InferEdge GTM brain

category

market profile

• text: Investment teams repeatedly update models, attribution and client materials, creating mechanical work around judgment-intensive decisions.
• text: Buy-side AI procurement must address citation, control, data security and fit with existing analyst workflows.

personas

• title: Head of investment research
  pains:

  • Analysts spend earnings season refreshing models and coverage instead of evaluating the investment thesis.
  • Generic AI output needs verification and rewriting to match desk standards.
• title: Portfolio manager or chief investment officer
  pains:

  • Needs timely portfolio attribution and reliable decision inputs without surrendering investment judgment.
  • Cannot trust an opaque output without source citations and review.
• title: Head of technology or AI at an asset manager
  pains:

  • Turn promising AI prototypes into controlled production workflows on firm data.
  • Meet security requirements while connecting internal models and templates.
• title: Head of client servicing
  pains:

  • Rebuild investor-specific product notes and reports for different mandates.
  • Scale client updates without adding manual production work.

icp

• text: Institutional buy-side firms including asset managers, hedge funds and investment teams covering equity or fixed income.
• text: Firms with repeatable research, attribution or servicing workflows, proprietary models and enough workflow volume to justify integration.
• text: Larger regulated investment organizations needing private deployment and governance, including multi-billion-dollar funds.

message pillars

• text: Deliver the complete workflow rather than a generic tool.
• text: Automate mechanical work while investment professionals retain judgment.
• text: Build for reliable production with evidence and controls.

objections

• objection: Can AI be trusted with investment decisions?
  response: Keep decisions with the investment team and evaluate cited output against a defined workflow and review standard.
• objection: Will our sensitive data leave our environment?
  response: Discuss VPC deployment, data access and governance requirements in the proof of concept.
• objection: Will the system fit our existing process?
  response: Scope one repeated workflow and test it against the desk's own data, models and templates.

competitors

• name: LinqAlpha
  why: Offers specialized AI agents for institutional investors and investment research.
• name: Hebbia
  why: Agentic document research and analysis for financial institutions.
• name: AlphaSense
  why: Investment research platform with licensed content and AI research agents.

influencers

• name: Aditya Mehta
  url: https://www.inferedge.com/about
  why: Cofounder and CEO with asset management experience.
• name: Amal Dani
  url: https://www.inferedge.com/about
  why: Cofounder and CTO with quantitative hedge fund experience.

keywords

• AI investment research workflows
• buy side AI agents
• automated earnings model updates
• portfolio attribution automation
• asset management AI research
• investment research AI VPC
• AI for fixed income research

voice

• institutional and direct
• focused on usable outcomes
• technically credible

signals

• text: An asset manager is hiring AI engineers or launching a buy-side research automation initiative.
• text: Investment team coverage is expanding while analysts are overloaded during earnings season.
• text: Firm seeks private AI deployment and auditability for proprietary investment data.

stack

• Excel
• MCP
• VPC

hiring

• Software Engineer - AI Platform

pricing

motion

channels

• direct sales
• SEO
• content marketing

confidence

Founders

• name: Aditya Mehta
  title: Founder/CEO
  role: CEO
  bio: I have been working at the intersection of financial services and technology for more than 8 years, first as a quant at Goldman Sachs and then in the core team at a lending startup Paysense (acquired for $185 Mn by Payu). I love finding problems in financial systems and figuring out solutions to improve them. I am a silver medalist from IIT Bombay.
• name: Amal Dani
  title: Founder
  role: Founder
  bio: I enjoy solving problems from a data and technology perspective. Before Harmoney, I built portfolio management solutions using tech at Goldman Sachs and data-driven trading strategies at a $2 Bn hedge fund. I am a computer science grad from IIT Bombay.
• name: Omkar Ghaisas
  title: Founder
  role: Founder
  bio: After graduation, I have spent the last eight years of my career in Corporate Finance and Wealth Management. I enjoy learning about and solving financial problems. I predominantly look after business development at Harmoney.