What used to take weeks of manual effort—digging through PDFs, transcribing data into spreadsheets, and running complex Excel models—can now be
completed in a matter of hours with 99% accuracy. This is not a future promise; it's the reality today for clients of 73 Strings.
Alternative asset managers, overseeing over $13.1 trillion in global AUM, have long faced the burden of fragmented data, time-consuming valuations, and static quarterly reporting cycles.
Traditional AI tools helped alleviate some of these pain points, but they were largely reactive—focused on prediction, not proactive execution.
73Strings created a new paradigm in AI systems that do not just analyze, but act— autonomously executing tasks, learning from feedback, and continuously optimizing performance under human oversight.
With an AI-first approach and deep domain expertise, 73 Strings is redefining financial automation—not by replacing analysts, but by empowering them.
In this article, we explore how 73 Strings has operationalized AI to transform alternative asset management, the technology that powers this transformation,
and what the future holds for institutional investors, private equity firms, and fund administrators.
The Traditional Bottleneck: Manual Valuations
Historically, valuation has been a labor-intensive process. Analysts gather fragmented data from emails, PDFs, and spreadsheets, input it manually into Excel models, and apply industry heuristics to arrive at fair values. This workflow is prone to human error, lacks scalability, and consumes valuable time that could be better spent on strategic analysis.
AI in Action: 73 Strings' Augmented Approach
73 Strings has reimagined this process by AI principles directly into its core product suite:
- 73 Extract autonomously parses unstructured data from financial documents whether PDFs, scanned reports, or emails—turning them into structured, validated data points ready for analysis.
- 73 Value builds valuation models using multiple methodologies, scenario analysis, and comparables. It suggests, executes, and explains its logic, all while enabling human override when needed.
- 73 Monitor offers ongoing oversight of portfolio company performance, risk triggers, and covenant compliance, flagging deviations in real-time.
These products and the AI continuously evolve through human feedback bugs raised etc. continuously improving the system.
Augmented, Not Replaced: The Human-in-the-Loop Philosophy
Unlike black-box AI models, 73 Strings is built with a “human-in-the-loopˮ architecture. The system recommends, but the analyst decides. It automates grunt work but elevates human judgment. This is not just efficient—itʼs compliant, auditable, and explainable, making it ideally suited for the regulated world of finance.
In short, AI at 73 Strings is not about replacing valuation professionals. It's about amplifying their expertise with intelligent tools that think, act, and learn—just like a trusted team member would.
The Technology Behind the Transformation: 73 Strings' AI Stack
What powers these systems at 73 Strings is not just clever automation—it's a deeply integrated, purpose-built AI stack designed for the unique challenges of alternative asset management. From interpreting unstructured documents to continuously refining valuation models, the platform combines best-in-class technologies across AI, Technology and secure cloud infrastructure.
Natural Language Processing (NLP)/ Vision Models for Financial Documents
At the foundation is advanced NLP and vision models tailored specifically for the financial domain. Unlike generic AI models, 73 Strings' NLP understands the nuances of investor reports, capital calls, board decks, and loan covenants. It can:
- Extract structured data from PDFs, emails, and scanned documents using OCR and semantic parsing.
- Convert visual information that appear in Charts in different types of financial documents into tabular structures using various types of vision models.
- Interpret context by identifying company-specific terms, industry jargon, and domain-specific metrics.
- Disambiguate entities like "EBITDA" or “leverageˮ in varied contexts and formats, ensuring accuracy across jurisdictions.
This allows analysts to skip the tedious and error-prone data entry process, accelerating workflows from days to hours.
Machine Learning for Valuation Accuracy and Intelligence
Valuation is both an art and a science—and 73 Strings enhances both through machine learning:
- Comparable company identification is handled via collaborative filtering techniques—akin to how streaming platforms recommend similar content. The system learns from past valuations, industry trends, and firm-specific benchmarks.
- Predictive modeling uncovers hidden patterns in financials, flagging anomalies or suggesting changes based on historical performance and macroeconomic variables.
- Feedback loops enable the system to learn from every user correction, continuously refining its accuracy over time.
The result? Reliable, explainable valuations that improve with scale and usage.
Cloud-Native, Secure, and Scalable Architecture
Built as a modern SaaS platform, 73 Strings is enterprise-ready from day one:
- SOC 1 & SOC 2 compliant to meet the strictest audit and data handling requirements.
- API-first architecture enables seamless integration with CRM systems, fund administration platforms, and portfolio management tools.
- Modular design ensures scalability, whether a client manages 10 portfolio companies or 10,000.
Security, reliability, and extensibility are not afterthoughts—they're core design principles enabling enterprise adoption at global scale.
AI in Action: Real-World Success Stories from 73 Strings' Clients
73 Strings applied AI is actively transforming how alternative asset managers operate. From private equity firms to institutional investors, the platform is enabling organizations to scale their operations, reduce turnaround times, and improve decision quality without sacrificing human oversight. Here are real-world examples that illustrate the power of this paradigm.
Private Equity and Venture Capital: The Efficiency Revolution
For PE and VC firms, managing a diverse portfolio of companies across industries and geographies often requires significant time and manpower. 73 Stringsʼ AI platform changes that.
- Wendel Group (€9.5B AUM): By automating data collection across its portfolio companies, Wendel significantly reduced the time analysts spent on manual data gathering—freeing them to focus on value creation and strategy.
- Eurazeo (€35B AUM): With investments spanning multiple strategies and regions, Eurazeo leverages 73 Strings to streamline valuation modeling and centralize insights, improving internal coordination and reporting timelines.
- Sofinnova Partners: As a life sciences-focused VC, Sofinnova faces frequent challenges in valuing pre-revenue biotech startups. 73 Strings' platform accelerates this process through structured scenario modeling and enhanced comparables analysis.
Impact: For many clients, quarterly reporting cycles that once took several weeks can now be completed in days—without compromising on auditability or methodological rigor.
Beyond Traditional Alternatives: Expanding into New Asset Classes
The flexibility of 73 Strings' platform enables clients to extend the use of platform beyond equity investments to Private Credit, Infrastructure Investments, Corporate M&A Teams, and Insurance Firms
Impact: By adapting to various asset classes, 73 Strings positions itself as a universal intelligence layer across the alternative investment lifecycle.
The Numbers Don't Lie: Quantifying the Impact
AI at 73 Strings is not just a vision—it delivers measurable, transformative results across valuation workflows. By combining deep domain expertise with cutting- edge AI, the platform consistently drives operational efficiency, improves data integrity, and enhances strategic decision-making. Here are the metrics that demonstrate its impact:
Operational Efficiency Gains
- 10x faster valuation cycles compared to traditional, spreadsheet-driven processes.
- From weeks to hours: End-to-end valuations that once took 2–3 weeks can now be completed in less than 48 hours.
- 80%+ reduction in manual touchpoints across data extraction, modeling, and reporting stages.
Accuracy and Reliability
- Up to 99% accuracy in extracting structured data from unstructured financial documents (e.g., PDFs, emails, investor updates).
- AI models continuously self-improve with each valuation cycle, ensuring higher accuracy over time.
- Built-in validation and human-in-the-loop checks maintain transparency and auditability.
Cost and Resource Optimization
- Up to 50% reduction in valuation-related operational costs for clients.
- Freed analyst time reallocated to strategic initiatives, scenario analysis, and client advisory.
- Improved resource scalability without proportional increases in headcount.
AUM Scale and Market Reach
- $2+ trillion in assets under management processed through the platform across private equity, venture capital, credit, and institutional portfolios.
- Real-time portfolio monitoring becoming the norm, replacing static quarterly batch processes.
Human Impact: Empowering Analysts
- Analysts spend 70-80% less time on data cleansing and manual model updates.
- Elevated focus on portfolio diagnostics, market signals, and performance strategy.
- Increased job satisfaction from transitioning out of “grunt workˮ into high- value analysis.
Market Validation and Industry Recognition
The success of 73 Strings' AI approach is not theoretical—it is being recognized and validated by some of the most influential names in finance and technology. From investor backing to industry accolades, the platformʼs momentum is backed by proof points that matter.
Strategic Investment from Industry Leaders
- $10.8 million Series A funding led by Blackstone Innovation Investments and Fidelity International Strategic Ventures—a powerful endorsement from firms that both invest in and benefit from the platform.
- $55 million Series B funding led by Goldman Sachs with Golub Capital and Hamilton Lane joining as new investors as well
- These investors are not just financial backers—they are strategic partners, aligned with 73 Stringsʼ long-term mission to transform alternative asset management.
Award-Winning Innovation
- Named Best Portfolio Management Software Provider at the US Emerging Manager Awards 2024, recognizing its impact on emerging fund managers and institutional investors alike.
- Regularly featured in fintech and private capital industry forums as a leader in valuation automation and augmented intelligence.
Trusted by Global Institutions
Trusted by major players across Europe, North America, and Asia, including:
- Wendel, Eurazeo, Sofina, Sofinnova, and other top-tier PE/VC firms.
- Sovereign wealth funds, pension funds, and insurance companies with multi-billion-dollar mandates.
- Deployed across Paris, London, New York, Toronto, and Bengaluru, supporting global investment workflows around the clock.
The Road Ahead: Future of Agentic AI in Finance
As the alternative asset management industry continues to scale and diversify, agentic AI is emerging as a cornerstone of future-ready investment operations. 73 Strings is actively shaping this evolution, both through continued innovation and by enabling firms to reimagine how valuations, risk, and reporting are managed in real time.
Technology Evolution and Innovation
The AI stack is evolving beyond automation to deliver proactive, insight- driven intelligence:
- Predictive analytics: Machine learning models forecasting portfolio performance, potential write-downs, and exit timelines.
- Agentic AI: Agentic chatbots that allow to answer any questions about portfolio financials, generate insights and reports, or trigger a new valuation workflow - all with just using natural language.
- Real-time collaboration: Multiple analysts and decision-makers working synchronously on valuation workflows.
- ESG integration: Embedding environmental, social, and governance metrics into valuation models for better stakeholder alignment.
Industry Transformation Trends
- Continuous monitoring is replacing the quarterly valuation cycle, driven by investor demand for real-time visibility.
- The industry is shifting from relationship-driven decisions to data-informed strategies.
- Mid-market players—historically constrained by limited resources—are gaining access to enterprise-grade tools via SaaS delivery.
- Enhanced secondary market insights are enabling more dynamic portfolio rebalancing and liquidity planning.