Capabilities

We put economics-grounded AI to work across the private equity deal cycle: due diligence and valuation, portfolio value creation, and secondaries.

Why Rational AI

We get stuff done

We deliver solutions that actually work. Under your operating conditions and with your end-users.

We are easy to work with

We meet you where you are. We adapt to your data readiness, your IT systems, and your end-users. We work collaboratively with your end-users and develop solutions they can readily audit and therefore trust.

We are good at our craft

Our experts have delivered major projects for demanding users including Amazon, Apollo, Bloomberg, Two Sigma, and the US SEC, informing billions of dollars of investments.

We bring experience from

Sample projects

Due diligence and valuation

9-figure

investment

TAM (Total Addressable Market) for residential solar panels

The situation: The deal team at a middle-market PE firm was evaluating a nine-figure investment in solar installers. Solar demand had rapidly grown over recent years, and the deal team were concerned if future growth would continue at a similar pace.
Our approach: We built a proprietary yearly demand model to forecast installations based on technology, behavioral, macro, and regulatory drivers. Next, using traditional and alt data sources, including proprietary inflation indicators from another portfolio company, we constructed multi-year forecasts for these drivers, and then coupled it with the yearly demand model to forecast multi-year TAM.
The outcome: Confirmed the deal team's concern of the business being overvalued, reducing the bid by 30+%.

$10Bn+

AUM

Precedent transactions for an acquisition

The situation: Each associate at a $10Bn+ buyout firm spent hours compiling and weighing relevant precedent transactions to form a baseline valuation of a potential acquisition. The firm wanted to streamline the underwriting process so associates could spend more of their time on high-judgment tasks.
Our approach: We used AI agents to scrape the web and internal documents to create an updated proprietary database of precedent transactions. Next, working with the deal team, we adjusted for qualitative and quantitative differences between the precedent transaction and the potential acquisition to develop a baseline valuation estimate.
The outcome: Reduced turnaround time from hours to minutes.

Portfolio company value creation

$1Bn+

loans

Credit underwriting for an online marketplace platform

The situation: The platform wanted to provide its merchants cost-effective credit with frictionless approvals.
Our approach: Implemented cashflow-based credit underwriting using AI to forecast merchant financials.
The outcome: Ran a $1Bn loan book, with minimal manual review, while keeping default losses in the low single digits.

Petabytes

of data across hundreds of thousands of hardware instances

Reduce data-processing outages for a financial services company

The situation: The firm wanted to achieve an uptime of 99.999% while processing petabytes of data across hundreds of thousands of hardware instances.
Our approach: We custom-built an algorithm to first learn what is normal operating behavior for each instance and then detect failed instances as deviations from normal operations.
The outcome: Reduced outages by 25%.

Billions

of interactions optimized

Redesign the customer experience for a video gaming platform

The situation: A video gaming platform with millions of active users wanted to improve its CLTV.
Our approach: Managed game recommendations and playtime incentives across millions of interactions, using multi-step optimizations to maximize customer lifetime value.
The outcome: Increased retention, generated net incremental revenue through ad-supported games, and reduced incentive costs.

More examples are available on request for specific areas of interest.

Talk through the AI opportunities inside your fund or portfolio.

We can help rank opportunities, assess vendors, prepare data, and build custom tools where they make sense.