We’re excited to announce our new ?????????? ??????????????????????—bringing real-time data analysis right into your Slack channels and DMs. Check out our docs to learn more and see how you can add Ana to your Slack workspace: https://lnkd.in/eQdrsg_f
TextQL
数据基础架构与分析
San Francisco，California 1,172 位关注者
Building the Ontology for LLMs to talk to Data, accurately and securely.
关于我们
TextQL is a platform that simplifies the data-to-insight process for organizations. The platform indexes BI tools and semantic layers, documents data in dbt, and uses OpenAI and language models to provide self-serve power analytics. With TextQL, non-technical users can easily and quickly work with data by asking questions in their work context (Slack/Teams/email) and getting automated answers quickly and safely. The platform also leverages NLP and semantic layers, including the dbt Labs semantic layer, to ensure reasonable solutions. TextQL's elegant handoffs to human analysts, when required, dramatically simplify the whole question-to-answer process with AI. Reach out to learn more: calendly.com/ethanding
- 网站
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textql.com
TextQL的外部链接
- 所属行业
- 数据基础架构与分析
- 规模
- 11-50 人
- 总部
- San Francisco，California
- 类型
- 私人持股
地点
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主要
获取路线
US，California，San Francisco
TextQL员工
动态
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AI agents are transforming industries, and retail is no exception. This weekend, TextQL will be at the NRF 2025: Retail's Big Show to showcase how our technology helps retailers uncover deep insights that drive buisiness outcomes. From inventory optimization to personalized customer experiences, our AI agents integrate seamlessly with your existing tools to deliver actionable insights and drive measurable results. Check out our dedicated NRF page to learn more about our solutions: nrf.textql.com. If you're attending NRF, let's talk about AI-powered retail! #NRF2025 #AIinRetail #RetailInnovation
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these best practices seem really simple if you’re heads-down in ai and using it everyday. but the truth is we’re still in the first out of the first inning in the adoption of ai products. for most people, working with ai agents is still a very new thing and definitely requires training and onboarding. whenever we onboard users to ana, our ai data scientist, we typically run workshops & office hours. these are some of the keys to success that have enabled our users to turbo-charge their productivity by 10x
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One of the best ways to get started with Ana is to treat her like a human data analyst that you’re collaborating with and ask her general questions about your data. Things like: - Give me an overview of my data - What type of analysis can I do? A common theme we keep hearing from data teams who have implemented TextQL is how they are reducing their back and forth between various teams and empowering users to perform their own exploratory data analysis.
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TextQL is proud to announce our corporate-friendly inclusion in the AI Hot 100 List by The AI Furnace ???? . We will attend The AI Hot 100 Conference in New York City on September 18th. We appreciate the assessment committee for identifying how mind-blowingly awesome we are and how we stand head and shoulders over any other product in the market. It's about time someone built a chat-with-your-data product, and we were surprised no one else was attempting it. #AIHot100 #AIConference #AIInnovation #Multimodal
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