We build custom AI solutions powered by Intelligent Agents.
Intelligent Agents are AI powered virtual workers. With powerful tools and careful training, Intelligent Agents can plan and execute complex tasks in human-like ways. This allows them to act like members of your team, not bots.
Intelligent Agents embed AI into existing workflows and seamlessly scale your business. This unlocks opportunities not available to previous generations of AI or robotic automation technologies.
Discover more about the benefits of Intelligent Agents, their uses and how Oakland tailors AI solutions to you in our blog, Why We Recommend the Intelligent Agent Approach to AI https://weareoakland.com/blog/why-we-recommend-the-intelligent-agent-approach-to-ai/
Our Intelligent Agent Ecosystem
They’re powerful, but building an Intelligent Agent can take time. Time you probably don’t have.
That’s where we come in. Thanks to our cutting-edge research, we can deploy an ecosystem of highly
configurable Intelligent Agents, pre-trained and equipped to solve real-world problems. These are ready
to deploy in weeks, not months.
Our agents can be deployed as standalone workers or as multi-agent ‘teams’ that work together across
your business.
Meet the agents
We’ve developed three cohorts of intelligent agents, all carefully designed to solve real world business challenges. Agent cohorts are highly adaptable and rapidly extensible to similar use cases.
You can learn more about some of our agents and the challenges they solve on this page. But, we know, seeing is believing.
So book a demo to see one of our agents in action.
So much insight is locked away in unstructured, free text documentation that overwhelms users. Our Knowledge Analyst agents make knowledge accessible, proactively sharing insights and alerts that are easy for users to consume.
LucyLessons Analyst
Challenge
The same mistakes occur time and again in business because knowledge isn’t shared. Often, hours are spent gathering ‘lessons learned’ and best practice. But these documents then gather dust. The information is just too big and messy for anyone to use it. Important lessons are lost in the noise.
What our agent does
Lucy is a highly scalable, proactive librarian. She can conduct a focused search of a lesson library and return tailored user insights. Lucy can also proactively identify new lessons or projects, using her tooling to connect users to insights they were not aware of.
CameronComplaints Manager
Challenge
Complaint volumes, process complexity and messy documentation often overwhelm automated complaint systems or overstretched human teams. But, complaint handling is critical to avoid reputational and financial damage. Rapidly assessing and actioning complaints is crucial but highly challenging.
What our agent does
Cameron is an always-on complaint manager. Cameron scans and evaluates the entire complaints backlog for risk and non-compliance. Cameron highlights risks and uses his reasoning to identify resolutions and provide insights. Cameron can proactively identify and alert users to new or unresolved complaints in real-time.
Many businesses have invested in monitoring systems but now face an overwhelming volume of alerts and alarms. Imagine if you had a team of experts with near-infinite memory and an endless attention span constantly monitoring your business? That’s what our Process Guardian agents do. They can spot hidden issues, slash response times and free your teams to focus on solving.
SarahSupply Chain Monitor
Challenge
Even small quality issues can disrupt entire supply chains if not resolved quickly. Rapidly assessing the downstream impacts and alerting the right people is critical. But these maps often don’t exist and can’t be made quickly. So, communications can’t be directed and issues spiral out of control.
What our agent does
Her AI capabilities allow Sarah to read and analyse complex product specs, supply chain data and organisational charts. Sarah can monitor quality issues in real-time, rapidly assessing downstream impacts and proactively alerting impacted teams. Sarah can carry out human-like quality management tasks but also has a near-limitless memory and attention span.
AndyAlarm Manager
Challenge
Many businesses have invested heavily in alarms and telemetry to monitor their assets. But the volume and velocity of these alerts is so high that control teams are often overwhelmed. Triage and prioritisation cannot happen quickly enough. Scattered documentation and complex rules add further difficulty. The result is critical alerts are missed entirely or mis-handled.
What our agent does
Andy, an Alarm Manager agent, is trained on alert handling protocols. Andy is given tooling to enable analysis of alerting data in real-time. This allows Andy to act as a triage agent for asset control operatives. Andy interprets and filters incoming alerts, proactively making simple fixes and passing higher-priority cases on to control operatives. This frees up human operatives from having to try and consume an overwhelming volume of incoming alerts.
Data is so often meaningless without context. But applying context is time consuming. How many warning signs are lost in the data or missed because nobody spots their relevance? What if you could find the time to tailor reporting and insights to every user, every time? Our business partner agents are always-available, expert guides to the facts. They’ll take the insight to you.
CharlieContract Analyst
Challenge
Maintaining a clear sight of your contract base is key to customer and supplier management. But inconsistent contract formats, bespoke terms and fragmented filing are common. This makes finding and interpreting contracts at speed and scale nearly impossible for humans. Many companies operate ‘blind’ to their risks and detailed obligations.
What our agent does
A contract analyst (Charlie) can read and analyse a business’ entire contract base. This allows Charlie to create and document a structured map of contractual entitlements and obligations. This creates an overall picture of the contract portfolio. Charlie can also then monitor live commercial and operational data and advise on emerging risks and issues.
RonReport Curator
Challenge
Management reporting is often presented ‘cold’ without context or informative commentary. This means the audience either cannot see key messages or find their reports irrelevant. Engagement with reporting is low. Expert business partners or analysts can create much richer reports, but they are often unavailable or unaffordable.
What our agent does
A report curator (Ron) integrates with multiple data sources. Using its data visualisation tools, Ron prepares tailored reporting and commentary for key user groups. Continuously available, Ron can also answer follow-up questions via a natural language interface. Users can also request Ron to alert them to emerging trends or when certain events or triggers are met.
Meet our AI experts
The AI Opportunity Case Study
Network Rail: Revolutionising knowledge management through Generative AI
Working together with Network Rail, Oakland is leveraging Generative AI to increase the adoption of vital organisational learning from a vast, under-utilised ‘lessons learned’ library.
For more information on how Oakland used AI to help the UK’s largest rail authority, read our case study here.
FAQs
What cloud provider(s) and technologies do your Intelligent Agents work with?
We have built our solution to work across all major cloud providers (Microsoft Azure, AWS, GCP). We have the ability to leverage tooling from whichever provider you have. Our Intelligent Agents can also be built on a wide range of Large Language Models (LLMs) and AI services (e.g. Azure AI Search Service).
What can Intelligent Agents offer that is different to using Co-Pilot or Chat GPT?
Pre-built generative AI tools such as Co-Pilot and public-facing Chat GPT, Bard, and Gemini, provide limited capabilities, primarily based around back-and forth, Q&A-style interaction. These tools are underpinned by powerful LLMs, so they are useful for simpler use cases (e.g. summarisation) and can leverage existing infrastructure and environments. For example, Microsoft customers can natively access GenAI capabilities via desktop applications using Co Pilot. However, these tools do not provide specific, tailored agent capabilities for advanced problem-solving. For more advanced use cases (e.g. requiring contextual understanding, proactive action or complex reasoning) agentic capability is required.
I’ve heard generative AI is prone to ‘hallucination’ (inventing plausible but false answers). Do Intelligent Agents hallucinate?
Intelligent Agents harness the power of generative AI (via Large Language Models or (“LLMs”) but are designed to be enterprise-ready solutions. The design of our Intelligent Agents means that they feature multiple safeguards against hallucination. Carefully selected training data, task orientation and careful prompting are all used during agent deployment to improve the quality and relevance of agent outputs. Further, where relevant Intelligent Agents provide citations back to their source data to assure users that their responses are accurate.
How can I be confident that Intelligent Agents are producing the right outputs?
Agent interactions are fully visible and available to users. Using natural language chat interfaces, users can also query agent actions, request follow up information or ask for further detail or citations to support agent responses. The powerful generative AI technologies that underpin Intelligent Agents allow enterprises to rapidly prompt and correct responses if necessary to ensure quality outputs.
Do all my AI powered solutions need to be Intelligent Agents?
Intelligent Agent capabilities, toolsets and integrations are configurable to business needs. Not all AI use cases will require highly sophisticated agents to solve them. There might also be occasions where agentic capability is not required (e.g. a basic chat interface will suffice). Lower complexity or non-agentic solutions can operate alongside Intelligent Agents.
If I use Intelligent Agents, does my business’s data belong to the providers of the underlying AI technologies (e.g. Open AI, Chat GPT, Microsoft)?
No. It is possible to create private instances of commercial or open source generative AI models and services to underpin your Intelligent Agents. This is our recommended approach, and it means that your data is secured and remains private to your organisation.
How do data quality issues impact Intelligent Agent performance?
Intelligent Agent performance will be impacted by the quality of available training data, like any other solution powered by generative AI. However, the flexibility and reasoning powers of Intelligent Agents can be leveraged to mitigate data quality issues and overcome limitations in training data. For example, Intelligent Agents can be trained to weigh up multiple data sources and provide a balanced opinion based on all the available data