About YPAI

AI data, evaluation and implementation under one accountable delivery model.

YPAI is a Norwegian AI company based in Oslo. We collect, license, annotate and evaluate multimodal data, and build production AI systems for organisations that need controlled delivery, documented rights and human-verified quality.

Clients can engage YPAI for an individual work package or connect multiple stages across data, evaluation and implementation.

Scope an engagement Become a contributor
Oslo, Norway Global delivery 150+ languages EEA-based processing available where required

Our mission

Make complex AI delivery accountable from source data to production.

AI projects often break at the interfaces between data, models, systems and operations.

One controlled delivery structure data · models · systems · operations

YPAI brings those stages into one controlled delivery structure. Each engagement is built around the actual model, workflow, environment, population and operating requirements, with defined ownership, documented rights, project-specific quality gates and clear acceptance criteria.

The work can begin with collection, licensing, annotation, evaluation, implementation or an existing production system that needs to be improved. Clients choose the stages they need without being forced into a fixed catalogue.

Our vision

AI delivery that organisations can review, operate and improve.

We are building YPAI around a straightforward principle: AI work should remain understandable after it moves into production.

That means data with documented provenance, evaluation tied to real decisions, systems designed around the customer's technology and data boundaries, and delivery records that support review, acceptance and handoff.

The objective is not simply to produce more data or deploy another AI tool. It is to create a delivery path that connects the original requirement to an operating result.

By the numbers

International delivery across data, languages and markets.

YPAI runs large-scale international data programmes across video, image, speech and multimodal delivery through the same operating core.

  1. 150+Languages covered
  2. 210,000+Contributor network
  3. 50+Countries represented
  4. 30 daysEnd-of-contract erasure SLA

  5. Selected organisations served through AI data and evaluation

    Cerence AI Nexdata Hyundai BYD Honda Kia NIO

How we work

A controlled structure for every engagement.

i

Project-specific by design

Each engagement is configured around the intended model, product, workflow, environment and user population. The delivery model is selected from the requirement rather than imposed through a fixed package.

ii

Defined ownership and acceptance

Projects begin with named ownership, decision paths, milestones, quality thresholds, output formats and acceptance methods. This creates a shared basis for production, review and final delivery.

iii

Human judgement where it matters

Human and specialist review can be placed at the stages where automated checks are not sufficient, including:

linguistic qualitydomain accuracyedge casesmodel behaviouroperational exceptions
iv

Documented rights and provenance

Consent records, model releases, rights chains, asset-level provenance, dataset documentation and version history are configured where relevant to the engagement.

v

Flexible delivery architecture

YPAI can support global delivery, customer-environment deployment, private architectures and EEA-based processing where required. Data-processing terms, subprocessors, access controls and processing locations are scoped for the specific project.

vi

Handoff or continued operation

An engagement can end with a defined handoff or continue through evaluation, monitoring and managed improvement. Deliveries can include:

manifestschecksumsdata cardsquality reportstechnical documentationacceptance evidence
iBefore

Project-specific by design

Each engagement is configured around the intended model, product, workflow, environment and user population. The delivery model is selected from the requirement rather than imposed through a fixed package.

iiAt start

Defined ownership and acceptance

Projects begin with named ownership, decision paths, milestones, quality thresholds, output formats and acceptance methods. This creates a shared basis for production, review and final delivery.

iiiThroughout

Human judgement where it matters

Human and specialist review can be placed at the stages where automated checks are not sufficient, including:

linguistic quality domain accuracy edge cases model behaviour operational exceptions

Documented rights and provenance

Consent records, model releases, rights chains, asset-level provenance, dataset documentation and version history are configured where relevant to the engagement.

ivAround

Flexible delivery architecture

YPAI can support global delivery, customer-environment deployment, private architectures and EEA-based processing where required.

Data-processing terms, subprocessors, access controls and processing locations are scoped for the specific project.

vAt close

Handoff or continued operation

An engagement can end with a defined handoff or continue through evaluation, monitoring and managed improvement. Deliveries can include:

manifests checksums data cards quality reports technical documentation acceptance evidence

Work with YPAI

Have a project to scope?

Share the objective, the current starting point and the operating requirements you already know. A project lead will map the appropriate service line, delivery structure and first validation step.

Scope an engagement Explore our services

Frequently asked questions

  1. Where is YPAI headquartered?

    YPAI is a Norwegian company based in Oslo. We deliver projects internationally and configure the operating model around each engagement's geographic, technical and data-processing requirements.

  2. What does YPAI do?

    YPAI provides two connected service lines:

    AI Data and Evaluation: collection, dataset licensing and sourcing, annotation, curation, quality assurance, model evaluation and agent evaluation.

    AI Implementation: discovery, architecture, RAG and knowledge systems, agents, document workflows, automation, private deployment, monitoring and managed improvement.

    Clients can purchase one stage or connect the stages required for a broader engagement.

  3. Who does YPAI work with?

    YPAI works with AI companies, model developers and enterprise teams across automotive, mobility, financial services, healthcare, industrial operations, the public sector and other domains with demanding data or implementation requirements.

    Selected organisations served through AI data and evaluation include Cerence AI, Nexdata, Hyundai, BYD, Honda, Kia and NIO.

  4. Can YPAI support EEA-based processing and private deployment?

    Yes, where the project requires it. YPAI can configure EEA-based processing, customer-environment deployment, private architectures and restricted-egress models where appropriate.

    The final architecture, subprocessors, transfer considerations, access controls and data-processing terms are agreed for the individual engagement.

  5. Does YPAI build AI systems as well as datasets?

    Yes. YPAI builds production AI systems around organisational workflows, documents, permissions, data boundaries and existing technology.

    This can include RAG systems, grounded assistants, agents, document automation, enterprise integrations, custom AI applications and the evaluation and monitoring required to operate them.

  6. How does YPAI recruit contributors, annotators and reviewers?

    YPAI maintains an international contributor network and recruits additional participants and specialists around project-specific requirements.

    Selection can account for language, dialect, geography, domain knowledge, equipment, environment, availability and other coverage requirements. Consent, rights, review and quality controls are configured for the work being performed.

Prefer email? contact@ypai.ai