Introducing spaCy Tailored Pipelines

2022-02-08 · Source: Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Fundamental Awareness, quick

Summary

Explosion has launched "spaCy Tailored Pipelines," a new development service offering custom natural language processing (NLP) solutions. This service is designed to build bespoke NLP pipelines tailored to specific client needs. These custom pipelines are delivered in a standardized format, utilizing spaCy's established projects system. This approach ensures that clients receive specialized text processing tools that are both consistent and easily integrated into their existing technical infrastructure, providing a direct solution for unique linguistic processing requirements.

Key takeaway

For AI Engineers or Directors of AI/ML seeking highly specialized natural language processing capabilities, Explosion's new spaCy Tailored Pipelines service offers a direct solution. If your team faces unique linguistic challenges not met by generic tools, consider this service to acquire custom-built, standardized NLP pipelines. This can streamline development and integration of bespoke text processing features into your applications.

Key insights

Explosion now offers custom spaCy NLP pipelines via a new development service.

Method

Explosion builds custom NLP pipelines, delivering them in a standardized format via spaCy's projects system.

Topics

• spaCy
• Natural Language Processing
• Custom Pipelines
• Development Services
• Text Processing

Best for: NLP Engineer, AI Engineer, Director of AI/ML

Related on AIssential

• Explosion, NLP, Generative AI, Entrepreneurship — SpaCy provides an opinionated, production-ready NLP pipeline, emphasizing practical application, developer experience, and sustainable business models.
• 3 SpaCy Tricks for Efficient Text Processing & Entity Recognition — Optimizing spaCy pipelines requires tailoring component usage, utilizing batch processing, and integrating rule-based entity recognition.
• spacy-llm: From quick prototyping with LLMs to more reliable and efficient NLP solutions — spacy-llm integrates LLMs into spaCy for structured NLP, moving from rapid prototyping to reliable, cost-efficient solutions.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai.