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Reportify

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Pesquisa de investimentos com IA sobre relatórios, earnings calls, ações e tendências de mercado na China, em Hong Kong e nos EUA

O que é Reportify?

Reportify is an AI platform for investment research. The site positions it as a tool for working with company filings, earnings calls, stock data, and market trends across China, Hong Kong, and the US.

The product centers on a Reportify Agent that accepts questions or tasks and appears to support several research workflows, including document search, quantitative screening, table generation, and scheduled market reviews. The site also exposes skills and agents, which suggests users can adapt the workspace to different research needs.

O que Reportify pode fazer?

Agent-based research workflows

Users can input a question or assign a task to the Reportify Agent, which is positioned as the main interface for investment research workflows.

Skills and custom agent creation

The homepage highlights skills such as Investment Analysis, Quant Analysis, and Document Search, and also shows options to create custom skills and agents.

Structured research outputs

Example workflows include comparison tables, stock screening rules, and scheduled market-review tasks, indicating support for structured analysis and recurring monitoring.

Multi-source research context

The navigation and page content reference reports, filings, news, socials, memory, help, financials, and transcripts, suggesting a research environment centered on market and company information.

Credit-based plan structure

The pricing page describes monthly credits, available models, agent executions, and OpenClaw conversations, showing a usage-based product model with tiered allowances.

Casos de uso

“Ad hoc investment research”

Ask research questions about companies, management commentary, or market themes and use the agent to pull together answers from supported financial materials.

“Structured analysis and reporting”

Build comparison tables or analysis summaries from company data, such as operating cash flow or capex guidance, when a repeatable format is needed.

“Quantitative screening”

Create screening rules like moving-average or momentum filters to narrow a market universe and produce a watchlist or exportable result.

“Recurring monitoring”

Set scheduled tasks to generate recurring market reviews and forecasts so research arrives on a regular cadence.

“Document search and retrieval”

Search reports and documents when the task is to locate specific statements, sections, or reference material inside a larger research set.

Perguntas frequentes

What is Reportify used for?

Reportify is presented as an AI platform for investment research. It helps users work with filings, earnings calls, stock data, and market trends across companies in China, Hong Kong, and the US.

What kinds of research tasks can it support?

The site shows product workflows such as asking questions in chat, creating tables, screening A-shares, and setting scheduled market-review tasks. Those examples suggest it is built for research and analysis workflows rather than a single fixed report template.

How does Reportify pricing work?

The pricing page shows plans with monthly credits, agent executions, and OpenClaw conversations. It also states that newer plans should not be directly compared with legacy plans.

Does Reportify list integrations?

The product pages do not provide detailed integration documentation in the collected text. The available evidence confirms a web-based product with agents, skills, reports, and document search, but not specific third-party integrations.

Informações rápidas

Category
AI platform for investment research
Primary markets
China, Hong Kong, and the US
Main interface
Reportify Agent
Pricing model
Tiered subscription plans with monthly credits
Source domain
reportify.cc

Análise de tráfego de Reportify

Os dados de tráfego são apenas para referência.

Visitas mensais
0
Classificação global
-
Taxa de rejeição
0.00%
Duração média da visita
00:00
Páginas por visita
0.00
Classificação do domínio
11

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