In an increasingly competitive business environment, operational efficiency is key to staying ahead of competitors. Many companies providing financial services face significant pressure to improve operational efficiency while managing rising workloads and resource constraints in order to remain relevant. To meet these demands, our client, an upcoming SaaS provider in the FinTech industry, set out to develop an AI-driven co-pilot to assist professionals in optimising their day-to-day operations, automating essential tasks, and enhancing decision-making processes. This solution, intended to support key financial activities, aimed to reduce manual efforts, minimise errors, and improve the overall efficiency of service delivery.
Recognising the Need for More Than Just Development
The company had successfully developed an AI co-pilot MVP that showed great potential in enhancing operational efficiency for financial professionals. However, as the project progressed, the company recognised the need to further refine and optimise the system to meet the demands of scaling it for a broader market. The challenge was to ensure that the co-pilot could handle increasingly complex tasks efficiently while keeping operational costs manageable. Additionally, the company sought to improve processing times and enhance the overall performance of the system to provide an even smoother experience for its users.
Rather than focusing solely on development, the company needed an R&D partner who could bring in specialised expertise to help refine the underlying technology, ensuring that the final product would be not only market-ready but also capable of performing at a high level in a competitive environment. The company teamed up with Faktion as a dedicated research and development partner, tasked with refining the solution without disrupting the core development, ensuring a more effective and scalable product at launch.
Turning Insights into Impact: How Our Research Significantly Enhanced the AI Copilot
Faktion was brought in as the R&D partner to help bridge the gap between the prototype and a fully scalable solution that uses state-of-the-art techniques to bring the copilot’s performance to a new level. Leveraging our expertise, we worked on refining the architecture of the co-pilot, improving model efficiency and minimising processing costs. By conducting targeted research and running experiments in areas such as model optimisation, chunking strategies, retrieval techniques, and enhanced processing algorithms, we were able to provide valuable insights that significantly boosted the performance of the co-pilot.
Our collaboration was designed to allow the in-house development team to focus on product creation, while we concentrated on research and technological improvements. This separation of responsibilities helped ensure that the development process remained efficient, while the overall performance of the co-pilot improving significantly as the development team could benefit from Faktion’s research and recommendations.
Collaborative Experimentation Without Disrupting the Core Development Process
Our approach was both iterative and collaborative. We initiated a series of targeted experiments, exploring various AI techniques such as fine-tuning models, optimising retrieval mechanisms, and employing advanced chunking strategies. These experiments were conducted in a separate sandbox environment, ensuring that the core product development remained unaffected.
Throughout the process, we applied rigorous testing and evaluation methods, comparing different AI models and optimisation strategies to determine the best possible configurations for the co-pilot. We worked closely with the company’s internal teams, providing ongoing insights and recommendations that informed the direction of the development process, allowing for continuous improvement over time, while maintaining project timelines.
One of the key benefits of our partnership was the ability to conduct deep technical research without interrupting the development workflow. This allowed the client to stay on track with their project timelines while still benefiting from significant performance enhancements that would have been difficult to achieve otherwise.
A Scalable and Market-ready AI Solution
By partnering with Faktion as their dedicated R&D partner, the company was able to enhance the performance and scalability of their AI co-pilot solution. Our research and expertise allowed the client to overcome key technical challenges, optimising their solution for faster processing, reduced operational costs, and improved scalability. The separation of research and development ensured that their product team could focus on delivering a high-quality solution to market, while our contributions helped create a more efficient and effective co-pilot.
This collaboration not only immediately improved the performance of the product but also positioned the company for long-term success in a competitive market. By leveraging the right expertise at the right time, the company was able to enhance its AI-driven solution, offering better service to its clients and securing its place as a leader in the industry.
