During fundraising, IR teams spend hundreds of hours on manual DDQ data entry and tagging due to rigid, generic software.
Norric partnered with a $12B private equity firm to incubate an AI-native DDQ platform in 5 weeks leveraging our core engine.
Background
During fundraising, asset managers receive tens of thousands of due diligence questions (DDQs) from LPs. Yet approximately 75% of DDQ responses are contextually repetitive, with the same underlying information resurfacing across investors, funds, and fundraising cycles. Despite this, the knowledge remains fragmented across prior submissions, individual inboxes, and unstructured documents.
As a result, Investor Relations (IR) teams spend up to 90% of their time manually logging and maintaining Q&A entries within incumbent DDQ software to preserve a centralized knowledge base. This process is labor-intensive, difficult to scale, and prone to inconsistencies.
At the same time, while large language models (LLMs) offer the promise of automating the analysis of unstructured documents and managing these repositories more efficiently, their outputs often lack the accuracy, consistency, and reliability required for high-stakes fundraising workflows.
Our Solution
Norric's core engine ingests and processes complex financial documents while providing a centralized workflow platform that streamlines collaboration across the fundraising lifecycle.
In close partnership with the firm, our forward-deployed engineers developed a platform tailored to asset managers' workflows, transforming a firm-specific solution into a comprehensive AI suite designed to address broader industry needs—all within five weeks.
1. Automated Repository Management
By automatically extracting and structuring questions and responses from historical documents, Norric eliminates manual data entry and maintains a centralized repository of institutional knowledge. Human reviewers remain integral to the process, validating and refining all AI-generated entries before they are incorporated into the system.
Furthermore, our agents detect inconsistencies across historical responses, flag questions that require periodic updates as underlying information evolves, and automatically enrich each entry with intelligent tags based on factors such as fund affiliation, geography, legal considerations, and other semantic nuances.
2. Get to a First Draft 90% Faster
When firms upload incoming DDQs, Norric identifies questions that have been answered previously and surfaces relevant responses with complete traceability to the underlying source materials. For every suggested answer, users can view supporting references, AI reasoning, confidence scores, and the exact locations from which the information was derived.
3. End-to-End Workspace
Users can draft, review, and finalize responses within a collaborative workspace equipped with role-based access controls, comprehensive audit trails, and commenting capabilities. Once a questionnaire has been completed, firms can export responses directly into the original format in which the DDQ was received, eliminating the need for manual reformatting.
The Results
Results
Norric eliminated 90% of manual DDQ data entry and repository maintenance, saving Investor Relations teams 1,000+ hours annually and generating over $500K in annual productivity and operational savings. By enabling firms to complete significantly more DDQs without increasing headcount, the platform also unlocked millions of dollars in opportunity value that would have otherwise been lost to operational constraints.