Discover how Intelligent Agent AI can revolutionise your data management with Oakland.
As generative AI continues to advance at pace, more businesses are adopting it into their data management and day-to-day operations. Picking off-the-shelf tools for your AI is simple and straightforward. Still, these ready-made generative systems don’t work seamlessly with your business, thanks to their one-size-fits-all approach. An Intelligent Agent, on the other hand, creates a new and fresh spin on generative AI, functioning as a virtual worker and performing the exact tasks your company requires.
In this guide, we’ll uncover all the benefits of an Intelligent Agent approach to your AI data strategy. Need more context? Explore our AI guide for a broader look at how we use artificial intelligence to drive insights from your data.
What is an Intelligent Agent in AI?
Intelligent agents are a natural evolution of the LLMs we are currently seeing enter the market. They are layered on top of large language models (such as OpenAI’s GPT model) and provided with specific instructions. At the core of an agent is the instruction to create a plan in response to a given problem – and then execute that plan. The artificial agents are also provided with powerful tools and a memory store to allow them to actually DO things for your company. These tools can be as simple as the ability to respond in plain text – but can be as complex as writing results back to a database, alerting employees through text, or creating graphical executive summaries.
Memory stores are also crucial to the work of an agent. They can be short term stores for use immediately, or a significantly larger body of corporate knowledge to be drawn on.
By leveraging these resources, artificial agents function effectively as artificial workers in your organisation.
What Makes Intelligent Agents Special?
There are a few key traits that make Intelligent Agents so incredibly useful, including:
- Autonomous Decision Making: Intelligent Agents are programmed to make decisions about information without needing direct human intervention.
- Goal Orientation: Each Intelligent Agent is designed to achieve a specific goal, resulting in highly targeted and deliberate outputs.
- Adaptability: Intelligent Agents can reconfigure themselves continually to environmental changes, whereas more basic AI would require expensive and time-consuming retraining to handle similar changes.
- Interactivity: Intelligent Agents work with their environment.
What is a Knowledge-Based Agent in Artificial Intelligence?
Knowledge-based agents are a type of Intelligent AI Agent with a knowledge base inference engine that applies logical rules to an existing knowledge base. For example, a knowledge based agent can read large quantities of documentation that your employees simply wouldn’t have time to work through in order to understand and respond to specific requests.
This makes a Knowledge-Based Agent highly adaptable to your company – an AI that’s truly ready for your specific needs. If knowledge management is a key issue for your company, discover how we’ve used Knowledge-Based Agents to automatically pull data for clients like Network Rail.
What are some Examples of Uses for Intelligent AI Agents?
Intelligent Agents are so customisable they can be used in a variety of applications to make your workers’ lives easier and drive ROI.
Project Analyst
Free up your human project analysts from repetitive analytic tasks using an Intelligent Agent with capabilities to interpret free text project documentation, interrogate supporting data and summarise insights.
Asset Historian
An Intelligent Agent can work as an Asset Historian by reading and supporting asset records, interrogating supporting data from many different datasets and providing a single comprehensive view of the asset. It can also answer questions about the asset from staff.
Resource Allocation
Assign tasks effectively to the right employees within your company using an Intelligent Agent. For instance, you could feed CVs into the AI, with which it could then build and populate a skills matrix used to optimise task allocation.
Data Science Co-Bot
Take some of the weight off of your data science team with an Intelligent Agent that can create and execute code to perform ad hoc data preparation, mastering routine task management.
Alert Triage
Read and filter telemetry alerts for your control engineers with an Intelligent Agent using control room policies, asset history and alarm description analysis.
Why Develop an AI Intelligent Agent with Oakland?
Oakland’s Intelligent Agent Framework allows for swift and simple creation and customisation of your generative AI tools so that it fits naturally into your workflow.
It works with your existing data and systems, preventing you from having to take time-consuming detours. Plus, we can use proprietary managed services, open-source technologies or both for a high degree of flexibility and control in your customisation.
We also prioritise your security so no data will ever leave your business or be pushed to public-facing AI models. Our years of experience working with security teams mean you can trust us. And we are also proudly compliant with industry standards, including CIS and ISO 27001.
With forty years of experience, Oakland knows company pain points around data and how decisions are made, and we use that knowledge when creating the ecosystem of virtual agents that we can deploy into your business.
Explore Oakland’s AI service offering to create an Intelligent Agent that will transform your data management, and contact us to learn more about what we can do for your data.
