Tame your Gigantic Database
Description: This video shows how C-Phrase can be used to interactively refine and explore vast and complex remote databases within a single small virtual machine.
In this video, you’ll see:
- Using C-Phrase to download and shape a fragment of the giant remote database Crunchbase.
- Querying large relational databases using plain English.
- A clean, user-friendly interface for non-technical users.
Ideal for analysts, decision-makers, and product teams working with very large and complex databases.
C-Phrase compared to Chat-GPT over a simple geography database
Description: This video presents a side-by-side comparison of C-Phrase and ChatGPT for handling natural language queries over a simple geography database. It demonstrates how each system interprets user questions and generates SQL, highlighting differences in accuracy, control, and user experience.
In this demo, you’ll see:
- Natural language queries like "Show all cities in California" or "What is the population of New York?"
- How ChatGPT and C-Phrase translate those queries into SQL
- Strengths of domain-specific tools like C-Phrase versus general LLMs
This comparison illustrates why purpose-built systems like C-Phrase can offer more predictable, accurate, and secure data access — especially in structured environments.
C-Phrase compared to Chat-GPT over a simple data warehouse
Description: This video compares C-Phrase and ChatGPT in executing natural language queries against the simple TICKET data warehouse. While ChatGPT demonstrates flexibility as a general-purpose language model, C-Phrase stands out with its accuracy, schema awareness, and enterprise-ready control.
In this demo, you’ll see:
- Natural language to SQL for analytic type questions
- Differences in how each system handles ambiguity and data constraints
- Why domain-specific tools like C-Phrase outperform general LLMs in real-world data environments
Whether you're building internal data tools or evaluating AI for enterprise analytics, this demo shows the trade-offs between a general LLM like ChatGPT and a focused, domain specific approach like C-Phrase. In short, C-Phrase is ready while GPT-based approaches are not.
Using C-Phrase and Chat-GPT to build a database (method-1)
Description: This video demonstrates Method 1 for building an SQL database using a combination of ChatGPT and C-Phrase. It walks through the process of generating a schema from natural language descriptions and importing it into C-Phrase to enable intelligent querying.
In this demo, you’ll see:
- Using ChatGPT to generate SQL
CREATE TABLEstatements from natural language. - Loading the generated schema into C-Phrase’s Admin Interface.
- Enabling natural language access over the newly created database.
- Accelerating database synthesis using AI + our batch loader tool.
This approach is ideal for developers, data teams, and startups looking to rapidly generate structured databases and enable intuitive, no-code access to them using natural language.
Using C-Phrase and Chat-GPT to build a database (method-2)
Description: This follow-up video demonstrates Method 2 for building an SQL database using ChatGPT in combination with C-Phrase. Unlike Method 1, which starts with ChatGPT generating SQL schema, this approach begins with C-Phrase’s Admin Interface to define the structure, then uses ChatGPT to populate and test the database more efficiently.
In this demo, you’ll see:
- Creating and managing a database schema directly in C-Phrase.
- Using ChatGPT to assist in generating sample data and queries.
- Testing natural language access immediately after setup.
- How the two tools complement each other for rapid development and validation of databases.
This method is ideal for teams looking for more control during schema creation while still leveraging AI to accelerate content generation and early testing.
Importing spreadsheets into C-Phrase
Description: This video demonstrates how you can import data from spreadsheet platforms like Google Sheets, Excel, and Airtable directly into C-Phrase, enabling natural language access over your own structured data.
In this demo, you’ll see:
- Importing spreadsheets into C-Phrase’s Admin Interface.
- Auto-detection of table structure and data types.
- Enabling instant natural language querying over imported data.
- Support for business users who rely on spreadsheets as primary data sources.
Turn your everyday spreadsheets into powerful, searchable databases — no SQL or technical setup required.
Using C-Phrase to access CrunchBase
Description: This video showcases how C-Phrase can be used as a natural language interface to explore and query the CrunchBase database. Instead of writing complex SQL or browsing through filters, users can simply type their questions in plain English and get instant, accurate answers.
In this demo, you’ll see:
- Connecting C-Phrase to CrunchBase data.
- Executing natural language queries like "List all AI startups founded after 2020" or "Who are the top investors in fintech?".
- Automatic translation of questions into SQL with immediate results.
- Making complex datasets accessible for business teams, researchers, and analysts.
Unlock insights from CrunchBase quickly and intuitively with the power of natural language and C-Phrase.
C-Phrase applied to e-commerce
Description: This video demonstrates how C-Phrase can be applied to an e-commerce database to enable natural language queries over products, orders, customers, and sales. It shows how business and non-technical teams can ask complex questions in plain English and receive immediate, SQL-driven answers.
- Querying sales and inventory data using natural language.
- Examples like “Which products had the highest revenue last month?” or “List all customers who bought more than 3 items.”
- Real-time SQL generation and response from relational data.
- Ideal for e-commerce managers, analysts, and operations teams looking for quick insights without technical overhead.
C-Phrase brings intuitive, self-service analytics to your e-commerce data — without writing a single line of SQL.
Applying C-Phrase to personal consumption tracking
Description: This video demonstrates how C-Phrase can be used to track and query personal consumption data, including carbon footprint metrics. By integrating natural language capabilities with a consumption database, users can easily monitor their habits and understand environmental impact through plain English questions.
In this demo, you’ll see:
- Tracking daily, weekly, and monthly carbon output.
- Query examples like “What was my highest carbon activity last week?” or “Show my emissions by category.”
- Visualization-ready SQL responses for carbon reporting dashboards.
- Ideal for individuals, sustainability-focused apps, and researchers monitoring eco-impact through behavior data.
With C-Phrase, personal sustainability tracking becomes transparent, actionable, and user-friendly — no SQL required.
Appling C-Phrase to personal information management
Description: This video highlights how C-Phrase can be applied to Personal Information Management (PIM) — helping users organize, query, and retrieve personal data using natural language. Whether it’s tasks, notes, contacts, or schedules, C-Phrase enables intuitive access to structured personal information without writing SQL.
In this demo, you’ll see:
- Managing personal records like tasks, reminders, and contacts.
- Query examples such as “What tasks are due next week?” or “Show contacts added this month.”
- Instant translation of natural language into precise SQL queries.
- Ideal for productivity tools, knowledge workers, and custom PIM apps.
Bring clarity and control to your personal data with the power of natural language and C-Phrase.
Launching C-Phrase on AWS
Description: This video provides a step-by-step walkthrough for launching a free trial of C-Phrase on AWS. It guides you through setting up the cloud instance, deploying the C-Phrase server, and accessing the natural language interface for querying your database.
In this demo, you’ll see:
- How to launch C-Phrase from the AWS Marketplace.
- Configuring the instance and accessing the admin dashboard.
- Connecting to a sample database and running natural language queries.
- Tips for getting started with your own data and exploring the platform.
If you're evaluating C-Phrase or need an easy cloud-based setup, this tutorial will help you get up and running on AWS in minutes.
C-Phrase's SQL coverage
Description: This video highlights the broad SQL coverage of C-Phrase, showcasing how the system handles a wide variety of natural language queries with precise and accurate SQL translations. From simple lookups to complex joins and aggregations, C-Phrase delivers powerful, flexible query capabilities to both technical and non-technical users.
In this demo, you’ll see:
- Support for SELECT queries with filters, sorting, and pagination.
- Joins across multiple related tables using natural language.
- Aggregations like SUM, COUNT, AVG, and GROUP BY.
- Handling of constraints, aliases, and nested queries.
- Real-time query generation and execution across supported databases.
Whether you're analyzing customer behavior, generating business reports, or querying complex schemas — C-Phrase covers it with ease and clarity.
C-Phrase in the metaverse
Description: This video explores how C-Phrase can be applied in the context of the metaverse, enabling users to interact with virtual worlds through natural language database queries. It illustrates how immersive digital environments can be powered by real-time access to structured data using plain English.
In this demo, you’ll see:
- Natural language interfaces integrated into metaverse applications.
- Querying virtual world data like locations, avatars, assets, and interactions.
- Live SQL generation for dynamic content updates and analytics.
- Demonstrating the fusion of AI-driven language tools with immersive technology.
See how C-Phrase brings data intelligence to the metaverse — making complex queries as easy as conversation.