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Expert data, evaluations & task environments

Fluency is cheap. Judgment isn’t.

Alura turns the judgment of verified finance professionals into training data, evaluations, and task environments for AI that has to be right.

Work with us See an expert review

01Verified professionals

  • CPA

    Certified Public Accountant

    New York EN

  • ACCA

    Chartered Certified Accountant

    Dubai AREN

  • SMMM

    Certified Public Accountant

    Istanbul TR

  • CA

    Chartered Accountant, ICAI

    Mumbai HIEN

  • CA

    Chartered Accountant, ICAP

    Karachi UREN

02Alura quality control

AluraEvery item, every time

FIN-0417 · Lease accounting · UAE

Dubai company, five-year office lease. How should it be booked?

  1. Author

    Answer and rationale written

    ACCA ✓

  2. Independent review

    A second expert checks it

    CPA · reviewing

  3. Adjudication

    Disagreements resolved

    If needed

  4. Calibration

    Checked against gold items

    Queued

03Delivered to your models

  • Training data

    Reference answers, rationales, preference pairs

    SFTRLHF

  • Evaluations

    Benchmarks, rubrics, critical-failure analysis

    EvalsRed-team

  • Task environments

    Real finance workflows for agents, expert-graded

    AgentsGraded

01The problem

A model can draft a lease schedule, a credit memo, or a compliance summary in seconds. The prose is clean. The numbers look right. And in regulated work, looking right is exactly how mistakes get through.

Alura puts verified professionals between your model and the real world. Accountants, analysts, and risk and compliance specialists write the data, design the tests, and find the failures before your customers do.

02One review, up close

A confident answer, read by someone who does this for a living.

A chartered accountant reviews a model’s answer on lease accounting. Each mark becomes either a training example or a benchmark item.

Eval FIN-0417 Lease accounting Jurisdiction: UAE Reviewer: ACCA, verified

Prompt

We’re a company based in Dubai. We just signed a five-year office lease at AED 240,000 a year, paid at the end of each year. Our incremental borrowing rate is 6%. How should we account for it?

Model response confidence: high

Under ASC 842, this is an operating lease. You should recognize a straight-line rent expense of AED 240,000 per year over the lease term. Because it is classified as an operating lease, no liability is recorded on the balance sheet; the future payments are disclosed as commitments in the notes.

Rubric

  • Framework identifiedFail
  • Recognition modelFail
  • MeasurementMissing
  • Year-one expenseWrong
  • ClarityPass

Verdict

Fluency5/5
Correctness1/5

CriticalLeaves ≈ AED 1,010,967 of lease liability off the balance sheet.

  • Reference answer + rationale → training set
  • Failure pattern → benchmark
  1. 1

    Wrong framework. A UAE company reports under IFRS, so IFRS 16 applies. If a US parent consolidates it, ASC 842 matters at group level, and a good answer says so.

  2. 2

    No such classification. IFRS 16 has a single lessee model. There is no operating-versus-finance split on the lessee side.

  3. 3

    Wrong under both standards. Book a right-of-use asset and a lease liability of about AED 1,010,967: five payments of 240,000 discounted at 6%. Year-one expense is 262,851, not 240,000.

03What we build

Data, tests, and environments, built by people who do the work.

  1. 01

    Expert training data

    Worked solutions, reasoning traces, and preference judgments written by credentialed finance professionals. Every item carries its rationale, so your team can see why an answer is right.

    • Fine-tuning
    • Preference data
    • Rationales
  2. 02

    Evaluations & benchmarks

    Domain benchmarks and rubric-based evaluations built to find hallucinations, unsupported figures, and the critical failures that would never survive review on a real finance team.

    • Benchmarks
    • Rubrics
    • Red-teaming
  3. 03

    Task environments

    Realistic accounting, document-analysis, and risk and compliance workflows where an agent has to finish the job, not describe it. Outcomes are graded by experts.

    • Agent evals
    • Document analysis
    • Workflows
  4. 04

    Multilingual & regional

    Financial conversations in English, Arabic, Turkish, Hindi, Urdu, and more, reviewed by professionals who know the local rules and customs as well as the language.

    • 5+ languages
    • Regional regulation
    • Cultural review

04Language & jurisdiction

Translate every word correctly and you can still get the finance wrong.

Our reviewers know the language, the local regulation, and the customer. The initial bench covers English, Arabic, Turkish, Hindi, and Urdu, with more to come.

Customer asks

كم سعر الفائدة على تمويل السكن؟

“What’s the interest rate on my home financing?”

A literal model answer

The interest rate (سعر الفائدة) on your home loan is fixed at 4.2% for the first three years.

What the expert flags

This customer banks with an Islamic lender. Home finance there is usually an Ijarah or Murabaha contract priced with a profit rate (معدل الربح). Calling it interest is the wrong concept, not just the wrong word.

Four regions, one review bench.

Typical 09:00–18:00 working hours in each region, plotted on UTC.

United StatesNew York ·
--:--
Middle EastDubai ·
--:--
Central AsiaTashkent ·
--:--
South AsiaDelhi ·
--:--

05Quality control

How a single item earns its place in your dataset.

  1. 01

    Verify

    Credentials, licenses, and a domain test, before anyone touches a task.

  2. 02

    Author

    An expert writes the task, the reference answer, and the reasoning behind it.

  3. 03

    Review

    A second professional checks the work independently. Disagreements go to adjudication.

  4. 04

    Calibrate

    Gold-standard items and agreement tracking keep every reviewer measured over time.

  5. 05

    Deliver

    Versioned data, with rationale and provenance attached to every item.

06Why Alura

Not a labeling marketplace.

Typical labeling marketplace Alura
Who does the work Generalist annotators, often anonymous Verified professionals with checked credentials
Quality control Majority vote and spot checks Domain-specific review, with expert adjudication
Languages English first, translated later Multilingual from day one, with regional rules
What you get back Labels Labels, rationale, and the failure modes behind them

07Where we’re going

Finance is where we start. It isn’t where we stop.

The same expert-data and evaluation infrastructure carries over to any field where a wrong answer has real consequences.

  • Financial servicesNow
  • InsuranceNext
  • LegalNext
  • HealthcareNext

Who we work with

  • AI companies

    Training data and evaluations for finance-capable models and agents.

  • Fintechs

    Evals before your assistant talks to a customer.

  • Accounting platforms

    Task environments for bookkeeping, close, and reconciliation agents.

  • Insurers

    Claims, underwriting, and policy-document reasoning, checked by practitioners.

  • Banks

    Risk, compliance, and multilingual customer interactions.

08Start a pilot

Building AI for work where a wrong answer costs something?

Tell us what your model has to get right. We’ll scope a pilot around it, with the experts, languages, and rubrics it needs.

hello@alura.ai