At Persephia, we love Artificial Intelligence (AI). That’s why we’ve spent the last decade researching it, teaching it, and applying it in industry applications. In the last few years there’s been a dramatic increase in interest in how AI can be applied to business operations. Specifically, many clients are interested in Generative AI (think large language models, image generators, etc.). While this is the area of AI that our team specializes in, we still have a wealth of experience across the incredibly broad field that is Artificial Intelligence. Because of this, we’re able to cut through the Generative AI hype to match clients with Artificial Intelligence solutions that properly meet their needs. In fact, some problems are still best solved without any Artificial Intelligence at all.

AI provides us with a set of powerful tools for solving specific kinds of problems. When applied correctly, AI can transform how your business operates. We’re here to help you find the areas where AI can actually create beneficial change in your business, design the right solutions, and make them work for you.

What We Offer

  • Opportunity Assessment – We’ll evaluate your workflows and challenges to determine where AI can create measurable impact.
  • Feasibility Analysis – Not every problem needs AI. We’ll tell you when simpler, more cost-effective solutions make more sense.
  • Prototype Development – From proof-of-concept to production-ready systems, we can help you build, test, and refine AI-driven tools.
  • Integration & Support – We’ll ensure AI systems work seamlessly with your existing processes and team.

Why Choose Us

  • Research-Level Expertise – One of our consultants holds a PhD in Artificial Intelligence, bringing cutting-edge academic knowledge to your project.
  • Real-World Experience – We’ve implemented AI in practical business contexts, avoiding common pitfalls and inefficiencies.
  • Honest Guidance – We’ll only recommend AI where it’s the right fit, and we’ll immediately tell you if it’s not.

Publications

Approaches to scalable, sustainable, and ethical natural language processing research in the face of rapid development

Ashleigh Richardson. PhD dissertation, published by The University of Queensland in 2024.

This thesis explores major concerns created by the rapid pace of development in natural language processing (NLP). Developments to state-of-the-art in NLP have been propelled by the creation of new machine learning models, bigger datasets, and more compute power. While these advances have been beneficial in many ways, the speed at which they have occurred has caused its own set of concerns around scalability, sustainability, and ethicality in research practices. In this thesis, three studies are reported that investigate methodologies and provide tools for research and investigation of NLP systems and datasets that are accessible to non-technical users.

A Systematic Study Reveals Unexpected Interactions in Pre-Trained Neural Machine Translation

Written by Ashleigh Richardson and Janet Wiles. Published in the International Conference on Language Resources and Evaluation (LREC) by the European Language Resources Association in 2022.

This paper presents a systematic study of the interactions between factors when pre-training and fine-tuning custom transformer networks for neural machine translation on data-constrained tasks.