Performance Improvement for Private Markets

Unless you’ve been under a rock you’ll have witnessed that 2023 was a pivotal year in AI, exemplified by global fascination with Large Language Models (LLMs), which showcased their capabilities in tasks such as translation and coding through simple prompts. This interest initially placed LLMs at the forefront of AI application development, igniting curiosity about their fast-evolving capabilities.

If you have a spare 20 minutes it's worth watching Jonge's big idea for 2024 exploring the opportunity for programmable medicines to reduce the cost of drug development and clinical trials. At its core it argues that standardised, codified approaches that drive repeatability are critical for future performance.

By harnessing the power of data, analytics and AI, asset managers and their portfolio companies will unlock new opportunities and differentiate themselves in a competitive market.

Private equity has recently entered a new phase in its evolution, comprised firstly of a step-change in the industry's scale and maturity, with secondly an in-tandem shift in the economic backdrop. Long-established firms have evolved into multi-strategy asset managers or sector / geographic specialists, whilst new entrants, of which there are many, in combination with heightened market transparency and the efficiencies of a dedicated ecosystem of service providers, have increased the level of competition for assets.

How to use Machine Learning — in the right place and at the right time.

DragonFly is a unique set of technology and tools that powers our investment strategy at WovenLight, from sourcing and diligence through to value creation under our ownership. Here, we take a look at one of the key challenges in developing DragonFly, building repeatable data analytics and machine learning solutions.

Taking inspiration from nature, WovenLight has built unique technology, DragonFly, to underpin a ‘PE 2.0’ approach throughout the investment life-cycle.