73 Strings has acquired Paris-based fintech Callisto as the valuation and portfolio intelligence provider looks to embed agentic AI deeper into private-market investment workflows. The deal will bring Callisto’s AI data infrastructure into 73 Strings’ platform, with an initial focus on enabling AI agents to work with financial documents, data rooms, spreadsheets and portfolio information while keeping valuation calculations auditable and human oversight in place.

73 Strings is expanding its artificial intelligence capabilities in private markets through the acquisition of Callisto, a Paris-based fintech focused on automating data-heavy investment workflows.

The deal brings Callisto’s AI engineering team and technology into 73 Strings, which provides valuation and portfolio intelligence software to alternative asset managers. The combined platform is intended to use agentic AI across processes including due diligence, data extraction, investment documentation and portfolio analysis.

The acquisition reflects a broader shift in private markets toward AI systems that can do more than summarize investment information. Asset managers are increasingly exploring AI for workflows that involve large collections of financial documents, spreadsheets, data rooms and proprietary databases.

Callisto’s technology is designed around those environments. According to the companies, its platform uses agentic data pipelines, financial-document embedding models and an orchestration layer that allows AI agents to work with complex Excel files, due-diligence questionnaires, data rooms and internal databases.

The technology will now be incorporated into 73 Strings’ existing valuation, extraction and monitoring products. The company said those platforms will become more agent-addressable, with the integration built around the Model Context Protocol (MCP) so AI agents can access relevant data and execute workflows.

That architecture could become important as financial institutions move from standalone AI assistants toward systems capable of taking action across enterprise applications.

In private equity and private credit, for example, an AI agent may need to retrieve portfolio information, interpret financial statements, perform calculations and produce an investment analysis. A general-purpose chatbot can help with individual steps, but executing the full workflow requires access to structured data and controlled connections to underlying systems.

73 Strings is initially targeting this capability through 73 Intelligence, its AI platform for private markets. The company said Callisto’s infrastructure will be used to add simulation capabilities, allowing asset managers to model how portfolio valuations and fund-level outcomes could change under different macroeconomic and market assumptions.

The move points to a broader evolution in portfolio intelligence. Traditional reporting largely explains what has already happened: valuations, performance and portfolio-company metrics. AI-assisted simulation potentially shifts the workflow toward exploring what could happen under different scenarios.

The distinction matters for investment teams managing complex private-market portfolios. Private assets typically involve less frequent pricing and more heterogeneous information than publicly traded securities. Investment professionals therefore need to combine financial statements, operating metrics, valuation assumptions and market conditions when assessing portfolio companies.

AI can potentially accelerate that process, but reliability remains critical. A valuation system cannot treat a probabilistic model’s output in the same way as an accounting calculation. 73 Strings said the new architecture will retain a deterministic core valuation engine, with traceable calculations and human judgment remaining central to valuation decisions.

That hybrid approach is notable because it separates AI-driven workflow automation from the underlying financial calculation engine. AI agents can retrieve information, organize inputs and assist with scenario analysis, while controlled calculation systems can provide reproducible outputs.

The acquisition also brings additional AI engineering talent into 73 Strings. Callisto co-founders Charles Farhat and William Profit have been appointed co-heads of AI Product and will report to Chief Product Officer Matt Storey.

The company said it has also been hiring senior engineering and product executives as demand for valuation technology increases.

73 Strings said its platform serves clients representing approximately $20 trillion in assets under management, including nine of the 10 largest private-capital firms globally. Those figures are company-provided.

The acquisition follows a $55 million Series B announced in 2025, led by Goldman Sachs Alternatives’ Growth Equity business, with participation from Blackstone Innovations Investments, Golub Capital, Hamilton Lane, Broadhaven Capital and 7RIDGE. HSBC Innovation Banking also supports the company, according to 73 Strings.

For the broader fintech market, the transaction highlights an emerging category of AI infrastructure for private capital. Instead of replacing investment professionals with autonomous systems, platforms are increasingly being designed to give AI controlled access to the structured information and workflows professionals already use.

That creates both an opportunity and a governance challenge. Private-market investment decisions involve sensitive financial information and potentially consequential valuation judgments. AI systems therefore need permission controls, audit trails, reproducible calculations and clear boundaries around human decision-making.

73 Strings’ combination of MCP-based agent access, deterministic valuation infrastructure and human oversight reflects that tension.

The success of the strategy will ultimately depend on whether AI can reduce the time spent on repetitive investment operations without compromising the accuracy and auditability required by institutional asset managers. The Callisto acquisition gives 73 Strings an expanded engineering base to pursue that goal as private-market firms continue to digitize their investment workflows.

Market Landscape

Private markets are becoming a significant target for AI-driven financial workflow automation, particularly in areas such as due diligence, portfolio monitoring, valuation and investment documentation.

The market is moving from document summarization toward AI systems that can interact with structured financial infrastructure. Protocols such as MCP could help agents connect with specialized enterprise platforms, while deterministic calculation engines and audit trails provide controls around higher-risk financial operations.

The development is relevant to Financial Technology, Digital Assets, Banking Technology Innovation and fintech infrastructure, particularly as alternative asset managers seek to automate workflows without removing human accountability from investment decisions.

Top Insights

• 73 Strings acquired Callisto to integrate agentic AI infrastructure into valuation, portfolio intelligence and private-market investment workflows.
• Callisto’s technology lets AI agents work with financial documents, Excel files, data rooms, DDQs and proprietary investment databases.
• MCP integration will make 73 Strings’ valuation, extraction and monitoring platforms more accessible to AI agents and automated workflows.
• 73 Intelligence will add simulation capabilities for modeling portfolio and fund outcomes under changing market and macroeconomic assumptions.
• 73 Strings says human judgment will remain central, with AI operating alongside traceable calculations and a deterministic valuation engine.

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