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Litir

Litir is an AI copilot for investment analysis that helps financial professionals process and interpret complex data more efficiently. The platform generates detailed summaries, enriches data instantly, and produces graphs and outputs to support investment decisions. It also includes peer selection capabilities to benchmark companies against relevant comparables.

Copenhagen, Denmark · HQ
Updated 4 days ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Investment professionals face overwhelming volumes of financial data, reports, and market information that must be synthesized quickly to make informed decisions. Manual analysis is time-consuming, prone to oversight, and often results in delayed or incomplete assessments of investment opportunities.

Solution

Litir provides an AI-powered copilot that streamlines the investment analysis workflow by automatically generating detailed summaries of financial documents and data sources. The platform enriches raw data instantly with relevant context and metrics, reducing the time analysts spend on manual research. Users can generate graphs and visual outputs directly from the tool, transforming complex datasets into clear, decision-ready formats. The peer selection feature helps analysts identify and compare appropriate comparable companies, supporting more accurate valuation and benchmarking work.

Target Audience

Primary users are investment analysts, portfolio managers, and financial professionals who need to accelerate their research and analysis workflows.

Features

  • AI-generated detailed summaries of financial documents and investment materials
  • Instant data enrichment that adds contextual metrics and relevant information to raw inputs
  • Automated graph and output generation for visual representation of financial data
  • Peer selection tool that identifies comparable companies for benchmarking and valuation analysis
This profile is AI-generated and may contain inaccuracies.