ModelRefs / Expense Categorization — Canonical Workflow
Expense Categorization — Canonical Workflow
Expense Categorization: provisional AI workflow implementation reference with candidate models, providers, tools, and architecture.
Overview
Draft policy- and ledger-category suggestions from authorized expense records, preserving source evidence and routing uncertain or exceptional cases to finance review. Finance deployment requires organization- and jurisdiction-specific access, retention, segregation-of-duties, approval, reconciliation, and audit controls. Candidate outputs should preserve source-data traceability and route missing, conflicting, or policy-sensitive cases to qualified finance reviewers. These pages describe provisional decision support; accountable people retain accounting, payment, audit, financial-reporting, and compliance authority.
Implementation profile
| Category | llms |
|---|---|
| Implementation maturity | enterprise |
| Primary use cases | extraction, reasoning |
| Deployment options | managed-api, hybrid |
| Architectures | serverless-api, managed-container, hybrid-private-cloud |
What this evidence does not establish
- No target receipt distribution, category taxonomy, policy corpus, currency rules, duplicate definition, or posting authority is registered.
- No measured field accuracy, category accuracy, policy recall, duplicate miss rate, reviewer burden, or posting outcome is attached.
Candidate models with published references
- BGE-M3
- GPT-5
- GPT-5 Mini
- Claude Sonnet 4.5
- Claude Opus 4
- Gemini 3 Pro
- Llama 4 Scout
- DeepSeek R1
- Mistral Large 2
- Command R+
- o3
- o4 Mini
Coverage means the model is a candidate worth evaluating for this workflow, not a ranking or a recommendation. Models whose reference pages are still in review are omitted.
Benchmarks relevant to this workflow
- GPQA Diamond — Graduate-level Google-Proof Q&A in physics, chemistry, and biology.
- MMLU-Pro — Harder MMLU successor with 10-option questions and reduced contamination.
- MMLU — Massive Multitask Language Understanding — 57 academic and professional subjects.
These are the benchmarks whose task shape bears on this workflow. Each one only describes its own protocol and date, so confirm the harness matches your workload before treating a score as evidence.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Expense Categorization — Canonical Workflow.