KelAI GTM brain

KelAI builds an AI-driven investment research engine to help hedge funds and institutional investors discover and validate trading signals.

category

AI quant research

market profile

  • text: Investment research involves fragmented data, tools and workflows; KelAI positions agents as a continuous research loop.
  • text: Buyers can compare agent-based research with quant backtesting environments and AI signal research products.

personas

  • title: Quantitative Portfolio Manager
    pains:
    • Research throughput limits the number of signals a team can investigate.
    • New ideas must be validated rigorously before influencing capital allocation.
  • title: Head of Quant Research
    pains:
    • Research data and knowledge are scattered across systems.
    • Researchers repeatedly reproduce tests and struggle to compound institutional knowledge.
  • title: Quant Developer
    pains:
    • Maintaining data, testing and research infrastructure diverts capacity from signal discovery.

icp

  • text: Hedge funds and institutional investors running systematic or quantitative strategies are explicit targets; AUM and employee thresholds are not stated.
  • text: Research teams with proprietary investment knowledge, multiple datasets and a repeatable signal testing process are a plausible fit.

message pillars

  • text: Present an AI engine for investment research.
  • text: Help teams discover and validate new ideas.
  • text: Focus on an institutional buyer.

objections

  • objection: How do we know discovered signals are robust rather than overfit?
    response: Evaluate out-of-sample results, transaction costs and reproducibility in a controlled pilot; no performance guarantee is implied.
  • objection: Will our proprietary research and data remain protected?
    response: Review data handling, access controls and deployment terms directly before sharing sensitive inputs.
  • objection: Our quant team already has a research stack.
    response: Test whether the system complements an existing research workflow and produces useful, independently verified hypotheses.

competitors

  • name: QuantConnect
    why: Provides quantitative research and backtesting infrastructure.
  • name: Kavout
    why: Offers AI-based investor research and signal discovery.
  • name: HDGE
    website: https://hdgefinance.com/
    why: Offers agent-based quant research and backtesting for funds and trading desks.

keywords

  • AI quant research platform
  • hedge fund signal discovery
  • automated alpha research
  • quantitative strategy backtesting
  • AI investment research
  • systematic trading signal validation

voice

  • Institutional
  • Technical
  • Research-oriented

signals

  • text: A hedge fund is hiring quant researchers or expanding systematic strategies.
  • text: An investment team is consolidating fragmented alternative data and research workflows.

hiring

  • Quant Researcher
  • Applied AI Engineer
  • Senior Infrastructure Engineer

pricing

model: unknown

motion

sales_led

channels

  • website
  • LinkedIn
  • YC directory

confidence

medium

Founders

  • name: Jeremie Cohen
    title: Founder/CEO
    role: CEO
    bio: Founder and CEO of KelAI. Managed a large global systematic equity book at WorldQuant and lead an ML team at Millennium Management. Nuclear engineer by training.

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