The LP Playbook: 3 key data & tech themes from the LPGP conference
It’s undeniable—the world of private markets has undergone a fundamental change. As LPs increase allocations across diverse strategies, from private equity to credit and infrastructure, the problem of data chaos has become a core business bottleneck. The recent LPGP Data & Technology Conference confirmed that the era of manual data management is now behind us.
Here are the three biggest themes LPs need to prioritise to gain the timely transparency and control required to manage risk and drive investment decisions:
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Unstructured data is hampering the investment process
For LPs, the sheer volume and varied nature of documents—think hundreds of PDFs, disparate spreadsheets, and portal dumps from dozens of GPs—create an operational and analytical black hole. Data is fragmented and non-standardised, requiring hours of costly, error-prone manual labor just to get into a spreadsheet.
The new approach: Automation and normalisation
To overcome this, LPs need to embrace technology that acts as a central data refinery.
- Solve ingestion first: The first step is to utilise advanced technologies, such as AI, Machine Learning, and Natural Language Processing (NLP), to automate data capture. This technology must automatically ingest, read, and extract critical financial and operational metrics from every document, turning unstructured reports into structured data. This automation eliminates the manual effort and is a mandatory prerequisite for any advanced analysis.
- Establish a single source of truth (SSOT): Since every GP reports differently, the extracted data must be instantly normalised and standardised against the LP’s own established data model. This normalisation creates a true, clean SSOT, finally allowing for rapid portfolio aggregation, cross-fund comparisons, and accurate look-through analysis.
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Responsible AI: Your analytical assistant, not your analyst replacement
The conference made it clear: AI isn’t science fiction, but rather a powerful tool for creating speed and efficiency. However, the focus must be on responsible AI (RAI), emphasising that any system is only as good as its foundation. AI’s current role is to augment and accelerate the work of human investment professionals, not replace them.
The new approach: Trust and transparency
LPs must ensure their technology accelerates decisions while maintaining accountability.
- Focus on efficiency and scale: The most immediate wins for LPs are using these intelligent platforms to provide real-time data access. Automating ingestion and standardisation frees investment teams from data wrangling and allows them to focus on strategy, manager selection, and decision-making.
- Auditability is key: For any data processed by an intelligent system, LPs need a complete audit trail and click-to-audit functionality. Auditability is non-negotiable. Every number must be traceable back to the source document, providing the transparency required for governance, compliance, and fiduciary duty.
- The “human-in-the-loop”: The system must incorporate human review for any data the AI flags as potentially anomalous. This blend of automated speed and human domain expertise ensures that decisions are based on the highest-quality, verifiable data, thereby mitigating the risks of error or ‘hallucination.’
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Data governance: Taking control in an unstandardised world
The most fundamental challenge is the industry’s lack of a common data language. While the market debates standards, LPs cannot afford to wait. They must implement a robust internal data governance structure that can handle the current reality of non-standardised GP reporting.
The new approach: Agility and control
The technology LPs use must be built for flexibility and seamless integration.
- Own your data model: Waiting for a universal standard is not an option. A modern data solution provides the framework for the LP to define its own unique data model and taxonomy. The platform then consistently maps all incoming GP data to this internal standard, giving the LP total control over how they track metrics and evaluate performance.
- Enable integration: Investment data should not sit in a silo. The chosen solution must be built for modularity and two-way integration. It should act as the central data refinery, cleaning and validating data before seamlessly pushing it directly into the LP’s downstream systems—whether that’s an accounting platform, performance management system, or a Business Intelligence (BI) tool.
- Transparency for the board: High-quality, standardised data is critical for communication. It empowers LPs to create tailored, consistent, and immediate reports for their stakeholders, enhancing trust and fulfilling the increasing demand for detailed portfolio transparency.
The bottom line for LPs: To thrive in the evolving private markets, you must treat the challenge of unstructured data as a technology problem to be solved by automation and intelligence, allowing your team to move from data gatherers to strategic analysts.
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About Canoe Intelligence
Canoe Intelligence (“Canoe”) is the platform for smarter alts management. We redefine alternative investment intelligence with AI-driven software that directly addresses the core challenges of private markets. Our technology empowers institutions, LPs, and wealth managers to future-proof their alts infrastructure, modernizing systems and providing a scalable foundation for long-term growth and compliance. By automating manual data processing with AI-native precision, Canoe helps clients reduce operational costs and risks, significantly lowering overhead and mitigating errors. Ultimately, our timely, accurate, and comprehensive data enables investment teams to drive superior investment outcomes through deeper insights and more profitable allocation strategies. With Canoe, it’s all about making Alts, smarter. Learn more at www.canoeintelligence.com.
MEDIA CONTACT:
Betsy Miller Daitch
Canoe Intelligence
+1 443-690-6200
bdaitch@canoeintelligence.com
