Seek AIの利用シーンは何ですか？

Seek AIを使用するには、プラットフォームにサインアップしてログインするだけです。そこから、クエリを入力するとAIパワーのシステムが従来のデータツールよりも短時間で正確な結果を生成します。使いやすく直感的なインターフェースで、ビジネスユーザーとデータチームの両方がデータ分析のニーズに合わせて生成力のあるAIの力を活用することができます。

Seek AIのコア機能

生成力のあるAIを活用したデータベースクエリ

シンプルで正確なデータ分析

安全なデータ処理とプライバシー

ビジネス分析を近代化

大量のデータセットへの迅速で効率的なアクセス

Seek AIの使用例

データの探索と分析

ビジネスインテリジェンスとレポート作成

市場調査とトレンド分析

顧客の行動分析

パフォーマンスの追跡と最適化

Seek AIのFAQ

Seek AIとは何ですか？
Seek AIの使い方は？
Seek AIの主な機能は何ですか？
Seek AIの利用シーンは何ですか？

Seek AI サポートメール、カスタマーサービス連絡先、返金連絡先など

さらに連絡するには、お問い合わせページ (https://www.seek.ai/contact-us) にアクセスしてください。
Seek AI 会社

Seek AI 会社名: Seek AI Inc. 。

Seek AI について詳しくは、会社概要ページ (https://www.seek.ai/mission) をご覧ください。。
Seek AI のLinkedin

Seek AI Linkedinリンク: https://www.linkedin.com/company/seekai
Seek AI のTwitter

Seek AI Twitterリンク: https://twitter.com/ai_seek

Seek AI レビュー (0)

5 点中 5 点

Seek AI の分析

Seek AI ウェブサイトのトラフィック分析

地理的なトラフィック

上位5地域

United States

17.04%

Mexico

6.55%

Brazil

5.66%

Russia

5.27%

India

4.40%

Dec 2022 - Mar 2025 デスクトップ端末のみ

ウェブサイトのトラフィックソース

オーガニック検索

43.99%

ダイレクト

37.24%

リファーラル

13.42%

ソーシャル

4.80%

ディスプレイ広告

0.47%

メール

0.08%

Dec 2022 - Mar 2025 グローバルデスクトップデバイスのみ

ソーシャルリスニング

All

YouTube

Tiktok

検索履歴

1:01:12

Automating Analytics with Generative AI w/ Sarah Nagy

Sarah Nagy (CEO, Seek.ai) joins us to chat about automating analytics with generative AI, the generative AI space in general, and much more.

Ternary Data

11月 28 2023

554

https://www.youtube.com/watch?v=SKvlfOzLpJA

43:00

Powering your Copilot for Data - with Artem Keydunov from Cube.dev

Text-to-SQL was one of the first applications of NLP. Thoughtspot offered “Ask your data questions” as their core differentiation compared to traditional dashboarding tools. Today, natural language queries on your databases are a commodity. There are 4 different ChatGPT plugins that offer this, as well as a bunch of startups like one of our previous guests, Seek.ai. Perplexity originally started with a similar product in 2022. Artem Keydunov from Cube.dev came on the podcast to talk about what the semantic layer is, and how it can work as the equivalent of RLHF for models to make it easy to build reliable data experiences with AI. 00:00:00 - Introductions 00:01:35 - History of Statsbot - Slack bot for querying data in Slack 00:04:45 - Building Cube to power Statsbot due to limitations in natural language processing at the time 00:06:50 - Open sourcing Cube as a standalone product 00:08:34 - Explaining the concept of a semantic layer and OLAP cubes 00:10:27 - Using semantic layers to provide context to AI models 00:11:54 - Challenges of using tabular vs. language data with AI models 00:13:11 - Workflow of natural language to SQL query using semantic layer 00:16:01 - Ensuring AI agents have proper data context and make correct queries 00:18:20 - Treating metrics definitions in the semantic layer as a codebase with collaboration 00:22:55 - Natural language capabilities becoming a commodity baseline for BI tools 00:24:37 - Recommendations for building data-driven AI applications 00:28:26 - Predictions on the consolidation of modern data stack tools/companies 00:30:14 - AI assistance augmenting but not fully automating data workflows 00:34:20 - Using external Python scripts to handle limitations of models with math 00:36:15 - Embedded analytics challenges and natural language commoditization 00:39:04 - Lightning round

Latent Space

10月 27 2023

439

https://www.youtube.com/watch?v=v8r-bpQmfac

30:15

ShiftAI | Real-Time Chat with your Data with Seek AI CEO Sarah Nagy

In this episode of the Shift AI podcast, host Boaz Ashkenazy interviews Sarah Nagy, CEO of Seek AI (http://seek.ai/), discussing her journey from astrophysics and finance to leading one of the fastest-growing AI companies. Sarah shares insights into her transition from quantitative analysis and data science in finance to creating Seek AI, which aims to make data more accessible to non-technical users through natural language interfaces. She highlights the significance of large language models in facilitating this transition and elaborates on Seek's achievements, including surpassing a major benchmark in natural language to SQL translation. Summary of topics covered: - **Introduction to Sarah Nagy**: The podcast begins with an introduction to Sarah Nagy, highlighting her past work in the financial sector and her transition to the AI industry, leading up to her role as CEO of Seek.ai. - **Background in Finance and Astrophysics**: Sarah shares her journey from working in astrophysics and quantitative finance to her growing interest in big data and machine learning, eventually leading data teams at startups and at Citadel. - **Founding of Seek.ai**: Frustrated with the challenges non-technical people face in accessing and understanding data, Sarah discusses how her experiences led to the founding of Seek.ai, aiming to make data accessible through a natural language interface. - **Large Language Models and Code Generation**: Sarah elaborates on the potential of large language models for code generation and their application in making data queries accessible to non-technical users, underpinning the technology behind Seek.ai. - **Seek.ai's Mission and Technology**: The discussion delves into Seek.ai's mission to enable business professionals to ask data-related questions in natural language, highlighting the company's use of analytical AI to process these queries efficiently. - **Challenges of Transitioning to AI from Finance**: Sarah reflects on the transition from working deeply with data in finance to leading an AI startup, discussing the challenges and opportunities this shift presented. - **Mentorship and Influence**: The conversation shifts to Sarah's early influences, including her family's background in tech and her mentors throughout her career, emphasizing the role of mentorship in her professional development. - **The Future of AI and Work**: Sarah offers her perspective on the evolving AI landscape, the excitement around large language models, and their implications for the future of work, including the potential for everyone to leverage AI for decision-making. - **Seek.ai's Achievements and Benchmarks**: Sarah shares recent accomplishments of Seek.ai, including their performance on the Spider benchmark for natural language to SQL translation, highlighting the company's leadership in the field. - **Vision for Seek.ai and the Industry**: The podcast concludes with Sarah's vision for the future of Seek.ai and the broader AI industry, touching on the opportunities for innovation and the importance of making AI accessible to a wider audience. ### Connect with Sarah Nagy - Twitter/X - (https://twitter.com/sarahrnagy) - LinkedIn⁠ - (https://www.linkedin.com/in/sarah-nagy) Connect with Boaz Ashkenazy - Twitter⁠ - (https://twitter.com/boazashkenazy) - ⁠LinkedIn⁠ - (https://www.linkedin.com/in/boazashkenazy) - Email: shift@simplyaugmented.com

Shift AI

3月 03 2024

100

https://www.youtube.com/watch?v=m1guADTx4cg