Enable your team to query portfolio metrics, benchmarks, and attribution data across markets using natural language. We translate questions into structured queries, generate charts, and summarize results, making it easier to act on performance across multiple asset classes.

With our Ontology driven table analyzer (OntoTab) we track performance across private and public investments as new data becomes available. We synthesize quarterly letters, extract financials and flag deviations in exposures or assumptions, so your team gets a running view of every manager and mandate.

Produce data-driven co-investment memos by ingesting portfolio metrics, investment book of records, and market intelligence, delivering decision-ready drafts that mirror your firm’s return targets and governance workflows.

Automatically craft re-underwriting memos by mining internal risk models, historical performance, and external datasets, refreshing thesis alignment and portfolio exposure analysis for evolving market, covenant, and liquidity conditions.

We encode your investment logic, assumptions, and decisions as structured data using proprietary ontologies. These include company segmentation, alternative performance, and company fundamentals, so knowledge compounds, decisions stay traceable, and teams reason from the same foundation.

Support active public equity decisions with AI-generated memos that reflect your internal framework. We back-test ideas, encode assumptions, analyze factor exposures, and log post-mortems, creating a consistent audit trail from conviction to outcome.

Our models are trained using a fund’s historical memos, investment committee materials, emails, and research notes, then fine-tuned for their terminology, assumptions, and template structure. We support reasoning across new investments, portfolio monitoring, or re-underwriting decisions.

Large funds have privacy and data access rules within the fund. For example, an impending funding or company purchase artifacts is only visible to deal team and decision maker.

Flag early signals and run predictive performance analyses across funds and companies. We blend qualitative tone analysis with quantitative trend modeling to identify emerging risks, performance drift, or anomalies, helping teams course-correct before issues escalate.