Services
Multilingual data services
Multilingual AI is only as good as the data behind each language, and the languages that matter most to a Canadian buyer are often the ones the global market treats as an afterthought. Corpshore Canada delivers multilingual data services across more than thirty-five languages, with particular depth in Canadian French, where models consistently underperform because the training data does not exist in volume. This programme builds it, matched by language variety rather than treated as regional colour, spanning Quebec, Acadian, Franco-Ontarian and western francophone communities. The practice sits inside an AI capability ranked fifth of fifty AI outsourcing companies worldwide by Outsource Accelerator, and it draws on a company that has operated across eighteen or more countries since 2015. Work is produced by native speakers on Canadian contracts, with quality managed as a gate and inter-annotator agreement measured, under Canadian privacy law.
How the service works
- 1
Language and variety scoping
We scope the languages and, within them, the varieties that matter for the use case, because Canadian French is not European French and treating them as one produces a model that sounds wrong to the people who matter most. The output is a sourcing and quality plan that names the varieties rather than lumping a language into a single bucket.
- 2
Native-speaker sourcing
Data is produced by native speakers matched by variety, on Canadian contracts where the work is delivered from Canada and through the group network for the wider language set. Regional variation is captured as signal, so the dataset reflects how a language is actually used across communities rather than a normalised standard nobody speaks.
- 3
Production with measured agreement
Translation, transcription, annotation, localisation and cultural adaptation are produced in batches with layered review and measured inter-annotator agreement against the programme threshold. A batch that misses does not ship, and where a guideline reads differently across a language community we treat that as a signal to refine rather than an error to bury.
- 4
Delivery, audit and iteration
Delivered data carries its language, its variety, its provenance and its consent chain, so it can be audited by language rather than trusted as a blended whole. As the model reveals which languages and varieties are weak, we iterate the sourcing and the guidelines, because multilingual coverage is a programme that deepens rather than a one-time delivery.
How we deliver it from Canada
Delivery of Canadian French and the core Canadian languages is from a distributed Canadian workforce, coordinated by a quality and programme team in Ontario, Quebec and Alberta, with the wider set of more than thirty-five languages produced through the group network across eighteen or more countries. Every language is matched by native speakers and, where it matters, by variety. Data is processed to your residency requirement including Canadian-only where a public sector buyer asks, and every dataset carries a documented consent and governance chain under Canadian privacy law.
Pilot, defined languages
A small native-speaker team with a quality lead proving the guideline and inter-annotator agreement on the target languages and varieties before volume is committed.
Programme, sustained multilingual volume
Native-speaker pods per language with a dedicated quality layer, variety matching and per-batch gating, sized to your throughput with output pricing and measured agreement.
Practice, broad language coverage
A standing practice across the full language set, blending Canadian delivery for French and core languages with global capacity for the wider set, under one governance framework.
Compliance and data handling
Multilingual data work is governed under PIPEDA and, where Quebec residents' data is in scope, Law 25, including its provisions on the collection and use of personal information and, where the data feeds an automated decision, the transparency that regime requires. Speakers delivering from Canada are engaged under Canadian labour standards, every dataset carries a documented consent chain, and cross-border handling for the wider language set is documented transparently in line with PIPEDA. Sensitive content is access-restricted and handled under the relevant group security framework.
Technology
We work in your annotation, translation and localisation tooling where you have it, and bring proven multilingual tooling where you do not, integrated under your governance rather than locked behind ours. Quality tooling captures inter-annotator agreement, variety tagging and provenance per language as first-class outputs. Specific platform choices are confirmed against the languages and the residency requirement during scoping rather than prescribed here.
How performance is measured
- Inter-annotator agreement per language against the threshold
- Batch acceptance and rework rate by language and variety
- Coverage across the target languages and varieties
- Throughput against the committed schedule
- Provenance, variety and consent completeness on delivered data
Reporting is broken out by language and variety, because a blended multilingual quality number hides exactly the weak languages a buyer needs to see. We report agreement, acceptance and coverage per language, and surface where a variety is thin so it can be sourced rather than quietly under-represented. Governance runs on an agreed cadence with the analysis prepared by us.
Where this applies
Technology and SaaS
Multilingual training, evaluation and localisation data for model developers who need Canadian French depth and native-speaker coverage across a wide language set with auditable provenance.
Government and public sector
Bilingual and multilingual data for services with federal language obligations, delivered with Canadian data residency and Canadian French matched by variety rather than translated.
Healthcare and life sciences
Multilingual clinical and patient-facing data produced by native speakers, on data that stays in Canada, with conservative handling of sensitive categories and a documented consent chain.
Pricing and engagement models
Multilingual data is priced per unit of output with quality gates, as a dedicated multilingual programme, or as a pilot that proves coverage and agreement on the target languages before you commit volume. Output pricing suits stable, high-volume languages, a dedicated programme suits broad or evolving coverage, and the pilot suits a buyer who wants measured agreement per language and variety before scaling.
Frequently asked questions
Why is Canadian French treated separately from French?
Because they are not the same, and a model trained mainly on European French sounds wrong to a Quebec user within a few sentences. Canadian French training data does not exist in the volume the language deserves, so we build it with native speakers matched across Quebec, Acadian, Franco-Ontarian and western francophone varieties, capturing the variation as signal rather than normalising it away.
How many languages can you cover?
More than thirty-five, drawing on a company that has operated across eighteen or more countries since 2015. Canadian French and the core Canadian languages are delivered from a Canadian workforce, and the wider set is produced through the group network, every language matched by native speakers and, where it matters for the use case, by regional variety.
How is quality controlled across many languages?
The same way it is on a single language, per language rather than blended. Every batch is gated on measured inter-annotator agreement against a threshold, reported by language and variety so a weak language cannot hide inside a flattering average. Where a guideline reads differently across a language community, we treat that as a signal to refine the guideline rather than an error to bury.
Who produces the multilingual data?
Native speakers, matched by variety, engaged under Canadian labour standards where the work is delivered from Canada and through the group network for the wider language set. Native fluency and cultural context are the point, because a fluent non-native or a machine translation misses the idiom, register and usage that make multilingual data actually useful to a model.
How is multilingual data governed and where does it sit?
Under PIPEDA and, where Quebec residents' data is in scope, Law 25. Canadian delivery keeps data in Canada by default and to your residency requirement including Canadian-only, cross-border handling for the wider set is documented transparently in line with PIPEDA, and every dataset carries a documented consent chain with sensitive content access-restricted under the relevant group security framework.
Does this connect to your bilingual contact centre work?
Yes. The Canadian French capability is the same one the bilingual services and conversational AI lines draw on, matched by variety and reviewed by French-first quality staff. That shared depth is why a multilingual data programme, a bilingual assistant and a bilingual operation can sit under one governance framework rather than being sourced from three unrelated vendors.
Build your Canadian team
Tell us the work, the languages and the coverage you need. You will have a considered response within six hours, or book a discovery call now.
Looking for a role rather than a partner? Explore careers at Corpshore Canada