Companies

Kimpton AI

kimpton.ai

Kimpton AI provides AI-native investment research tools that help portfolio managers analyze portfolios and generate trade proposals.

HQSan Francisco, California, United States
Employees1-50
Jobs checked 44m ago
FintechAI ApplicationB2B SaaS

About

Kimpton AI builds an AI-native investment research platform for portfolio managers and other buy-side investors. Its always-on analyst ingests portfolio data, synthesizes research, drafts trade proposals, monitors portfolios, and delivers morning briefs; its differentiator is a “caddy, not the golfer” workflow in which AI handles preparation while the human portfolio manager retains final investment authority.

Market

Kimpton competes in B2B buy-side investment-research and portfolio-management software, positioning itself as an AI-native terminal or IDE that converts institutional data, mandates, and portfolio context into structured trade proposals rather than offering only a general-purpose chatbot or a standalone research database. Its differentiation is the integration of cited research, dashboards, charting, reports, and recurring workflows with a specific fund's positions and strategy, while keeping final investment judgment with the human portfolio manager. The market is crowded with established research platforms and AI-native entrants, so Kimpton's fund-operator heritage and mandate-aware personalization are meaningful but not necessarily insurmountable advantages.

Target Customers

Kimpton targets institutional public-markets investors, especially hedge-fund portfolio managers, family-office investment heads, active equity managers, and other buy-side investment teams; sophisticated individual investors are also served. Its initial enterprise focus is fundamental-equity funds in the approximately $1B-$10B range, with enterprise plans designed for firms deploying the platform across multiple portfolio managers and analysts.

At a Glance

Problem

Investment managers are under pressure to improve performance, but much of a portfolio manager’s time is consumed by fragmented research, data gathering, monitoring, and repetitive analyst work. Kimpton frames the economic pain as both the cost of that labor and the opportunity cost of keeping the person with investment judgment away from decisions that can affect returns. The central use case is turning a fund’s mandate, strategy, positions, and transaction history into a structured, evidence-backed trade proposal rather than another memo or presentation.

Kimpton is especially focused on fundamental equity managers whose teams must continuously monitor exposures, thesis drift, earnings coverage, positioning, and risk. Its founders argue that AI can conduct research at dramatically greater efficiency than a human analyst, while the portfolio manager remains responsible for judgment and final decisions.

Product / Service

Kimpton is an AI-native investment research and portfolio-workflow platform. Its agents combine market data, earnings, news, portfolio holdings, transaction data, and firm-specific context to produce cited research briefs, long-form reports, dashboards, charts, portfolio projections, and trade proposals. Those proposals can include sizing, rationale, tax analysis, mandate-compliance checks, counterarguments, and an exportable path toward execution, while Kimpton explicitly avoids making the AI the final decision-maker.

The delivery model is a self-serve Pro subscription priced at $200 per person per month, alongside a custom-priced Enterprise offering for firms. Enterprise adds capabilities such as multi-user access, sub-portfolio management, compliance reporting, dedicated support, and FactSet integration. The benefit is a persistent, portfolio-aware research assistant that automates preparation and repetitive workflows while preserving the PM’s control over investment decisions.

Market

Kimpton competes in AI-powered financial research and institutional buy-side workflow software, with a sharper focus on portfolio managers and converting research into structured trades. Adjacent competitors include Rogo, which positions itself as an AI partner for financial institutions; Hebbia, an AI platform for finance; and AlphaSense, an enterprise market-intelligence platform using generative AI. Kimpton’s differentiation is its combination of firm and portfolio context, research automation, dashboards, and trade proposals in one PM-oriented workspace rather than a research-only interface.

The company is early but has moved beyond a purely pre-launch position. It publicly launched through Y Combinator in June 2026, reports that it is live with a first institutional client—a $3.3 billion manager—and identifies fundamental equity funds managing $1 billion to $10 billion as its first market. The public materials reviewed disclose no revenue or ARR figure, so Kimpton is best characterized as an early commercial company with initial institutional traction, not as demonstrably revenue-generating at scale.

Founders & Leadership

Jack ZumwaltFounder
Co-founder & CEO
Mauricio OrtizFounder
Co-founder & CTO
Adrian Del BosqueFounder
Founding Engineer

Funding History

2026-06
Pre-Seed / Seed$500K

Y Combinator

Recent News

2026-07-16product
A shared brain for the investment team

Kimpton announced new data connectors that bring a team’s private knowledge into the same research surface as filings, market data, and portfolio context.

2026-06-25product
Introducing consumption-based pricing

Kimpton introduced credit-based pricing, including daily free credits, monthly plan credits, one-time top-ups, auto-recharge, and spending controls.

2026-06-12product
Introducing Kimpton Email Agent

Kimpton launched an Email Agent that turns inbox content and attachments into an investment workflow, connecting messages to market context and follow-up tasks.

2026-06-01
Kimpton launches on Y Combinator: Cursor for portfolio managers

Kimpton announced its public launch through Y Combinator. The company describes the product as an AI-native terminal where agents research and propose trades, built by a team that previously ran a quantitative fund.

2026-05-07product
Enterprise workflow hardening

Kimpton added enterprise operating features including team workspaces, scoped sharing, scheduled skills, notifications, vault-context controls, and stronger permission boundaries.

2026-04-17product
Vault and Terminal

Kimpton introduced Vault for semantic search over uploaded research and a Terminal workspace with live reasoning and tool streaming.

2026-04-11partnership
Infinite canvas, backtesting, reports, and enterprise data

Kimpton expanded its research workspace with inline canvas outputs, Pine Script backtesting, AI reports, model portfolios, a data gateway, and FactSet OAuth for enterprise users.

2026-03-26product
Dashboards and trade proposals

Kimpton added natural-language dashboard creation, customizable widgets, portfolio tracking, and evidence-backed trade proposals.

2026-03-14product
Skills and personalization

Kimpton introduced reusable research skills, contextual references, workspace organization, and personalization features for investment workflows.

2026-03-04
Kimpton AI Joins Y Combinator X26

Kimpton announced acceptance into Y Combinator’s X26 batch as it develops an AI investment-research platform for the buy side.

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Business Model

Kimpton sells subscription access: Pro costs $200 per person per month, while Enterprise is custom-priced per firm and scales with seat count. Enterprise includes FactSet integration, multi-user access, compliance reporting, and dedicated support.

Products

AI-native investment research and portfolio-analysis terminalDeep ResearchTrade ProposalsAI-generated ReportsNatural-language AI DashboardsAgentic Charting and BacktestsSkills for recurring analyst workflows

Tech Stack

AI-agent and AI-inference layerNatural-language interfaces for dashboards, charts, reports, and workflow automationInstitutional financial-data integrations: FactSet, Massive, Tiingo, and PolymarketRead-only brokerage connectivity through Plaid or similar secure connectorsInteractive charting, Monte Carlo simulations, and backtestingReal-time and historical options data through OPRA

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