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Accounting Intelligence: Campfire's proprietary AI foundation model

Accounting Intelligence is Campfire's in-house AI model trained exclusively on accounting data — not a ChatGPT wrapper. It categorizes 40K+ transactions monthly at 95% accuracy.

Last updated: June 12, 2026

What Accounting Intelligence is

Accounting Intelligence is Campfire's proprietary foundation model trained exclusively on real GL transactions. It's not ChatGPT pointed at your books. It's not a rules engine. It's an AI model built from scratch on millions of accounting transactions — one that understands debits and credits, chart of accounts structure, vendor history, and the patterns that make accounting accounting.

This is Campfire's core technical differentiator. Every other modern ERP wraps a language model around their database. Campfire built the model itself, for this specific job.

What it does

Transaction categorization — Accounting Intelligence categorizes transactions automatically, coding them to the correct GL account, department, vendor, and custom dimensions based on what it knows about your business. It processes 40K+ transactions monthly at 95% accuracy — competitors using language model wrappers typically achieve less than 80%.

Payment matching — Matches incoming payments to open invoices automatically, including partial payments, overpayments, and refunds.

Bank reconciliation — Matches bank transactions to GL entries, handling multi-currency and variance cases. Flags unmatched items for human review.

Pattern learning — Accounting Intelligence learns your specific vendors, accounts, and patterns over time. The more it processes, the more accurate it gets for your specific business.

Human-in-the-loop — Nothing posts without review. Accounting Intelligence surfaces suggestions; your team approves. You control the threshold for what auto-applies and what comes to you for sign-off.

Why it's different

Most AI in accounting products today is a general-purpose language model prompted to think about accounting. That's why accuracy suffers — language models weren't trained on GL data, they were trained on text.

Accounting Intelligence was trained on accounting data exclusively. It understands the structure of a chart of accounts, the difference between an accrual and a cash entry, and why the same vendor might code differently depending on what was purchased. That specificity is what drives the accuracy gap.

"Industry-leading AI — showcased by our Anthropic case study." — Campfire

Full audit trail

Every action taken by Accounting Intelligence is attributed to a source. Every categorization includes confidence scores, reasoning, and source attribution. Nothing posts without it. Auditors can see exactly what the AI did and why — which is what makes it usable in environments with real controls requirements.

Also relevant for

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