Harnessing AI to Drive Efficiency and Business Value at Littlefish

With a focus on harnessing the power of AI to boost operational efficiency and deliver measurable business benefits from service desk automation to improving document workflows, Littlefish is exploring how large language models (LLMs) like Copilot, Azure OpenAI, and ChatGPT can transform traditional processes. Below we explore some of the use cases.

Service Desk

One of the most advanced and established uses of AI at Littlefish is within the service desk. When support agents engage in live chat sessions with users, the post-chat wrap-up typically involves manually summarising the conversation and updating the corresponding support ticket. This administrative task, while necessary, is time-consuming and repetitive pulling service agents away from value-add customer interactions.

To address this, Littlefish developed an AI-driven process that intercepts the chat transcript immediately after the session concludes. It uses a large language model to summarise the conversation, generating all the necessary ticket artefacts including summaries, descriptions, and resolution notes, all while ensuring the data remains anonymised. Reducing the administrative workload of service teams has allowed them to regain multiple minutes per chat, which they can redirect towards delivering higher quality interactions, as well as ensuring consistency and completeness in documentation. This means increased agent productivity and faster ticket resolution times, which directly enhance user satisfaction and free up resources for higher-value tasks.

Ticket Quality

Delivering high-quality data content within incident tickets is key for a managed service provider, from both a user experience perspective and also in delivering a proactive problem management service, as this relies on high-quality data for trending.

Historically, team leaders have had to spend a significant portion of their time conducting quality analysis on tickets to ensure that the work being done at the service desk meets the desired standards. By providing these standards to AI and running tickets through AI, managers are able to quality check not just a small sample of tickets, but tens of thousands a month. This also enables centralised reporting of quality data, allowing the service desk leadership team to identify areas of concern early and address them. This not only saves some time for team leaders, but also delivers a robust process that has far wider coverage of tickets than could ever be accomplished by a human alone.

Project Proposals

Beyond the service desk, Littlefish is exploring copilots in project management, particularly to support the creation of project proposals. While this application is still in proof of concept with a limited number of staff, the goal is to be able to automate the creation of the majority of proposals, enabling architects to top and tail these. Such drafts would support an accelerated response time for client proposals and enhanced proposal quality by having a set of technical standards that the AI must write designs against. The expectation is that within six months, by using inputs like timesheet data and satisfaction scores, the proposals can be enhanced to take account of previously delivered projects and their outcomes to ensure continual improvement in the quality of the proposals. This will significantly reduce the time and effort required to create project proposals, allowing the team to focus on more strategic project tasks.

HR Copilot

A HR Copilot will be soon released to deal with any HR queries. The copilot will have access to all HR policy documents so users can get answers to questions about things like annual leave, overtime, and maternity leave quickly and easily. This is a fast and convenient way for employees to find the information they need, and it also significantly reduces the workload of HR teams.

If you would like to learn more about what AI can achieve for your business, get in touch with a member of our team today.