We get stuff done
We deliver timely, practical solutions that work under your actual operating conditions and with your actual end-users.
An AI-native economics shop for private equity.
We build explainable, transparent AI and machine learning models grounded in economics for private equity investors.
Our team and Brain Trust bring experience from
Why Rational AI
We put economics-grounded AI to work across the private equity deal cycle.
We are good at our craft
We have delivered major projects for sophisticated customers including Amazon, Apollo, Bloomberg, and Two Sigma. Several members of our technical staff are PhDs and experts in their domains.
We are easy to work with
We meet you where you are, adapting to your data readiness, your IT systems, and your end-users. We keep development transparent and design solutions your end-users can readily audit.
Sample projects
Due diligence and valuation
Size the market for solar panels
Forecasted demand by using statistical models to identify the technology, macro, and regulatory drivers of demand, then rolling projections forward using forecasts of those drivers.
Concluded that COVID-era growth was unsustainable, leading the investment team to reduce its bid on a 9-figure acquisition.
Portfolio company value creation
Underwrite small-business credit for a marketplace platform
Ran a $1Bn loan business using AI to qualify borrowers and set loan amounts and durations.
Reduced loan origination costs while keeping default losses in the low single digits.
Reduce data-processing outages for a financial services company
Monitored hundreds of thousands of hardware instances to rapidly detect malfunctioning components using custom-built algorithms.
Reduced outages by 25%.
Redesign the customer experience for a video gaming platform
Managed game recommendations and playtime incentives across millions of interactions, using multi-step optimizations to maximize customer lifetime value.
Increased retention, generated net incremental revenue through ad-supported games, and reduced incentive costs.
Ongoing engagement
Value privately held companies at scale for secondaries deals
We are rapidly underwriting hundreds of companies using a combination of machine learning and agentic AI, improving valuation consistency, response times, and risk management.
More examples are available on request for specific areas of interest.
Our Brain Trust
We are economists who combine economic insights, business practicalities, and AI to assist in deal sourcing, valuation, and portfolio value creation. With combined expertise in operations, financial markets, and AI, we are uniquely positioned to address your business needs.
Aziz Lookman, PhD
Founder & Chief Analytics Officer
Aziz has spent more than twenty years combining subject-matter expertise with analytics and data. He was Head of AI at Two Sigma Private Equity, Global Chief Risk Officer at Amazon Capital Services, and Head of AI at AIG Professional Liability, and taught as a professor at Carnegie Mellon.
PhD in Finance, Carnegie Mellon University. BTech, IIT Bombay.
Amar Yashlaha
Data Architecture Advisor
Large-scale data warehousing and integration pipelines, with cloud services designed for Fortune 500 companies.
MS Electrical Engineering, Michigan State University
Stephane Caraguel
Machine Learning Advisor
Modeling that combines behavioral science and analytics. Bayesian networks across insurance, investment, adtech, and healthcare, including work on a NASA mission.
MS Applied Mathematics and Computer Science, ENSIIE
Niren Nazareth
Capital Markets Advisor
Twenty years in capital markets and investment banking. Raised over $20 billion at Deutsche Bank for clients including Alibaba, Dish Network, and the US Treasury.
MBA in Finance, Columbia University. CFA charterholder.
Jeff Helzner, PhD
Decision Science Advisor
Research decision scientist at Blackboard Insurance and AIG InsureTech. Led behavioral science work at AIG and taught as a professor at Columbia.
PhD in Logic, Computation and Methodology, Carnegie Mellon University
Work on problems with real bottom-line impact.
Real problems
The problems you solve show up directly in how funds and portfolio companies perform.
A deep bench
You will learn from colleagues and advisors with experience in statistics, machine learning, and business strategy.
A respectful team
We treat each other respectfully and are committed to each other's professional development.
Applied AI Engineer
Intern & full-timeDevelop AI tools for private equity investors across the deal cycle: sourcing, valuation, and portfolio value creation. The role blends data science, software engineering, and business sense.
Primary focus is junior-level full-time hires with authorization to work in the US.
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.