Real-world data systems for auditable AI
YPAI manufactures multimodal data products and evaluation sets designed for domain shift, regulated environments, and deployment inside your security perimeter.
This capability layer connects into sovereign model deployment and agent governance when required.
What breaks outside the benchmark
Standard training data fails when deployment conditions diverge from collection conditions. We manufacture data products that anticipate and cover this gap.
Domain shift is the real bottleneck
Models trained on clean inputs degrade when microphones, cameras, lighting, acoustics, and workflows change in production. We build datasets that expose and cover this variance before deployment.
Long-tail human variance
Real users differ from benchmark speakers. We capture demographic, dialectal, and behavioral diversity.
Regulated data constraints
Some deployments cannot use public data. We manufacture first-party datasets with audit trails.
Evaluation before deployment
Standard benchmarks mask production failure modes. We design evaluation sets that reflect your actual operating conditions, not sanitized lab environments.
Data products across input types
Audio, video, documents, and sensor data captured under controlled variability with consent verification and governance artifacts.
Speech data built for real conditions
Capture speech in the environments where systems fail: in-vehicle noise, reverberant rooms, far-field pickup, accented speakers, emotional states. Multi-device recording captures microphone variability.
- In-vehicle and in-cabin audio
- Far-field and close-talk capture
- Multi-accent, multi-dialect pools
- Emotion and speaking style variation
From specification to production delivery
Each engagement produces a defined data product: coverage specification, collection execution, delivery formats, and optional evaluation sets.
Coverage specification
- - Demographic matrix Age, gender, accent, dialect distributions
- - Environment conditions Noise types, lighting, device profiles
- - Edge case allocation Quota for low-resource segments
Collection execution
- - Consent and provenance GDPR-aligned, per-sample audit trail
- - Multi-device capture Synchronized cross-device recording
- - QA pipeline Automated + human review gates
Delivery formats
- - Raw and processed Originals plus ML-ready features
- - Annotation layers Transcripts, labels, bounding boxes
- - Integration support S3, GCS, Azure, on-prem delivery
Evaluation sets
- - Domain-shift benchmarks Expose production failure modes
- - Held-out segments Reserved speakers, environments
- - Regression tracking Versioned sets for iteration
Evaluation sets designed for domain shift reveal failure modes that standard benchmarks hide. We can build held-out test data that reflects your actual deployment conditions.
Evaluation that reflects production
Cross-device evaluation
Device variabilityTest performance across the microphone, camera, and sensor variants your users actually have.
Cross-environment test sets
Environment shiftEvaluate in the acoustic and visual conditions where lab-trained models degrade.
Demographic coverage analysis
Fairness testingVerify performance equity across age, accent, dialect, and behavioral segments.
Adversarial conditions
Robustness testingEdge cases, corrupted inputs, and stress scenarios that break production systems.
Temporal drift detection
Drift monitoringHeld-out data from different time periods to detect model staleness.
Regression test suites
CI/CD integrationVersioned evaluation sets for tracking model performance across iterations.
Consent, provenance, and audit readiness
We can deliver documentation aligned to your risk profile: consent records, provenance logs, demographic breakdowns, QA audit trails, and data processing agreements. Format and depth depend on your compliance requirements.
Yes. We support consent-based collection, legitimate interest frameworks, and contractual necessity depending on jurisdiction and use case. Legal basis is documented per-sample.
Primary operations are EU-based (Norway). We can arrange US residency or on-premise delivery for restricted deployments. Residency requirements are defined in the project scope.
Consent is collected through our platform with clear disclosure of data use, retention, and rights. Participants can withdraw, and we support downstream anonymization or deletion requirements.
Yes. We routinely sign DPAs and can operate under client-provided agreements where feasible. Standard Contractual Clauses (SCCs) are available for cross-border transfers.
For governance questions, contact: dpo@yourpersonalai.net
Multimodal Data Systems
Real environments, real variance, defined QA
Sovereign AI Infrastructure
Deploy models inside your perimeter when required
Agentic Systems & Governance
Audit trails and HITL gates for high-stakes workflows
Need an integrated deployment? We connect data products to sovereign model hosting and governed agent workflows.
From scoping to production dataset
Describe your use case
What modalities, environments, and constraints define your deployment?
Technical assessment
We evaluate feasibility, define QA rubrics, and identify governance requirements.
Pilot delivery
Small-scale data delivery to validate quality gates, formats, and integration.
Production scale
Full dataset delivery with ongoing QA, versioning, and support.
Engineering intake
Inquiry details are treated as confidential. You will receive a response from technical staff.
We're reviewing your requirements.
What happens next
- Within 1 business day: Technical assessment of your use case
- If suitable: Coverage specification and scoping call
Inquiry details are treated as confidential.
We will define the data product required for your deployment context and constraints. If YPAI is not the right fit, we will say so directly.
Talk to an engineer