Matters

The Data Store is what lets a multi-step workflow actually work. A close involves several agents — intake, reconcile, adjust, review, publish — and each one needs to hand structured results to the next. Rather than passing data through brittle exports or messages, each agent writes clean rows to a shared table the next agent reads. It’s also inspectable end to end, so you can always see exactly what data a run was working from.

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Next Steps

1. See how File Explorer handles raw documents
2. Understand how Workstreams isolate table data
3. Trace the runtime data flow