Turn industry expertise into AI capability.

Navaday builds proprietary datasets for AI labs with the businesses and experts who know the work.

Talk to our teamBecome a data partner
SourceDataset structure
  1. InspectionEvaluation tasksQuestions and criteria
  2. ServiceLinked historiesEvents in context
  3. CodeReview datasetsChanges and reasoning
  4. ContractsDecision contextRevisions and rationale
  5. ResearchAnalysis tasksMethods and observations
  6. TelemetryEvent sequencesSignals and conditions

Work with Navaday

The opportunity

Expert work leaves a record the web rarely captures.

Most AI is trained on what was published. In technical fields, the work that matters happens inside businesses, and its record rarely leaves them.

Operating recordsYears of decisions, exceptions and outcomes, kept in the systems a business already runs.
Domain expertiseThe people who did the work, explaining what the records leave unsaid.
Specialized AI data

Training and evaluation data for work the public web cannot teach. Scarce, because one business holds it, and renewed as the business keeps operating.

How we work

From source data to licensed delivery.

Six stages, built around your industry. Open a stage to explore the detail.

  1. Connect the sourceStart with the files and systems your business already uses.
    Source categoriesEngineering
    • DesignModels and drawingsGeometry
    • ProductionPrograms and work ordersProcess
    • InspectionMeasurements and reportsQuality
    • OperationsLogs and maintenance historyContext
    • ReviewNotes and decisionsReasoning
  2. Agree the scopeDefine rights, sensitive information and permitted uses with the data partner.
    Define the releasePartner review
    Rights
    Confirm authority to license
    Sensitive information
    Identify exclusions and required treatment
    Technical content
    Preserve context needed for the task
    Release scope
    Agree on fields, files and permitted uses

    The release is defined with the data partner for the intended use.

  3. Add domain expertiseCombine your team’s operational knowledge with expert interpretation and review.
    • OperatorsExplain terminology, working conditions and how records connect.
    • Domain expertsInterpret the evidence and define what a good answer requires.
    What enrichment captures
    Evidence
    Source references
    Context
    Assumptions and conditions
    Reasoning
    Basis for a judgment
    Review
    Criteria and unresolved questions
  4. Build the datasetStructure linked records, training tasks or evaluations around the lab’s requirements.
    Task structureTraining · evaluation
    prompt
    The question or task
    context
    Relevant source material
    reference
    Expert answer and reasoning
    rubric
    Criteria for evaluation
    provenance
    Source and review references
    split
    Training or evaluation allocation
  5. Support buyer evaluationGive AI labs a private room to review scope, schema and approved samples.
    Buyer evaluationPrivate room
    Dataset presentationThe information behind a buying decision
    • ScopeWhat does the dataset cover?
    • SamplesWhat can the lab inspect?
    • SchemaHow is the data organized?
    • TermsWhich uses can be licensed?

    Share approved material with authorized recipients.

  6. License and deliverAgree on use and delivery terms, with opportunities for updates and further licensing.
    Structure the agreementLicensing
    Permitted use
    Training, fine-tuning or evaluation
    Delivery
    Dataset version and format
    Commercial terms
    Scope, duration and payment
    Ongoing work
    Updates and future requirements

    Each new use or delivery follows the agreed terms.

See a sample of our pipeline

Build a data partnership around your industry.

Tell us about your data or the task your model needs to learn. hello@navaday.ai