Case Studies

Case Study: AI Optimised Presales Team Efficiency

Fidra Analytics constructs an AI-powered RAG system to increase Presales efficiency of tech distribution giant, Westcoast.

Problem Statement

A leading Tech and IT distributor, Westcoast, had a Presales team facing significant efficiency issues.
An estimated 80% of staff time was devoted to answering high volumes of repetitive, yet complex, queries.

With company growth at Westcoast came more enquires to an already busy team.

An AI solution could streamline these operations, increase departmental capacity, and better use company time.

Our Approach

Using the principles of Agile Software Development, Fidra Analytics began two week sprint iterations to investigate the needs of the customer and collaborate closely on development.

Westcoast engaged in Sprint Planning with Fidra Analytics so that each iteration was focussed on valuable output. Each iteration ended in a Sprint Demo, where Fidra Analytics showcased everything achieved in those two weeks.

Westcoast’s constant involvement and inspection here was vital. Customer feedback ensures the end solution is highly specialised to suit our client’s individual needs, positioning business value as a core driver.

Following these initial collaborations, it was clear that the Presales team would most benefit from an AI-powered RAG system to minimise information search times and allow them to focus energy on other tasks.

Technical Overview

Development

After completing early exploration, the Fidra Analytics team developed a Minimum Viable Product (MVP) in a number of weeks. This was critical in order to prove the capabilities of the solution and gather wider Westcoast feedback on further development.

How does a Retrieval Augmented Generation system work?

Step 1 – information retrieval
The system scans the knowledge sources and collects the
relevant information.

Step 2- prompt generation
The system combines the original employee question, the relevant information found in Step 1, and the ‘company context’.
Company context is information about Westcoast (e.g. the system should generate responses that suit a sales team).
These three form the ‘prompt’.

Step 3- the Large Language Model
The prompt is sent to an LLM, which uses Natural Language Processing to generate helpful, clear, and syntactically correct responses.

System Integration

Privacy and security was paramount here.

We used Westcoast’s existing user authentication system to control access to the AI tool.
We contained all data to one geographic location- mitigating security and GDPR risks.
Third parties do not save messages and cannot use them to train other LLMs – giving Westcoast full control over their data.

Monitoring and Optimisation

With a concrete MVP complete, Fidra Analytics were able to focus on speed optimisation and response improvements. A user friendly front end is also in the pipeline.

Value

Customer Benefit

Westcoast saw immediate benefit from this project.

Westcoast’s Presales team receive complex enquiries: for example, an organisation may be looking to upgrade their company laptops, but only use certain vendor products, like HPE. Previously, the Westcoast team would have had to manually search the manufacturer PDFs to find the compatible devices – but Fidra Analytics’ AI system now does this automatically. The new RAG system scans the knowledge sources and provides the Westcoast employee with a quick, tailored list compiling all the laptops from that vendor that suit the client’s needs.

Customer Feedback

“The Fidra Analytics team impressed us with their knowledge, removing the hype from the conversation and instead showing practical implementation to bring capabilities to life.”
Karl Harris, CIO Westcoast

“As a Presales Architect, I can now dramatically reduce the amount of time it takes me to produce customer quotes. I can now spend time focussing on fine tuning the solutions we prepare for our customer. The biggest impact is the reduction in support needed for our newer members of the team.”
Presales Architect, Westcoast

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