How do you connect the Hermes Agent production tool? Let's start with read-only permissions
When Hermes Agent needs to connect to production databases, cloud accounts, ticketing systems, or co
Horizon is an AI tool that builds, backtests, and automates trading strategies in natural language. It allows users to describe stocks, crypto assets, or forex strategies in plain language, with backtesting and automated trading exploration. It is suitable for quantitative trading learners, trading strategy researchers, and investment users who want to test their strategies in low-code, as well as for validation and organization in trading strategy building, historical backtesting, strategy automation, stock and crypto market research. Before using it, you need to note that backtesting does not represent future returns, and automated trading risks are high, so AI strategies should not be used as investment advice, especially boundaries such as data sources, material authorization, result review, account permissions, or payment limits. It is suitable for strategy research and learning, and risks should be strictly controlled before real trading.
Before actually choosing Horizon, users need to determine what kind of task it solves: describing and testing trading strategy ideas in natural language. It is suitable as a work aid with clear boundaries, not as a substitute for all human judgment; The clearer the input content, business constraints, and review process, the easier it is for the results to be translated into real-world scenarios.
Horizon's core capabilities focus on AI trading strategy generation, backtesting, automated trading, stock crypto, and forex strategy research. These tools are better suited for processing duplicates, first draft generation, candidates, or initial evaluations, and then allowing users to continue filtering and correcting.
It is suitable for strategy prototyping, trading learning, backtesting and comparison, and automated trading experiments. If you are an individual user, you can use it to reduce trial and error from scratch; If it is used by a team, it is more suitable as a precursor to the existing process, so that subsequent review, communication or delivery is more reliable.
People who understand market risk and can assess backtesting bias are more suitable. Teams with budget, compliance, brand consistency, or business risk requirements need to confirm permissions, templates, export methods, and manual review mechanisms.
It does not guarantee profitability and should not be a subs服装re for licensed investment advisors or trading risk management. When it comes to medical, recruitment, financial, legal, portrait, personal data, investment judgments, or third-party materials, it is recommended to use only the content that you have the right to process, and to manually confirm it before making a formal decision or publishing it.
Can Horizon's backtesting prove that the strategy is making money? **
No, I can't. Backtesting can only tell the historical performance, and the market may be completely different in the future.
Can I trade automatically? **
It involves automated trading capabilities, but it is essential to understand the risks, money management, and platform rules before enabling it.
Is it suitable for beginners? **
It is suitable for learning strategy logic, but newbies should not invest a lot of money directly.
ToolSpend is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.
TickerTrends is an AI tool for users who need a clearer way to handle focused digital work. It can support creation, automation, analysis, learning, media production, development, research, customer operations, or document workflows depending on the product scope. Start with a small low-risk task, compare the result with your own standards, and keep human review for facts, permissions, privacy, brand voice, safety, and final delivery.
TheAnalystAI is an AI tool for users who need a clearer way to handle focused digital work. It can support creation, automation, analysis, learning, media production, development, research, customer operations, or document workflows depending on the product scope. Start with a small low-risk task, compare the result with your own standards, and keep human review for facts, permissions, privacy, brand voice, safety, and final delivery.
Tendi is an AI tool for users who need a clearer way to handle focused digital work. It can support creation, automation, analysis, learning, media production, development, research, customer operations, or document workflows depending on the product scope. Start with a small low-risk task, compare the result with your own standards, and keep human review for facts, permissions, privacy, brand voice, safety, and final delivery.
Tabby is a practical AI tool for teams and individual users who need a clearer way to handle focused digital tasks. It can support content work, document handling, automation, learning, communication, media production, research, or customer workflows depending on the product scope. Users should start with a small low-risk task, compare the output with their own standards, and keep human review for facts, permissions, privacy, brand voice, and final delivery.
Syft Analytics helps users turn clear source material into editable results for content, media, data, learning, or operational workflows. It is best used when the goal, input, output format, and review standard are clear. Users should test it with a low-risk task first and keep human review for customer data, student work, financial information, portraits, production code, or public content.
OtterQuant is an AI financial market intelligence and natural language screening tool that is mainly used to integrate real-time reports, Reddit tracking, earnings conference call minutes, Congressman transaction disclosures, news, natural language screening and market data. It is suitable for individual investors, researchers, trading learners and people who need to track U.S. stock information. Common uses include quickly understanding recent information about a stock, proposing filtering conditions in natural language, and compiling portfolio related data into reports. Be aware when using it, it provides research assistance and does not constitute investment advice. Market data may be delayed, and risks, prices and personal affordability should be checked by yourself before trading. The free plan includes core market data and weekly AI usage quotas, and Pro is approximately US$16.99 per month. It is recommended to use one or two low-risk tasks to test input materials, output quality, manual modification amount and final adoption ratio before deciding whether to put them into a fixed process.
OLY.AI is an AI financial analysis and QuickBooks insight tool that is mainly used to transform QuickBooks and document data into real-time financial insight and prediction scenarios. It is suitable for bookkeepers, small business owners, operations teams and financial advisers. It can connect to QuickBooks Online for financial analysis, budget generation, forecasts and scenario planning clues, and can also help teams understand financial status faster. When using it, note that financial insights need to be reviewed by accountants or responsible persons and cannot be a substitute for audits, tax returns or investment advice. It is recommended to use one or two low-risk tasks to test input materials, output quality, manual modification amount and final adoption ratio before deciding whether to put them into a fixed process.
Offset is an AI financial model and file data extraction tool, mainly used to extract data from financial documents and quickly build financial models. It is suitable for investment analysts, financial teams, corporate strategists and researchers. It can quickly build financial models, extract accurate data from filing documents, and support local deployment to protect privacy. When using it, it should be noted that the results of the financial model require professional review and cannot be directly used as investment, financing or audit conclusions. It is recommended that one or two low-risk tasks be used to test input materials, output quality, manual modifications, and final adoption ratios before deciding whether to put them into a fixed process and document whether they are suitable for long-term use and team review.
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