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Potential dataset inputs
Authorized ticket lifecycles, release histories, incident response tasks, issue-to-fix traces, QA scenarios, and technical support outcomes.
Industries & use cases
The world’s workflows are becoming AI’s training ground.
Domain knowledge lives in everyday operations. We focus on the structure of work: what happened, what action followed, and how the outcome can be evaluated.
01 / Sector opportunities
Where context becomes model signal.
01 / SOFTWARE & IT
Software engineering and IT operations
Engineering agents need examples that go beyond a code snippet: the bug report, repository context, diagnostic steps, tool interactions, resolution, and verification.
02 / CUSTOMER EXPERIENCE
Support and service operations
Teach systems to understand actual customer intent, constraints, handoffs, and the steps leading to an appropriate resolution.
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Potential dataset inputs
Support conversations, escalation pathways, troubleshooting journeys, CRM state transitions, and resolution categories—subject to customer confidentiality and privacy requirements.
03 / BUSINESS OPERATIONS
Finance and document-heavy workflows
Business AI must navigate forms, approvals, policies, exception handling, and evidence—often across several systems and document types.
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Potential dataset inputs
Authorized reconciliation cases, anonymized operational artifacts, document extraction examples, policy application, and exception routing. Regulated or sensitive material requires enhanced review.
04 / COMMERCE
Retail, restaurants and frontline operations
Everyday business tasks can expose meaningful relationships among demand, decisions, staff actions, operational constraints, and outcomes.
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Potential dataset inputs
Inventory and replenishment workflows, scheduling exceptions, catering or order journeys, vendor coordination, and service recovery examples.
05 / MULTIMODAL AI
Language, media and perception
Ground language and vision systems with context-rich, rights-appropriate source material across modalities and real scenarios.
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Potential dataset inputs
Multilingual audio, natural conversations, image/video collections, multimodal context pairs, and expert-labeled evaluation examples.
02 / Source responsibly
Industry complexity is part of the specification.
A dataset that seems useful in principle may not be transferable, permissible, or suitable for model use. We begin with those constraints instead of discovering them after collection.
Before a dataset is approved
Potential rights, confidentiality agreements, sensitive information, customer consent, geographic and sector rules, and security handling all need consideration. Specific legal and regulatory conclusions should be established with qualified counsel and the buyer’s security team.
Start a conversation
Discuss a data needBuilding an AI system for a particular industry?
Bring the workflow and success criteria. We’ll explore what authentic, usable examples could look like.