Building Domain-Specific AI for Institutional Investing

The system intuitively learns and thus recommends which investment opportunities "fit" inside an investor's portfolio

The $100 Trillion-Scale Challenge

2.3 million institutional investors oversee more than $130 trillion, making hundreds of thousands of allocation decisions every day in a race that today's talent pool and tool-stack simply cannot win.

Yet this unprecedented scale creates cascading cost crises
that threaten institutional mission fulfillment:

Massive Tool & Integration Expenses
Institutions pour millions into largely two types of platforms: data feeds and analytics platforms. They license risk feeds, private-fund databases, private-company records, public-market streams, sentiment trackers, and index services just to see the full picture.
Followed by portfolio-management suites, dashboards, valuation engines, data-aggregation hubs, and CRMs to actually work that data. Even after all that spend, the systems still don't talk to each other, and IT teams burn years trying to stitch them together. Budgets balloon long before a single, reliable portfolio snapshot appears.
Massive Tool & Integration Expenses
Escalating Analyst Costs
Qualified investment professionals command premium salaries. Yet even top analysts spend 80% of their time stitching data together—finding interrelationships, spotting incorrect information, and building a 360-degree view across fragmented systems.
Only after all this data preparation work can actual investment analysis begin. Despite having sophisticated tools, the preparatory work hasn't gotten any shorter.
Escalating Analyst Costs
Investment Decision Speed and Quality
Poor investment insights lead to devastating losses. GPs present misleading IRRs all the time. For example, one fund claimed 24% returns while one of our customers found the actual performance was only 6% after accounting for fees and J curve distributions.
Quarterly benchmarking is "almost never done." Institutions make allocation decisions in an information vacuum. Without real-time investment monitoring systems, institutions miss critical entry and exit opportunities.
Investment Decision Speed and Quality

The Result

Allocators abandon internal capabilities entirely. They rely on consultants, OCIOs, and
fund-of-fund structures just to reach baseline goals.

In growth markets, these operational gaps may go unnoticed, but in downturns, lack of insightful decision-making proves catastrophic.

The Paradigm Shift

Domain-Specific AI: The Only Scalable Solution That Thinks Like The Investor

We build domain-specific AI that fundamentally changes institutional investing. Unlike horizontal base models applied to specialized problems, our AI systems are engineered exclusively on institutional investment data, decision-making processes, committee feedback, due diligence frameworks, and regulatory requirements. Traditional solutions have hit their limits, leaving the world's most sophisticated investors managing tomorrow's capital with yesterday's manual processes.
Our specialized architecture enables two powerful capabilities. It analyzes thousands of investment data points through advanced reasoning models. It understands regulatory constraints across different institution types. With this architecture, the whole lifecycle of investment decision-making from screening and dilligence to monitoring and exits, is completely automated with the investor's own criteria and profiles.

Meet The Team

Dr. Ashby Monk

Founding Advisor

Executive & Research Director at SLTI, working to advance institutional investment practices.

Previous Head of Research at Addepar, and Co-founder and President at RCI/Navigator.

Holds academic credentials from Oxford, University of Paris-1, and Princeton.

Rajeev Bharadhwaj

Chief Executive Officer

Rajeev is a seasoned entrepreneur with a history of leading companies to successful exits, including Ejasent (acquired by Veritas) and Griddable (acquired by Salesforce).

Founding CTO of Aryaka Networks a pre-IPO company.

 Expertise across data, SaaS, virtualization, and networking sectors.

Dr. Christopher Thomas

PhD, Chief Technology Officer

Former NLP Lead at Glint, acquired by LinkedIn, and Director of Applied Research & NLP at Kyndi. Founding

Director of Machine Learning at Atomic Search.

PhD from the Ohio Center of Excellence in Knowledge-Enabled Computing.

Tobin Kim

Chief Product Officer

Former Global Head of Product at Masttro, and Product Executive Leadership at Addepar and Bloomberg.

Started career in investment banking and private equity followed by a decade in long/short equity portfolio management.

MBA in Finance from the Wharton School of the University of Pennsylvania and BA in Economics from Johns Hopkins University.

Raj Kumar Yadav

Head, India

Seasoned professional with experience in data science and AI, having held leadership roles across multiple industries.

Specializes in building and managing teams to deliver innovative solutions in areas like GenAI, machine learning, and analytics.

Proven track record in driving business growth, P&L management, and strategic planning.

Our Investment Backbone

Strategic Investors

Specializing in technology investments, KDX Ventures supports startups with strategic capital and insights, aiming to drive growth and innovation.

With a focus on promising startups, UCR Investments provides both funding and deep industry knowledge to help companies reach their full potential.

Angel Investors

Jim Smith

Stereo Capital

As a General Partner, Jim leverages his expertise to guide tech startups from inception to market leadership.

Paul Constantinides

Salesforce

Paul's role as EVP Engineering brings a strategic edge to developing enterprise solutions that shape the future.

Sriram Samu

Kroger

At the helm of engineering, Sriram drives retail technology forward, improving customer engagement through innovation.

Saar Gillai

Semtech

A tech executive and board member, Saar offers strategic guidance to startups aiming for technological disruption.

Michael Shepherd

GrowthPoint and StealthPoint

A founder and partner specializing in growth-stage tech advice, focusing on finance, M&A, and strategic growth opportunities.

Advisory Board

R Venkatanathan

Ex-Managing Director with 35 years in global financial markets, specializing in UHNW clients and FO portfolio management.

Mark Potts

Global tech executive, ex-HP CTO/VP, with expertise in AI, RPA, Blockchain, and leadership in ASX-listed tech companies.

Emerson Yip

Ex-JPMorgan Asset Management Managing Director and ex-TPG. 25 years of experience in investment banking, private equity, and public equities portfolio management across Asia and the US.

Prabakar Sundarrajan

Heads technology and strategic elements of The Fabric’s co-creation initiatives, bringing 30+ years of entrepreneurial success to the effort. Co-founded and had successful exits in multiple start-ups.

Partners

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