Why are private market investors constrained by fragmented data systems?

Outcomes First AI

Private market decisions directly affect millions of end members, yet institutional investors are often constrained by fragmented, delayed data that increases cost and risk while limiting clarity and conviction. SheltonAI addresses this by operating as a continuous decision engine for private markets, enabling faster, better-informed decisions that improve returns, reduce operational drag, and strengthen governance.

The world’s first asset-level Operating Engine

SheltonAI was purpose-built as the central operating layer for sovereign wealth funds and pension systems investing in private markets. Designed as the home screen for private markets, the AI-native platform replaces fragmented tools with a unified, real-time system for portfolio visibility, risk assessment, and forward-looking decision support that translates complexity into actionable insight and stronger long-term outcomes for members.

Mission-Driven

Under the leadership of Harrison Shaw, CEO of SheltonAI, the company is redefining what is possible in private market investing by staying anchored to what matters most: members. Shaw has set a goal for SheltonAI to support 100 million pension and sovereign wealth fund beneficiaries by 2026, guiding how the platform is built, prioritized, and measured for impact.

Turning Operational Automation into Investment Insight

How does SheltonAI automate complex institutional investment workflows?

10x-ing the Hardest Work in Private Markets

SheltonAI automates the most time-consuming work institutional investors face by extracting, structuring, and validating data directly from investor documents. The platform interprets fund terms, reconciles cash flows across systems, validates NAVs against custodian records, and automatically updates models as new financials arrive. By capturing up to seven times more data points than manual processes, SheltonAI significantly reduces the time teams spend on data preparation.

We help institutional investors make better decisions at scale, and that impact ultimately shows up in outcomes for members,” says Paige Shiring, Director.

“When teams no longer have to manually extract, reconcile and validate data, they can focus on improving performance, managing risk and delivering better outcomes for members,” says Paige Shiring, Director at SheltonAI.

How does SheltonAI integrate risk management into daily investment decisions?

Embedding Total Portfolio View Risk and Decision Intelligence into Daily Workflows

With a trusted data foundation in place, SheltonAI embeds risk management and decision intelligence directly into day-to-day workflows. Investors can identify where value is being created, surface emerging risks earlier, and act with greater confidence—without waiting for delayed reporting.

From Asset-Level Insight to Action Instantly

Teams use SheltonAI to benchmark performance, assess GP effectiveness, identify regions and sectors positioned to outperform, and stress-test portfolios against changing conditions such as rising interest rates. Dynamic scenario modelling allows assumptions to be adjusted in real time, while a clear audit trail ensures decisions remain transparent, defensible, and well-governed.

Real-World Case Studies

What measurable results have institutional investors achieved using SheltonAI?

SheltonAI partners with some of the world’s largest institutional investors, delivering measurable value across investment, operations, and risk teams.

A large Canadian pension fund used SheltonAI to proactively identify portfolio positions at risk of missing internal IRR hurdles. With bottom-up portfolio data and validated forward projections, the team exited underperforming investments and redeployed capital into higher-yielding opportunities. The fund expects to realize more than CAD $200 million in value over five years.

A large Australian superannuation fund uses SheltonAI’s proprietary valuation framework to estimate daily NAV as part of its quarter-end workflow. On a trailing five-quarter basis, SheltonAI’s estimates have been approximately 13x more accurate than prior GP marks. As a result, the fund now benefits from more timely and accurate valuations without waiting for external reporting, driving an estimated AUD $100 million in value over five years through reduced NAV drift, improved accuracy, and operational time savings.

A large UK pension fund uses VeriFees, SheltonAI’s management fee and carry audit tool, to proactively identify potential over- and under-charges. By significantly reducing the time required to ingest and monitor data—saving thousands of hours—and flagging potential mischarges, the fund expects to generate approximately GBP £10 million in return over five years.