Paris-based startup 73 Strings was established to modernise the data and valuation infrastructure for private market participants. Data Management Insight spoke to founder and chief executive Yann Magnan about the company’s operations and its ambitions.
Data Management Insight: Hello Yann, when was 73 Strings created and how does it serve financial institutions?
Yann Magnan: We founded 73 Strings in 2020 to solve a problem private markets had stopped solving for itself: the post-investment process, including valuation, portfolio monitoring and data flow between general partners (GPs) and their stakeholders, was manual, fragmented and increasingly out of step with how the industry was being asked to operate.
73 Strings is the governed data and valuation infrastructure for transaction-grade private markets. Our platform, 73 Intelligence, brings data extraction, portfolio observability and valuation into one governed system, with AI turning structured and unstructured inputs into auditable, immediately usable outputs.
The impact is measurable. Clients run valuations up to 10x faster, reduce operational costs by as much as 50% and achieve more than 99 per cent data extraction accuracy. More importantly, they get clarity and speed without giving up the audit trail, which is exactly what a market with rising Limited Partner (LP), auditor and regulatory scrutiny demands.
DMI: What is the driving mission behind 73 Strings?
YM: Our mission is to become the infrastructure layer the industry runs on for valuation, portfolio data and the analytics built on top of both, used by GPs, valuation providers, auditors, financing banks and other stakeholders alike.
The shift driving us is structural. As private markets move toward evergreen structures, retail and 401(k) participation and more frequent valuation cycles, alongside the longstanding demands of fund finance, back leverage and hedging, valuations are no longer just quarterly reporting artefacts. They are transaction inputs. Every net asset value (NAV) is, in effect, a transaction price.
That changes what the work has to be. We give firms the data substrate, governance and intelligence layer to make valuation continuous, auditable and ready to hold up the moment a regulator, an LP, an auditor or a financing bank asks. Faster reporting is the surface benefit. The real goal is a governed process the whole ecosystem can rely on.
DMI: What are the most common pain points that 73 Strings solves for its clients?
YM: The biggest issue is data fragmentation. Critical information sits across systems, formats and teams, which means firms can’t use it effectively and certainly can’t feed it to AI without compounding the inconsistency.
We solve it by structuring and standardising both the inputs and outputs of the valuation process inside a purpose-built private capital data model. Every input is captured the same way each cycle and every output ships with full lineage, including inputs, methodology, judgment calls and version history. Defensibility becomes the default state, not a mode firms switch into when an auditor calls.
The second pain point is the cognitive load on analysts. Time is spent reconciling data, comparing periods and building reports in Excel, not on judgment. We replace those workflows with AI-assisted processes and bring valuation, technology and portfolio monitoring teams onto a single platform. The work shifts from data-wrangling to decision-making.
DMI: What are the newest challenges that 73 Strings is helping clients overcome?
YM: AI readiness is the dominant new challenge. Firms want to deploy generative AI but their underlying data isn’t structured, governed or auditable enough to support it. Without that foundation, AI accelerates the wrong answers.
At the same time, volume and frequency are climbing. Analysts are expected to process more data, more history and more market inputs than ever, with less time per decision. We use AI to compress that cognitive load but only because our data substrate makes the AI trustworthy in the first place.
The wealth channel is also raising the bar quickly. Evergreen and retail flows mean NAVs feed subscriptions, redemptions, fund finance and hedging, often tied directly to performance and compensation. That standard is migrating to every GP, not just those running evergreen products. Auditors, regulators and financing banks are paying closer attention. Consistency, transparency and auditability are now table stakes.
DMI: How is unstructured data provision changing in the age of AI?
YM: Unstructured data has moved from byproduct to core asset but only for firms that can actually make it usable. Financials, memos, board packs and covenant reports: the information exists but it sits in formats that resist automation and in volumes that defeat manual processing.
Hundreds – increasingly thousands – of consistent, time-series data points per portfolio company, captured the same way every reporting cycle: that’s what turns disconnected documents into an observable system of record. Our private capital data model is built for exactly this. Raw inputs become consistent, machine-readable information that investment teams, valuation and risk committees, operating partners, IR teams and LPs can all rely on.
The next wave of progress will be determined by data quality and governance, not raw model capability. The organisations that get this right now will compound the advantage as AI tools keep improving, because better models can’t fix worse data.
DMI: What does 73 Strings see as the next big thing in data management?
YM: The next shift is a progression up the stack. Most firms in private markets are still building their system of record: the governed data substrate that captures portfolio information consistently. A strong data model plus generative AI turns that record into a system of intelligence, producing defensible, transaction-grade outputs.
The real unlock is the next two layers. A system of action, where governed execution transacts on those valuations, feeding subscriptions, redemptions, fund finance, hedging and compensation with the same auditable trail. Then a system of coordination, where GPs, valuation providers, auditors, financing banks and other stakeholders operate from a common governed data layer rather than reconciling the same data independently.
That is where 73 Strings is heading. Intelligence is becoming abundant. Governed execution, the infrastructure that makes intelligence trustworthy enough to transact on and share across the ecosystem, remains scarce. That is the layer we are building.
DMI: What’s in the pipeline for 2026?
YM: 2026 is about scaling what makes us different. The best technology for private markets has to be built by people who understand private markets, and we have, by a very large margin, the tech industry’s deepest bench of private market valuation professionals. That expertise is what keeps the platform genuinely useful to the people doing the work.
On the product side, we continue to invest across valuation, portfolio observability and data extraction, making it faster for firms to run high-quality, auditable valuations at scale and to put intelligence on top the moment it’s needed. Private markets are moving toward a world where valuation is continuous, governed and shared across the ecosystem. We are building the infrastructure that makes that possible and intend to be the standard it runs on.
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