Quality Assurance (QA) is an intensive endeavour that feels very repetitive to humans. In this article, we explore the potential of using Agentic AI to automate this process. In particular, we’ll apply this methodology to a real-world example: ensuring that parallellm.com (the “target website”) runs smoothly, round the clock. Any issues that do arise will be flagged very quickly.

The application of Agentic AI to QA has great potential, since traditional website scanning is notoriously difficult. Their HTML layouts are liable to change at any moment. AI Agents, when set up in the right way, can tolerate such changes, whereas traditional heuristic rules are hard-coded and brittle against this effect.

I’m absolutely thrilled to announce the Beta launch of Parallellm - supercharge your AI conversations in parallel!

With Parallellm, you can cross-compare answers from several LLMs (without switching tabs), spot hallucinations very quickly, and discover which LLM models excel or struggle for your use case.

🫵 Beta testers needed! Please try out the platform for FREE (no card required). I’d be very grateful for any feedback you might have. If you feel you want to upgrade, you can do it later. Payments are secure and powered by Stripe.

I am delighted to announce that ZL Labs is partnering with Lanboss AI, helping them on their mission to deliver secure and AI-compliant products in commercial and education spaces.

As a part of this venture, I will be helping Lanboss build out the novel Orange Octopus product, an AI proxy service that intelligently enables organizations and schools to harness the power of AI in a safe and controlled manner.

Adopters of the Orange Octopus will benefit from centralised access and visibility of AI interactions, intelligent platform selection and routing, and enterprise-grade security controls. The product will be supported and enhanced by the expertise and years of experience in Machine Learning and AI that I bring.

XKCD comics have become a cornerstone of internet culture, particularly in technical circles, with their witty takes on science, programming, and mathematics. However, finding the perfect XKCD for a particular topic or reference can be challenging - there are now over 3,000 comics in the archive, and traditional search methods rely heavily on exact keyword matches or remembering specific comic numbers.

This project explores how modern Natural Language Processing (NLP) techniques can be used to search XKCD comics semantically, understanding the underlying meaning rather than just matching keywords. By applying vector embeddings and Retrieval Augmented Generation (RAG) to comic descriptions, we can now perform a search based on concepts, themes, and abstract ideas.

I am delighted to announce that ZL Labs is now providing expert training services to Skiller Whale, supporting their mission to deliver high-impact, interactive micro-workshops to tech teams across Europe.

In this role, I’ll leverage my expertise in AI, Python and SQL to deliver Skiller Whale’s personalised learning plans, providing focused, interactive coaching and hands-on exercises designed to rapidly upskill technical teams.

Stay tuna-ed for further updates! 🐟 🗞️