Daloopa

Research & Analysis — Paid

An AI copilot that extracts source-linked financial data and automates building and updating company models.

Source-linked model automation

Overview

Daloopa is a research and analysis tool built for fundamental analysts and small funds who build financial models by hand and want the manual data entry removed. This Daloopa review covers an AI copilot that pulls data straight from filings and earnings decks into ready-to-use models. It runs on a paid pricing model with pricing available only by contacting the company directly.

The core strength is source-linked data: every number in a model traces back to the filing or presentation it came from, so an analyst can verify a figure in seconds instead of hunting through a 10-K. Daloopa automates the model-building and refresh process itself, updating figures as new filings land rather than forcing an analyst to redo the work each quarter. That combination reduces the manual errors that creep in when someone copies numbers by hand under a deadline, which matters when a single bad input can throw off an entire valuation.

The honest limitation is who this is built for. Daloopa is built for professionals, not casual investors doing light research on the side, and the learning curve reflects that. Pricing is not public either, so there is no way to gauge cost without contacting sales directly, which adds friction for anyone just comparing options before committing time to a demo.

Daloopa covers US and global stocks and fits long-term investing at an advanced skill level, running semi-automated so an analyst still drives the process while the platform handles the data extraction. It offers API access for teams that want to pull data into their own systems, though there is no mobile app and no free trial, so testing means committing to a sales conversation first. Retail investors who do not build financial models should skip this one entirely. Analysts drowning in manual data entry are exactly who it is built for.

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