Introduction

If you run an accounting or tax practice, you already have the systems — the ledgers, the tax software, the document drives, the practice tools. What you don’t have is a way to put agents to work across all of them without ripping anything out. That’s what this platform does. Adopt AI turns the manual, repetitive parts of accounting and tax work — reconciliations, the month-end close, variance commentary, document intake, workpaper prep — into agent-run workflows that a professional reviews and approves before anything reaches a client. The agent prepares; you sign off.

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What Adopt AI Does for Accounting & Tax

Adopt AI is an orchestration layer that sits on top of the tools your firm already uses. It reads data from those systems, runs agents over it, and writes results back — without replacing your ledger, your tax engine, or your document store. Every workflow ends with a human. An agent might reconcile fifty accounts, draft the journal entries, and flag three exceptions — but it pauses and hands those exceptions to a controller before the books are touched. This is the core idea: agents do the work, professionals keep control.

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The Two Views: Builder and App

The same platform is surfaced through two lenses, and it helps to hold both in mind from the start. The Builder is where the platform is assembled — where you register systems, compose skills, wire up agents, and set up the data infrastructure behind them. It’s the workshop. The End-User App is where people run the agents day to day. A team member opens an agent, scopes it to a client, has a conversation, and steps in whenever the agent asks for a decision. It’s the storefront. Neither view re-implements the other. Builders assemble; end-users run and review. Both work over the same underlying objects.

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The Building Blocks

The platform is made of six core concepts. Three of them are the capability track — what an agent can do. The other four are the primitives — the data and infrastructure agents draw on. Each layer adds exactly one thing the layer below it lacks: Connectors add access, Skills add intent, Agents add behaviour. The primitives keep the data clean, organized, and separated by client so agents never have to hit raw systems mid-conversation.

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Who This Is For

This documentation is written for the people setting up and running Adopt AI inside an accounting or tax firm — the practitioners building agents in the Builder, and the team members running them in the App. You don’t need to be an engineer. If you understand how your firm’s close, tax, or advisory work actually happens, you have what you need to follow along.

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Next Steps

1. Understand the platform architecture
2. Start with Connectors — the foundation everything else is built on
3. See how everything connects