AIP accelerates the initial phases of deal sourcing by enabling analyst and research teams in Private Equity to perform AI-driven analyses and manage investment prospects at scale. AIP allows for customization to meet specific organizational needs while promoting a unified methodology. This ensures that, despite the inherent flexibility, there is a standardized approach to the process across the entire organization. This standardization addresses the common concern of varying methodologies among analysts, establishing a cohesive and efficient workflow that enhances collaboration and decision-making across teams.
By integrating advanced multimodal language models and other system integrations, AIP’s Ontology is enriched with insights from PDFs and various document types, which are then combined with data from other structured sources, both internal and third-party. This process is designed to facilitate the processes shown on right side.
Screening
AIP allows users to automate the screening of inbound pitch decks using user configured screening criteria. For example, “the company’s revenue must be above a certain threshold. Their growth over last 5 years must be at least 10%. They must be based out of certain countries.” Organizations can further configure the rules to automate conditions to move an opportunity through the review process. While the pipeline is efficiently managed by these automated systems, it retains the flexibility for users to conduct thorough human reviews and make adjustments as needed.
Due Diligence
AIP simplifies the completion of Due Diligence Questionnaires by offering suggested answers for preset questions (for example, what is the company vision and how is it different from other companies in the space, what are the main risks and ways to mitigate them, etc.). A set of bespoke questions are also proposed by the Large Language Model based on the specific pitch deck being analysed and answers that were generated for preset questions. Users can easily configure these responses, export any unanswered questions, and upload follow-up information for swift questionnaire fulfillment.
Reports
Using the AIP Ontology users can quickly generate templatized reports for Investment Committees or other purposes. The Ontology provides a structured foundation used by the Large Language Model to generate predefined elements of the report, to mitigate the risk of hallucinations. These reports are automatically generated, and are reviewed and manually edited by users before being exported or shared via email.
AIP Portfolio Manager for Private Equity offers a sophisticated integration framework that consolidates disparate data sources into a cohesive Ontology, tailored for the private equity sector. This includes CRMs, financial databases like Preqin, as well as third-party and open-source data.
By transforming inconsistent data formats into a standardized private equity Ontology, AIP ensures that firms can navigate their individual investment landscape with precision and ease. The platform’s intuitive front-end is customizable to meet the unique business needs of each firm, enabling the creation of highly personalized output artifacts. For example, tear sheets, analyses for driving internal portfolio rebalancing, reports to share with Limited Partners, and more.
AI Data Management & Integration
Leverage AIP’s ability to rapidly integrate and normalize data from a multitude of sources, ensuring high data quality with built-in validation and governance controls. Gen AI data extraction techniques are employed to minimize inconsistencies and validate information.
Comprehensive Investment Ontology
Craft a dynamic and adaptable data framework for robust portfolio monitoring, analytics, and reporting, accessible both within the platform and externally, such as through Excel or other systems. Fine-tuned permission settings facilitate effective cross-functional data collaboration.
Tailored AI-Driven Applications
Deploy customizable workflows ranging from automated proactive reporting to sophisticated disclosure management and memo creation. These applications are designed for one-click deployment and can be easily tailored to general partners' (GPs) specific needs or directly provided to limited partners (LPs) through bespoke interfaces.
Versatile Modelling & Analytics
Empower users with low-code tools to develop new metrics, ratios, forecasts, or valuation models. The platform’s flexibility ensures that users can innovate and adapt analytical models to evolving business requirements.
AIP streamlines response generation and sign-off for Inbound Operational Due Diligence requests from Limited Partners. It enables users to swiftly search previous Due Diligence Questionnaire (DDQ) inquiries and the firm’s policy documents to craft comprehensive answers. Additionally, AIP recommends responses that have already received legal and compliance approval. The integrated process state machine orchestrates a detailed, multi-stage approval workflow, guaranteeing that responses receive the necessary human-in-the-loop confirmation before being finalized.
Advanced O-RAG Implementation
Advanced Ontology Retrieval-Augmented Generation (O-RAG) Implementation: Searches through previous Due Diligence Questionnaire (DDQ) requests and the complete collection of policy documents to generate the most current responses that are legally and compliance-approved for inbound inquiries.
Fully Customizable Request Categorization Framework
Intelligently designates approvers for individual questions based on their expertise, streamlining the approval process.
Customizable and Automated Alerting Mechanism
Minimizes email exchanges between request submitters and approvers, ensuring timely responses to inquiries.
Full Auditability
Provides full insight into the Language Model's (LLM) chain of thought, tool use, response generation, request approvals, and any changes over time to legally approved responses.