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Asset Owners & Allocators

Asset owners and Allocators, such as institutional investors, wealth management firms, and consultants, can streamline manager diligence, onboarding, annual reviews, and reporting with CENTRL’s AI platform

AI Research Assistant
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CENTRL’s AI platform is used by asset owners and allocators to automate their manager research and diligence process, enabling better decision-making and freeing up time for higher-value tasks. Diligence and research teams using the CENTRL platform for investment and operational due diligence, or sub-advisor and compliance oversight of managers and service providers, are experiencing significant efficiency gains and deeper insights.

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Alternative Investment Firm Achieves 80% Efficiency Gain with CENTRL’s Agentic AI Platform, DD360

Nov 18, 2025

Alternative Investment Firm Achieves 80% Efficiency Gain with CENTRL’s Agentic AI Platform, DD360

A US-Based Investment Firm achieved an 80% increase in efficiency across underwriting and reporting functions, transforming previously manual workflows into automated, streamlined processes. Turnaround times were reduced from days to hours, enabling faster decision-making and improved responsiveness to stakeholders.

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Rethinking Communication in the Age of AI

Nov 18, 2025

Investor expectations for speed, accuracy, and transparency are reshaping how alternative investment firms communicate and operate. AI is helping managers meet these demands by automating repetitive tasks like due diligence responses, enabling faster, more consistent, and data-driven communication. Success, however, will depend on domain-trained AI systems, disciplined data management, and strong human oversight to ensure accuracy, compliance, and trust.

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Will Due Diligence Questionnaires Survive the AI Revolution?

Oct 14, 2025

Will Due Diligence Questionnaires Survive the AI Revolution?

The world of investment management is changing faster than ever. Investor expectations are rising, regulations are tightening, and asset managers are diversifying across strategies, geographies, and vehicles. In this evolving landscape, one question looms large: will traditional DDQs survive the AI revolution?

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