Description
Pangeanic is a multilingual AI data and language technology company, founded in Valencia in 2000, that has moved from translation services into supplying the data, human feedback, and deployment infrastructure behind AI systems. It works with AI labs, enterprises, and public-sector organizations that need language coverage, human oversight, and control over where their models run.
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The company's work covers three areas. The first is data for AI: licensed and custom-built datasets across text, speech, audio, image, video, and multimodal formats, along with annotation, expert review, and RLHF (reinforcement learning from human feedback) services to align model behavior with a client's terminology and policies. The second is model customization: selecting, fine-tuning, and evaluating small, task-specific language models, including retrieval-augmented grounding in a client's own knowledge, aimed at organizations that want a model matched to one workflow rather than a large general-purpose system. The third is the ECO Intelligence Platform, which connects adaptive machine translation, machine translation quality estimation, document translation across PDF, Word, PowerPoint, Excel, and scanned files, and multilingual retrieval, and can be deployed on private cloud, on-premises, or air-gapped infrastructure for organizations with strict data-residency requirements. Pangeanic still offers standalone machine translation and enterprise document translation as part of its Language Tech line, alongside the newer training-data and sovereign-AI work.
Pangeanic points to projects such as contributing multilingual data, human feedback, and alignment work to Spanish- and Catalan-language models built with the Barcelona Supercomputing Center, and supporting secure document translation for the Spanish Tax Agency, as examples of its data and deployment work in production. The company positions itself for AI labs sourcing training and evaluation data, enterprise language teams automating translation workflows, and private- and public-sector teams that need to deploy AI under their own infrastructure and governance. Pricing is quoted per project rather than published, and prospective clients are asked to describe their languages, data types, volume, and timeline before Pangeanic scopes the work.
- CategoryMachine Learning Platforms
- Pricing ModelContact sales
- DeploymentOn-premises, Private Cloud
- PlatformsWeb
Pangeanic's Core Features
Licensed and custom multilingual datasets: text, speech, audio, image, video, and multimodal
Bespoke data collection and specialist annotation for defined tasks and domains
RLHF and human-feedback services to align model behavior with client terminology and policy
Small language model selection, fine-tuning, and evaluation for task-specific deployment
Retrieval-augmented grounding of models in a client's own controlled knowledge
Adaptive machine translation with quality estimation (MTQE) for routing content to human review
Enterprise document translation across PDF, Word, PowerPoint, Excel, and scanned files
Private cloud, on-premises, and air-gapped deployment options for sensitive workloads
Data masking and anonymization for regulated or sensitive datasets
How to use Pangeanic?
Define the requirement: Describe the model task, languages, data types, volume, and timeline
Source or commission data: License an existing dataset from the catalog or commission a custom collection
Prepare and review: Have the data annotated, labeled, and reviewed by human experts
Align or customize: Use RLHF and evaluation sets to align a model, or fine-tune a small language model to the task
Deploy through ECO: Connect translation, retrieval, and quality estimation into a private-cloud or on-premises workflow
Evaluate in production: Use human-validated evaluation sets to compare models across languages and domains over time
Pangeanic's Use Cases
- RLHF and model alignment
- Sovereign AI deployment
- Enterprise document translation
- Small language model customization
