DataLang

DataLang is a versatile and user-friendly platform designed to empower businesses and individuals to build custom AI chatbots trained on their unique data. It bridges the gap between complex datasets and accessible, conversational interfaces. By connecting to a wide array of data sources, DataLang allows you to unlock the value hidden within your information, making it interactive and queryable through natural language.

The platform supports an extensive list of data sources, including various SQL databases (PostgreSQL, MySQL, SQL Server, MariaDB, Oracle, Amazon Redshift, SQLite, Snowflake), files (like CSVs or text documents), popular productivity tools (Notion, Google Sheets), and even content from websites or other platforms like HubSpot. This flexibility ensures that no matter where your data resides, you can leverage it to create a knowledgeable chatbot.

How to use DataLang

DataLang simplifies the chatbot creation process into four straightforward steps, making it accessible even for users without a technical background:

1. Set up your Data Source: The first step is to connect DataLang to your data. You can configure connections to your databases, upload files, or link to services like Notion or Google Sheets. The platform provides a secure way to establish these connections.
2. Add a Data View: To ensure security and control, you don't expose your entire database. Instead, you create a 'Data View'. This is essentially a specific query or a defined subset of your data (e.g., 'SELECT * FROM Sales WHERE customer = X') that the chatbot will be allowed to access. This feature is crucial for controlling data privacy and relevance.
3. Chat with your data: Once your data views are configured, you can select which ones to use for training your chatbot. DataLang uses this curated information to train a GPT model, enabling it to understand and answer questions based solely on the data you've provided.
4. Share it!: After your chatbot is trained and tested, DataLang offers multiple deployment options. You can share it with a simple public URL, embed it as a widget directly onto your website for customer interaction, publish it as a custom GPT in the official GPT Store, or integrate it into other applications using its API.

Core Features of DataLang

• Multi-Source Connectivity: Connect to a vast range of data sources including SQL databases, files, Notion, Google Sheets, HubSpot, and websites.
• Custom GPT Publishing: Easily package and publish your data-powered chatbot to the ChatGPT Store, making it accessible to a wider audience or your customers.
• Flexible Deployment: Share your chatbot through a public link, embeddable website widget, or a powerful API for custom integrations.
• Granular Data Control: Use 'Data Views' to precisely define which data the AI can access, ensuring security and context-accuracy.
• Database to API: A unique feature that allows you to expose data from your database as a secure API endpoint, which can then be consumed by your custom GPT or other applications.
• No-Code/Low-Code Interface: The entire process is designed to be intuitive, allowing users of all skill levels to build powerful chatbots without writing extensive code.
• Self-Hosting for Enterprises: For organizations with strict data privacy requirements, DataLang offers a self-hosted option, allowing you to run the platform on your own infrastructure.

Use Cases for DataLang

DataLang can be applied in numerous scenarios to enhance efficiency and engagement:

• Internal Knowledge Base: Create a chatbot for employees to ask questions about company policies, project data stored in Notion, or sales figures from a SQL database.
• Enhanced Customer Support: Build a support bot trained on your product documentation and FAQs to provide instant, 24/7 assistance to your customers.
• Personalized Client Services: For SaaS companies, create a unique, secure GPT for each major client, trained on their specific usage data and reports.
• Interactive Data Analysis: Enable marketing or sales teams to query performance data using natural language instead of needing a data analyst to run reports.
• Lead Generation: Embed a chatbot on your website to engage visitors, answer their questions about your services, and qualify leads.

Advantages of DataLang

DataLang offers significant advantages by transforming static data into a dynamic asset. It democratizes data access, allowing non-technical team members to gain insights without needing to learn complex query languages. This saves time, reduces the burden on technical teams, and empowers faster decision-making. The high level of customization and security through 'Data Views' ensures that you maintain full control over your information. Its scalability, from a free plan to an enterprise-level self-hosted solution, makes it suitable for projects of any size.

Pricing and Plans

DataLang offers a tiered pricing model to suit different needs:

• Free: $0/month. Includes 1 user, 1 data source, and 100 credits. Ideal for creating a simple chatbot.
• Basic: $19/month. Includes 2 users, 10 data sources, and 1,000 credits/month. Suited for individual users or small projects.
• Pro: $49/month. The recommended plan, it includes 6 users, 50 data sources, 3,000 credits/month, and basic support. Designed for small teams.
• Business: $399/month. For large teams, it offers 12 users, 1,000 data sources, 20,000 credits/month, and priority support.
• Self-hosted: Starting at $20,000/year. Deploy DataLang on your own infrastructure with unlimited users, data sources, and credits. Includes an account manager and yearly updates.

Yearly subscriptions offer a 17% discount.