Actis and Model ML: A Blueprint for Private Equity Innovation

Actis and Model ML: A Blueprint for Private Equity Innovation

Overview

1. Location: London

2. Team Size: 350

3. Partnered Since: Dec 2024

4. Primary Use Cases: Portfolio & fund reporting, Portfolio management & acceleration, Due diligence, DDQs, LP & product communications, Note taking

Key Challenges

• Manual Portfolio & Fund Reporting: Actis faced challenges in preparing detailed portfolio and fund reports. These tasks required significant manual effort to gather, analyse, and present data from multiple sources. The process was time-intensive and prone to inconsistencies, limiting the ability to deliver timely and accurate insights to stakeholders.

• Manual Portfolio Management & Acceleration: Managing and accelerating portfolio companies required Actis to manually track performance metrics, market trends, and operational updates. This process involved gathering data from various sources, which was labour-intensive and slowed down decision-making.

• Manual Due Diligence (DD) and DDQs: Conducting due diligence and responding to Due Diligence Questionnaires (DDQs) required Actis to manually compile and verify large volumes of data. This process was resource-intensive and often delayed deal timelines.

• Manual Drafting of LP and Product Communications: Actis needed to draft detailed communications for Limited Partners (LPs) and product updates. This involved manually gathering data such as fund performance, portfolio updates, market insights, and strategic initiatives from multiple sources. The process was time-consuming and required significant effort to ensure accuracy and consistency across communications.

• Manual Note-Taking on Calls: Notes from calls were either handwritten or manually typed, leading to inconsistencies, occasional inaccuracies, and less detailed records. Sharing these notes among team members was also a manual process, further complicating collaboration and reducing efficiency.

How Model ML Helps Today

• Streamlined Portfolio & Fund Reporting: Model ML automates the process of gathering and analysing data for portfolio and fund reporting. By extracting and organising data from multiple sources, the tool enables Actis to generate accurate and timely reports with minimal manual effort.

• Enhanced Portfolio Management & Acceleration: Model ML helps Actis track performance metrics, market trends, and operational updates in real time. This allows the team to make faster, data-driven decisions to accelerate portfolio company growth.

• Efficient Due Diligence & DDQs: Model ML simplifies the due diligence process by automating data extraction and organisation. The tool enables Actis to respond to DDQs quickly and accurately, reducing the time and effort required for these tasks.

• Streamlined Drafting of LP and Product Communications: Model ML enables Actis to automate the drafting of LP and product communications by extracting and organizing relevant data into pre-defined templates. This ensures that communications are accurate, consistent, and delivered in a timely manner, significantly reducing the manual effort required.

• Effortless Data Extraction: Model ML simplifies the extraction of information from PDFs and Word documents into grid or Excel formats. This makes data easier and quicker to analyse, significantly reducing the time spent on manual data entry.

• Automated Note-Taking: The Model ML bot joins meetings, ensuring accurate and consistent notes are captured. These notes are easily accessible to all team members, improving collaboration and reducing the risk of errors or omissions.

• Portfolio Data Integration: Actis has been working closely with the portfolio data integration team to integrate Model ML into their portfolio companies. This integration will allow portfolio companies to leverage Model ML’s capabilities for their own operations, enhancing efficiency and enabling better data-driven decision-making at the portfolio level.

• Second Layer of Enterprise Software at the GP Level: At the General Partner (GP) level, Actis will be using Model ML as a second layer of enterprise software. This ensures that Model ML is embedded into their workflows, providing a seamless and scalable solution for managing data, reporting, and collaboration across the firm.

• Participation in AI Committee Meetings: Model ML actively participates in Actis’s AI committee meetings, providing insights into industry trends and best practices. By sharing what is being observed across the industry and advising accordingly, Model ML ensures that Actis remains informed and aligned with the latest advancements in AI. This collaboration keeps Actis at the forefront of innovation while maintaining transparency and alignment with their strategic goals.

Impact & Outcomes

• Higher Granularity and Faster Research: Research tasks, including due diligence and drafting LP communications, are now conducted with a higher degree of detail and completed much faster, enabling Actis to deliver more comprehensive insights in less time.

• Significant Time Savings: Manual, time-intensive tasks such as portfolio reporting, DDQs, and note-taking have been significantly reduced, freeing up resources for more strategic, value-add activities.

• Customisation and Flexibility: The ability to create prompts and templates from scratch allows Model ML to be fully tailored to Actis’s specific needs. This ensures that the tool delivers information in the preferred format for each use case, enhancing efficiency and usability.

• Improved Collaboration: Automated note-taking and centralized data sharing have improved collaboration across teams, ensuring everyone has access to accurate and consistent information.

• Portfolio-Level Efficiency: By integrating Model ML into portfolio companies, Actis will enable its investments to benefit from the same efficiencies, improving operational performance and decision-making across the portfolio.

• Scalable GP-Level Solution: Model ML’s role as a second layer of enterprise software at the GP level will provide Actis with a scalable and integrated solution for managing workflows, reporting, and data analysis across the firm.

• Industry Alignment: Through AI Committee Participation By participating in Actis’s AI committee meetings, Model ML ensures that Actis stays ahead of industry trends and innovations. This collaboration provides Actis with valuable insights and strategic advice, helping them remain competitive and informed in a rapidly evolving landscape.

How Model ML Will Help In the Future

• Enhanced Process Automation: With advanced prompt creation, Model ML will continue to streamline Actis’s processes and automate more daily tasks, further reducing time spent on manual work.

• Increased Strategic Focus: By automating routine tasks, Actis will be able to provide more strategic, value-add advice to clients while expanding capacity without compromising service quality.

• Faster Deal Execution: Automating the creation of marketing documents, such as Information Memorandums and teasers, will reduce preparation time, enabling Actis to execute deals faster.

• Deeper Portfolio Integration: As Model ML continues to be integrated into Actis’s portfolio companies, the tool will enable even greater operational efficiencies and data-driven insights at the portfolio level, enhancing the value creation process.

• Continued AI Collaboration: Model ML’s ongoing participation in Actis’s AI committee meetings will ensure that Actis remains aligned with the latest advancements in AI. This collaboration will help Actis identify new opportunities for automation and innovation, further enhancing their competitive edge.