Write Natural Language Queries Instead of SQL

Gather data from multiple sources, enrich it with useful metadata, and make it easily accessible and queryable by a broad range of users, regardless of their technical expertise.

Step 1

Gather Data from Multiple Sources

From bulk data integration for ETL to custom workflow automation for business processes, tools like Airbyte and n8n ensure that data from various sources are collected consistently and efficiently.

Step 2

Take Control of your Data

Makes data more discoverable and understandable with DataHub by enriching your data with metadata, by helping users understand where your data came from, what they mean, and what their relationship is to the rest of your data assets.

Step 3

Discover and Query the Data with Natural Language

Queries in natural language are first used to look up relevant tables and columns. Then, a SQL query is auto-generated to answer the query. Describe your data objective in natural language and let Shakudo do the rest.

Why on Shakudo

Simple, Fast, and Powerful

Shakudo offers the fastest way to self-serve the best-in-class LLM systems and vector databases. Set up and start using your data and AI stack components in minutes.

Security and Production-Ready Endpoints

Shakudo keeps your data secure and inside your existing infrastructure — your data will not be used in any form.

Efficient Data Processing Pipeline and Tools for Real-Time Data Ingestion

Shakudo pipeline jobs use best-in-class stack components to keep your vector databases refreshed.

Language to SQL Is Only One Piece of the Puzzle

Growth-Ready Infrastructure

Scale

  • Ensures compatibility with expanding operations through Kubernetes-based scalability.
  • Maintains performance stability during high demand as your company grows.
  • Accommodates increasing workload volumes through flexible resource management.

Comprehensive Tooling 

Complete

  • Integrates with over 116 pre-configured data stack components for diverse business needs.
  • Automates cloud infrastructure setup and maintenance, simplifying data scientists' workflow.
  • Delivers pre-built patterns for common ML tasks, streamlining development and deployment processes.

Streamlined Operations 

Efficiency

  • Enables quick access to GPUs for faster ML model training.
  • Provides an intuitive single pane UI, making advanced data science tasks more accessible.
  • Facilitates seamless collaboration and consistent environments, cutting down on project timelines.

Get Started with Language to SQL on Shakudo

Chat with one of our experts to answer your questions about your data stack, data tools you need, and deploying Shakudo on your cloud.
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Language to SQL FAQs

Frequently Asked Questions

What range of models are available on Shakudo?

Shakudo supports an extensive array of models, including top commercial options like those from OpenAI and Cohere, as well as a variety of open source alternatives. For a detailed list of supported models, visit our integrations page.

Can Shakudo integrate with my existing data systems?

Yes, Shakudo is designed to be highly compatible with existing data systems. With its numerous pre-configured data stack components, it can easily be integrated into your current workflows to enhance data processing and machine learning capabilities.

How can I ensure my data remains secure while using Shakudo?

Security is a top priority at Shakudo. Your data belongs on your cloud — that’s why Shakudo can be easily deployed on any cloud or your on-prem infrastructure.

What kind of support can I expect from Shakudo?

Shakudo offers robust support options including a comprehensive knowledge base, 24/7/365 live support for critical issues, and dedicated account management to ensure you get the most out of the platform.

How quickly can I get started with deploying models on Shakudo?

You can get started almost immediately. Shakudo's user-friendly interface and extensive documentation mean that setting up and deploying your models can be done with minimal setup time.

Can Shakudo handle large-scale machine learning projects?

Yes, Shakudo is built for scale. Thanks to its underlying Kubernetes architecture and scalable components, it can handle large-scale machine learning projects with ease, providing the necessary resources as your project grows.