Insights
Why Your Enterprise Needs a Unified Approach To Generative AI
Discover why a strategic, enterprise-wide AI strategy is essential to deliver real value, with tangible support, security and usability across the business.
RAG, Agents and Graph: Your AI Compliance Dream Team
The dream team of AI compliance - read on to discover how Retrieval Augmented Generation (RAG), AI agent frameworks and knowledge graph techniques combine to support regulatory compliant AI systems.
Automating Data Classification with AI Agents
How to use AI agents to automate your data classification tasks (metadata, labeling, schema inference) and significantly reduce manual effort.
The DNA of an AI Agent
A detailed look at AI agents and how they work, including components, reasoning, autonomy and how AI agents are shifting the paradigm for software design.
Setting an Acceptable Use Policy for Generative AI in Your Business
Why and how enterprises need to build and maintain an Acceptable Use policy, which should create guardrails, rules and oversight for how generative models are used internally.
AI Agents and the Three Lines of Defence: A Banking Inspired Approach
This blog provides an AI governance framework for highly-regulated industries, using the banking industry as inspiration.
5 Essential Best Practices for LLM Governance: A Framework for Success
Key practices for organising, monitoring and securing large language model systems in enterprise settings.
The Dawn of Autonomous Agents: Transforming Business Process Automation
Autonomous agents are redefining automation, from driving smarter workflows, to reducing manual effort, leading to new possibilities unlocked.
Autonomous Agents: The Next Frontier in AI-Driven Business Transformation
See how autonomous agents are driving the evolution of AI in business, bringing intelligence, adaptability and speed to every single business process.
Securing the Generative AI Software Supply Chain
Sharing the security risks in the generative AI software pipeline and how organisations must embed security at every stage, from model development to deployment.
Generative AI - With Great Power, Comes Even Greater Responsibility
Explore the essential steps for governing generative AI in this blog by Ben Saunders. As generative AI becomes a powerful tool for innovation, it's crucial to establish robust guardrails and controls to prevent unintended consequences. Learn about the potential risks of unrestricted AI use, including ethical and legal implications, and discover how to implement technical controls and governance frameworks to ensure responsible AI deployment. Stay ahead in the digital age by adopting effective governance strategies that balance innovation with accountability.
To Fine Tune, or Not to Fine Tune, That is the Question - How LLMOps Can Help
In the rapidly advancing field of Artificial Intelligence, particularly with Large Language Models (LLMs) from OpenAI, Google, and others, fine-tuning these models remains essential. This blog explores why fine-tuning is crucial for industry-specific applications, enhancing customer experience, and boosting employee productivity. It delves into LLMOps, a specialized framework ensuring efficient, reliable, and compliant operations of LLMs. By focusing on data management, model development, prompt engineering, deployment, observability, ethical evaluations, and reinforcement learning, organizations can harness LLMs' full potential while maintaining regulatory compliance and operational excellence.