{"id":987507501,"date":"2026-10-22T19:25:04","date_gmt":"2026-10-22T19:25:04","guid":{"rendered":"https:\/\/www.datamediq.com\/datamediq-ai-assistant\/"},"modified":"2026-11-05T13:55:35","modified_gmt":"2026-11-05T13:55:35","slug":"datamediq-ai-assistant","status":"publish","type":"page","link":"https:\/\/www.datamediq.com\/en\/datamediq-ai-assistant\/","title":{"rendered":"DatamedIQ – AI Assistant"},"content":{"rendered":"

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AI Assistant \u2013 Talk to Your Data<\/h1>\n

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From the Dashboard to the Dialog<\/h2>\n

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The brand-new AI Assistant brings artificial intelligence directly into the Insights Hub\u2014and thus right where your analysis takes place. It understands the current context of your analysis, takes into account selected KPIs, time periods, and filters, and makes your data accessible directly via voice commands. You ask a question, delve deeper into the results with follow-up questions, and work your way step by step toward the relevant connections.<\/p>\n

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Ask Questions Instead of Searching<\/h3>\n

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Do you see something unusual in your data? Just ask. The AI Assistant accesses the context of your current analysis directly. That means you don\u2019t have to explain which market, time period, or filters you\u2019re looking at every time. Instead, you can dive right in\u2014for example, with questions like:<\/p>\n

\n

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“Which brands are currently gaining market share?”<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font=”Panton Regular|600|||||||” text_text_color=”#053d4f” text_font_size=”18px” text_line_height=”1.3em” custom_margin_tablet=”||20px||false|false” custom_margin_phone=”||20px||false|false” custom_margin_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n

“What stands out most about this trend?”<\/p>\n

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“Which products are driving growth?”<\/p>\n

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“Are there regions that are developing in significantly different ways?”<\/p>\n

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Right in your DatamedIQ modules<\/h2>\n

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The AI Assistant is integrated into the Insights Hub\u2019s Premium modules and complements the existing analytics features right where you\u2019re already working. This creates an additional layer of analysis\u2014based directly on your available DatamedIQ data:<\/p>\n

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OTC Insights<\/h3>\n

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Analyze markets, brands, products, and competitors.<\/p>\n

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POS Insights<\/h3>\n

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Analyze performance at the digital point of sale.<\/p>\n

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OTC Maps<\/h3>\n

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Identify and compare regional trends.<\/p>\n

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Persona Insights<\/h3>\n

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Analyze shopper profiles and relevant target audiences.<\/p>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.27.4″ _module_preset=”default” da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row _builder_version=”4.20.4″ _module_preset=”default” background_enable_color=”off” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.20.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” max_width=”800px” module_alignment=”center” custom_margin=”0px||10px||false|false” custom_margin_tablet=”||10px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|desktop” custom_padding=”0px||0px||false|false” header_2_font_size_tablet=”42px” header_2_font_size_phone=”36px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

Users especially appreciate…<\/h2>\n

[\/et_pb_text][et_pb_accordion open_toggle_text_color=”#053d4f” open_toggle_background_color=”#ffffff” closed_toggle_text_color=”#053d4f” closed_toggle_background_color=”#FFFFFF” toggle_icon=”3||divi||400″ icon_color=”#c9c9c9″ use_icon_font_size=”on” icon_font_size=”26px” _builder_version=”4.27.4″ _module_preset=”default” toggle_text_color=”#053d4f” toggle_font=”Panton SemiBold||||||||” toggle_font_size=”18px” closed_toggle_font=”Panton SemiBold||||||||” closed_toggle_font_size=”18px” body_font=”Panton Regular||||||||” body_text_color=”#606060″ body_font_size=”18px” body_line_height=”1.5em” background_color=”RGBA(255,255,255,0)” custom_margin=”0px||50px||false|false” custom_margin_tablet=”0px||50px||false|false” custom_margin_phone=”||40px||false|false” custom_margin_last_edited=”on|phone” custom_padding=”20px|3%|20px|3%|false|false” hover_transition_duration=”0ms” border_width_all=”0px” border_width_bottom=”1px” global_colors_info=”{}”][et_pb_accordion_item title=”…that the context is already there.” open=”on” _builder_version=”4.27.4″ _module_preset=”default” background_color=”rgba(247,247,247,0)” background_enable_color=”on” custom_margin=”||10px||false|false” custom_padding=”||30px||false|false” hover_transition_duration=”50ms” global_colors_info=”{}” toggle_line_height=”1.3em”]<\/p>\n

One of the biggest advantages of the AI Assistant is that it doesn’t operate in isolation from your analysis.<\/p>\n

If you have already selected a specific market, KPI, time period, or filter, this context can be taken into account immediately.<\/p>\n

So you don’t have to write:<\/p>\n

“I am analyzing Product X in Market Y for the period from January through September \u2026”<\/p>\n

Instead, you can ask directly:<\/p>\n

“What stands out here?”<\/p>\n

or:<\/p>\n

“Which trend should I examine more closely?”<\/p>\n

This reduces the need for manual data entry and makes the analysis much more intuitive.<\/p>\n

[\/et_pb_accordion_item][et_pb_accordion_item title=”… that it’s more than just a chat.” _builder_version=”4.27.4″ _module_preset=”default” background_color=”rgba(247,247,247,0)” background_enable_color=”on” custom_margin=”||10px||false|false” custom_padding=”||30px||false|false” hover_transition_duration=”50ms” global_colors_info=”{}” toggle_line_height=”1.3em” open=”off”]<\/p>\n

The AI Assistant is not intended to be a traditional chatbot, but rather a part of your analytics workflow in the Insights Hub.<\/p>\n

Feel free to ask:<\/strong><\/p>\n

Simply phrase your questions in natural language. The AI Assistant will build on your current analysis and help you contextualize and explore the results in greater depth.<\/p>\n

Dig Deeper with Follow-Up Questions:<\/strong><\/p>\n

An analysis rarely yields a single answer.<\/p>\n

You can ask more questions right away:<\/p>\n

“Which competitors should I compare?”<\/p>\n

“Where is this effect particularly noticeable?”<\/p>\n

“Which products contribute the most to this trend?”<\/p>\n

“What do these brands have in common?”<\/p>\n

This is how a more in-depth analysis is developed step by step.<\/p>\n

[\/et_pb_accordion_item][et_pb_accordion_item title=”…that it makes recurring analyses easier.” _builder_version=”4.27.4″ _module_preset=”default” background_color=”rgba(247,247,247,0)” background_enable_color=”on” custom_margin=”||10px||false|false” custom_padding=”||30px||false|false” hover_transition_duration=”50ms” global_colors_info=”{}” toggle_line_height=”1.3em” open=”off”]<\/p>\n

Certain questions come up time and time again.<\/p>\n

With Custom Tasks, you can save frequently used prompts and run them again at any time.<\/p>\n

For example:<\/p>\n

Market Winners, Losers, and Newcomers<\/strong><\/p>\n

Create a brief overview of the selected market. Show which companies and products are gaining or losing market share and whether new competitors have entered the market.<\/p>\n

This allows you to perform recurring analyses more quickly and build them more consistently.<\/p>\n

[\/et_pb_accordion_item][et_pb_accordion_item title=”…you can choose the right AI model for every task.” _builder_version=”4.27.4″ _module_preset=”default” background_color=”rgba(247,247,247,0)” background_enable_color=”on” custom_margin=”||10px||false|false” custom_padding=”||30px||false|false” hover_transition_duration=”50ms” global_colors_info=”{}” toggle_line_height=”1.3em” open=”off”]<\/p>\n

Not every question is the same.<\/p>\n

Simple ad hoc questions require a different approach than more complex analyses. That\u2019s why AI Assistant lets you choose between different AI models.<\/p>\n

This way, you can decide for yourself which model is best suited for your specific task.<\/p>\n

[\/et_pb_accordion_item][et_pb_accordion_item title=”…that you can resume previous analyses at any time.” _builder_version=”4.27.4″ _module_preset=”default” background_color=”rgba(247,247,247,0)” background_enable_color=”on” custom_margin=”||10px||false|false” custom_padding=”||30px||false|false” hover_transition_duration=”50ms” global_colors_info=”{}” toggle_line_height=”1.3em” open=”off”]<\/p>\n

Your previous chats will be saved.<\/p>\n

This allows you to revisit previous discussions, review results, and continue your analysis later.<\/p>\n

This ensures that your analysis history remains available at all times, especially for long-term topics or recurring market observations.<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.27.4″ _module_preset=”default” da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row _builder_version=”4.16″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” max_width=”800px” module_alignment=”center” custom_margin=”0px||10px||false|false” custom_margin_tablet=”||10px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|desktop” custom_padding=”0px||0px||false|false” header_2_font_size_tablet=”42px” header_2_font_size_phone=”36px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

Your advantages at a glance<\/h2>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_icon font_icon=”||fa||400″ icon_color=”#053d4f” icon_width=”25px” _builder_version=”4.16″ _module_preset=”default” custom_margin=”||20px||false|false” global_colors_info=”{}”][\/et_pb_icon][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” header_3_font=”Panton SemiBold||||||||” header_3_text_color=”#053d4f” header_3_font_size=”24px” max_width=”500px” module_alignment=”center” custom_margin=”0px||15px||false|false” custom_margin_tablet=”||30px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|phone” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n

Fewer manual steps<\/h3>\n

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The current analysis context has already been taken into account.<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_icon font_icon=”||fa||400″ icon_color=”#053d4f” icon_width=”25px” _builder_version=”4.16″ _module_preset=”default” custom_margin=”||20px||false|false” global_colors_info=”{}”][\/et_pb_icon][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” header_3_font=”Panton SemiBold||||||||” header_3_text_color=”#053d4f” header_3_font_size=”24px” max_width=”500px” module_alignment=”center” custom_margin=”0px||15px||false|false” custom_margin_tablet=”||30px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|phone” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n

Faster Responses<\/h3>\n

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They ask directly, instead of having to work their way through several views.<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_icon font_icon=”||fa||400″ icon_color=”#053d4f” icon_width=”25px” _builder_version=”4.16″ _module_preset=”default” custom_margin=”||20px||false|false” global_colors_info=”{}”][\/et_pb_icon][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” header_3_font=”Panton SemiBold||||||||” header_3_text_color=”#053d4f” header_3_font_size=”24px” max_width=”500px” module_alignment=”center” custom_margin=”0px||15px||false|false” custom_margin_tablet=”||30px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|phone” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n

More Depth<\/h3>\n

[\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font=”Panton Regular||||||||” text_text_color=”#606060″ text_font_size=”18px” text_line_height=”1.3em” custom_margin_tablet=”||20px||false|false” custom_margin_phone=”||20px||false|false” custom_margin_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

Results can be examined in more detail, step by step, by asking follow-up questions.<\/p>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_icon font_icon=”||fa||400″ icon_color=”#053d4f” icon_width=”25px” _builder_version=”4.16″ _module_preset=”default” custom_margin=”||20px||false|false” global_colors_info=”{}”][\/et_pb_icon][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” header_3_font=”Panton SemiBold||||||||” header_3_text_color=”#053d4f” header_3_font_size=”24px” max_width=”500px” module_alignment=”center” custom_margin=”0px||15px||false|false” custom_margin_tablet=”||30px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|phone” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n

More Connections<\/h3>\n

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Different data sources can be viewed together.<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_icon font_icon=”||fa||400″ icon_color=”#053d4f” icon_width=”25px” _builder_version=”4.16″ _module_preset=”default” custom_margin=”||20px||false|false” global_colors_info=”{}”][\/et_pb_icon][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” header_3_font=”Panton SemiBold||||||||” header_3_text_color=”#053d4f” header_3_font_size=”24px” max_width=”500px” module_alignment=”center” custom_margin=”0px||15px||false|false” custom_margin_tablet=”||30px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|phone” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n

Simplifying Recurring Analyses<\/h3>\n

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Custom Tasks make frequently asked questions available at any time.<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_icon font_icon=”||fa||400″ icon_color=”#053d4f” icon_width=”25px” _builder_version=”4.16″ _module_preset=”default” custom_margin=”||20px||false|false” global_colors_info=”{}”][\/et_pb_icon][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” header_3_font=”Panton SemiBold||||||||” header_3_text_color=”#053d4f” header_3_font_size=”24px” max_width=”500px” module_alignment=”center” custom_margin=”0px||15px||false|false” custom_margin_tablet=”||30px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|phone” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n

Everything in one place<\/h3>\n

[\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font=”Panton Regular||||||||” text_text_color=”#606060″ text_font_size=”18px” text_line_height=”1.3em” custom_margin_tablet=”||20px||false|false” custom_margin_phone=”||20px||false|false” custom_margin_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

Data, analytics, and AI support remain directly within the Insights Hub.<\/p>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Section” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”||9px|||” da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row _builder_version=”4.16″ _module_preset=”default” max_width=”1750px” custom_margin=”0px||50px||false|false” custom_padding=”0px||0px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_2_font=”Panton SemiBold||||||||” header_2_text_align=”center” header_2_text_color=”#053d4f” header_2_font_size=”42px” header_2_line_height=”1.1em” max_width=”800px” module_alignment=”center” custom_margin=”0px||10px||false|false” custom_margin_tablet=”||10px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|desktop” custom_padding=”0px||0px||false|false” header_2_font_size_tablet=”42px” header_2_font_size_phone=”36px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

Connect data. Identify patterns.<\/h2>\n

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One of the AI Assistant\u2019s key benefits is its ability to analyze different data sources together. For example, it allows you to link visibility and digital shelf performance with actual sales data. This enables you to:<\/p>\n

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Identifying Correlations<\/h3>\n

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Examine potential performance drivers<\/h3>\n

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Viewing Different Data Sources Together<\/h3>\n

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Identify abnormalities more quickly<\/h3>\n

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Derive new starting points for further analysis<\/h3>\n

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Example: Twin Regions for A\/B Testing<\/h2>\n

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A use case in OTC Maps illustrates what this might look like in practice<\/p>\n

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The AI Assistant can be used to identify so-called “twin regions”\u2014that is, regions with market behavior that is as similar as possible.<\/p>\n

These can be used, for example, as test and control regions for A\/B tests.<\/p>\n

The AI Assistant takes the currently selected data and parameters into account and can:<\/p>\n

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