Synthetic business data
Purpose-built records for fictional businesses, with consistent inputs, realistic exceptions and traceable outcomes.
KLYRONE · AI DATA SERVICES
Industry expertise.
Original AI data.
The hardest part of a workflow rarely lives in a textbook. It lives in the exceptions, the decisions and the reasons behind them.
Our domain experts create original scenarios, synthetic business data and specialist workflows for AI training and evaluation—from electric and gas billing to healthcare RCM, EDI and financial operations. Built from professional knowledge, not your private business records.
For AI labs, data companies and enterprise AI teams.DEEP DOMAIN EXPERTISEWORKFLOW DESIGNCONTINUOUS CURATIONFRONTIER AI TRAINING
BEYOND MORE DATA
Capture the judgment.
Not just the document.
A useful example connects the input, the decision, the evidence and the outcome. That is the level of context we aim to scope with each partner.
Expert-authored tasks
Original domain scenarios, reference responses and review rubrics designed around the capability you want to test.
Evaluation sets
Representative cases and difficult edge cases, with agreed scoring criteria and clearly documented limitations.
OUR SPECIALIST DOMAINS
Industry expertise.
Down to the exception.
We bring operational knowledge and domain experts across these six areas. Together with your team, we turn that expertise into original training tasks and evaluations. The examples below use purpose-built scenarios and synthetic business records.
Energy billing · electric & gas
The operational detail behind utility bills: usage, rates, adjustments, exceptions and reconciliation.
Example pilot: investigate a billing discrepancy using supplied meter reads, tariff rules and adjustment history.
EDI workflows
Electronic data interchange across transaction mapping, validation, acknowledgements and exception handling.
Example pilot: trace a rejected transaction, identify the mapping or validation issue and propose a correction against the supplied specification.
Healthcare revenue cycle
Healthcare RCM workflows spanning eligibility, claims, denials, payment posting and accounts-receivable follow-up.
Example pilot: review a synthetic denial case, identify missing evidence and select the next administrative action—not a clinical decision.
Banking & finance
Transaction operations, financial reconciliation, document review and evidence-led exception resolution.
Example pilot: reconcile a transaction across supplied records and explain when an unresolved exception requires escalation.
Accounting & bookkeeping
Invoice processing, ledger classification, bank reconciliation, month-end close and reporting workflows.
Example pilot: resolve a reconciliation difference and document the proposed treatment with supporting evidence.
Tax compliance
Document preparation, rule application, reconciliations and review checkpoints for jurisdiction-specific tax workflows.
Example pilot: assess a case against a supplied, dated rule set, identify missing information and flag where professional review is required.
EXPERTS THROUGHOUT THE LIFECYCLE
Not a one-time data drop.
A continuous learning loop.
Domain experts stay involved as workflows evolve: authoring scenarios, reviewing outputs, resolving ambiguous cases and refining the next iteration. The aim is training material that reflects how work actually gets done—not just how a process is described.
Design the workflow
Define inputs, permitted actions, decision points, evidence requirements and escalation boundaries.
Curate and challenge
Review reference outcomes, capture difficult exceptions and calibrate scoring rubrics across reviewers.
Improve for the next run
Use evaluation feedback to revise tasks, version changes and maintain separate training and held-out evaluation sets.
FROM DOMAIN KNOWLEDGE TO TRAINING MATERIAL
Built for your pipeline.
Validated in a pilot.
Agree schemas, task coverage, reference answers, scoring criteria and provenance before scaling. Training readiness is assessed against your requirements—not assumed from the size of a dataset.
- 01
Define the task
Agree the domain, model use case, formats, coverage and acceptance criteria before creating the pilot.
- 02
Create the scenario
Design fictional businesses, synthetic records and realistic exceptions from domain expertise. Define consistency rules and expected outcomes.
- 03
Design with domain experts
Build a representative pilot with task specifications, reference outcomes, review rubrics and documented limitations.
- 04
Evaluate, refine, repeat
Use reviewer findings and model failure patterns to improve coverage, difficulty and consistency. Scale against agreed acceptance criteria.
ORIGINAL BY DESIGN
Professional knowledge.
Not private records.
This service creates new material from domain expertise. It is not a programme to collect or sell customer, patient, employee or client records.
- Original scenarios and synthetic records for fictional businesses.
- No confidential client documents or private records required.
- Expert-reviewed reference answers and documented quality checks.
- Agreed delivery scope, usage rights and acceptance criteria.
Synthetic does not automatically mean training-ready. Each pilot is reviewed for consistency, realism and suitability for the intended task.
SERVICE QUESTIONS
Set the right expectations.
Who is this for?
AI labs, specialist data providers, evaluation teams and enterprises that need original, domain-specific tasks, synthetic business data and expert review.
Do you need our customer data?
No. This service is built around original scenarios and synthetic records created from professional knowledge. We do not need your customer records to scope or design a pilot.
What can we commission?
A scoped pilot of synthetic records, expert-authored tasks, reference outputs and evaluation rubrics. Formats, volume, reviewer expertise, delivery dates, usage rights and pricing are agreed before work begins.
Can you work with our task specification?
Yes. Share your domain, task definition, intended use, sample schema and quality criteria. We will assess fit and propose a focused pilot.
What should we share first?
A non-confidential brief covering your target domain, AI use case, desired format, approximate volume and timeline. Please do not send private records, credentials or confidential client documents when booking or emailing.
BUILD WITH INDUSTRY CONTEXT
What does your AI
need to understand?
Tell us the domain, the task and what good looks like.
Let’s find out whether a focused pilot makes sense.