Tax Reasoning (UAE)
IRAC scenarios with explicit correct/incorrect variants reduced hallucinations on tricky VAT timing prompts.
We create high fidelity legal datasets that reduce hallucinations and improve LegalBench style performance. Start with UAE Tax and Jordanian Tax Law, or request a custom dataset for any country. Each example follows a scenario Q&A format with embedded IRAC.
Heads up: PDF translation is coming soon.
Purpose-built datasets for real practice. Available now: UAE Tax and Jordanian Tax Law. Additional countries on request.
Lawyer-authored hypotheticals and prompts with Issue, Rule, Application, Conclusion annotations—designed for reasoning-heavy fine-tuning.
We tailor questions to patterns that help models score higher on LegalBench tasks (rankings), with explicit correct/incorrect variants.
We collaborate with seasoned attorneys to aupwd thor, refine, and annotate authentic scenarios. Each pack includes grounded citations and structured labels so your model learns the why, not just the what.
“Their IRAC scenarios cut down hallucinations and made our tax model far more grounded on jurisdiction-specific prompts.”
“The held-out test set with lawyer review gave us trustworthy evals out of the box.”
Rows per Minimum Dataset
Jurisdictions Available Now
Structured Reasoning Labels
Imaginary Parties, Real Law
Available now: Tax Law (UAE, Jordan).
On request: Any country / additional areas (Contracts, Litigation, Regulatory, Compliance, Privacy, IP, Employment, M&A).
Minimum dataset: 5,000 rows.
Pricing: ranges from 5.98–100+ depending on jurisdiction, exclusivity, scope, and reviewer seniority.
(Exclusive categories & complex jurisdictions priced higher.)
Terms: milestone-based with an upfront deposit. Non-exclusive and exclusive licenses available (with terms that protect our IP and business).
Scenarios use imaginary parties; real law application is drafted and double-checked by lawyers.
Derived from our legal research and public information with citations and provenance.
Every order includes a held-out test set with variations per law/case check, reviewed by a lawyer.
Non-exclusive and exclusive packages with protective terms.
{"id":"uae-tax-000123",
"jurisdiction":"UAE",
"practice_area":"Tax",
"question":"A VAT-registered company receives an advance payment for a future supply. When is the output VAT due?",
"answer":"Under UAE VAT law, tax becomes due at the earlier of invoice issuance, receipt of payment, or supply date. Here, VAT is due upon receipt of the advance.",
"irac":{"issue":"VAT timing on advance","rule":"Tax due at earlier of invoice/payment/supply","application":"Payment received before invoice/supply -> VAT due now","conclusion":"Output VAT due upon advance"},
"citations":["UAE VAT Decree-Law No. 8 of 2017, Art. X"],
"labels":{"correct":true,"difficulty":"medium"},
"metadata":{"variant":"base","dataset_split":"train"}}
See how curated, IRAC-structured data reduces hallucinations and strengthens jurisdiction-specific reasoning.
IRAC scenarios with explicit correct/incorrect variants reduced hallucinations on tricky VAT timing prompts.
Adversarial variants improved robustness on LegalBench-style tasks across similar fact patterns.
Held-out test sets include at least one variation per law/case check, with lawyer verification.
| Feature | Ours | Generic Web Crawl |
|---|---|---|
| IRAC-Structured Q&A | Yes | No |
| Jurisdiction Tagging | Fine-grained | Sparse |
| Lawyer QA | Yes | No |
| Benchmark-Aware Design | Yes (LegalBench) | No |
Train and test splits in JSONL or CSV. Scenario Q&A with IRAC fields (Issue, Rule, Application, Conclusion), citations, and negotiable metadata add-ons.
Pricing ranges from 5.98–100+ based on jurisdiction, exclusivity, scope, and reviewer seniority. Minimum dataset is 5,000 rows. Payments are milestone-based with a deposit.
UAE Tax and Jordanian Tax Law. We can produce custom datasets for any country on request.
We design examples to reflect patterns found in LegalBench-style tasks. See the paper and rankings.
No. Our datasets are for machine learning training and research. Scenarios use imaginary parties; the law application is drafted and reviewed by lawyers.
Reduce hallucinations and boost LegalBench-style performance with jurisdiction-specific, IRAC-structured data.
PDF translation is coming soon.