Linq

Linq is an AI-powered research platform built for Professional investors. Rather than ACTing as a General-purpose chatbot, it focuses on the everyday work of hedge funds, asset managers, and Investment analysts: digging through filings and reports, answering questions quickly, and turning findings into usable write-ups. The result is a workspace where financial data and documents can be queried in plain language.

What it does

Linq combines large language model Technology with financial-domain data sources to support investment research. Users can ask questions about companies or markets and receive condensed answers drawn from large collections of financial documents. The platform is also positioned to assist across the research cycle, from preparing for calls to capturing notes and drafting investment mEMOs.

Key capabilities

• High-precision search: A search layer designed to retrieve relevant passages from dense financial material rather than generic web results.
• Instant Q&A: Natural-language questions return quick answers so analysts can orient themselves before deeper reading.
• Document synthesis: Financial reports and filings can be summarized and compared to support analysis.
• Memo drafting: The tool helps assemble investment memos and background on new targets using industry datasets.
• Workflow support: Scheduling calls, producing live notes, and drafting follow-ups are described as part of the offering.
• SECurity and compliance: The company states it follows ISO 27001 practices and has been progressing toward SOC 2 Type 1 attestation; current status may vary, so confirm details directly.

Who it is for

The platform targets buy-sIDE professionals such as hedge fund analysts, portfolio managers, asset managers, and investment research teams. It suits users who already work with large volumes of financial disclosures and want to shorten the path from raw documents to a defensible view. Teams that need auditable sourcing and data handling controls will want to review the vendor's security documentation before adopting it.

How to get started

Prospective users typically begin by visiting the official website and requesting access or a demo, since Enterprise research tools often onboard CLIents through a sales conversation. After account setup, the usual first steps are connecting or selecting relevant document sources, testing a few questions on a familiar company, and comparing the ouTPUt against source filings. building a small internal pilot with one or two analysts is a practical way to judge answer quality before wider rollout.

Pricing and access

Specific plan details are not published in the source material and may vary by firm size and usage, so pricing should be confirmed with the vendor. Access APPears to be web-based, and availability may depend on account approval. Treat any compliance certifications or feature claims as items to verify during evaluation, and remember that AI-generated research output should always be checked against primary documents before it Informs an investment decision.