Best AI Development Platforms for SQL

Find and compare the best AI Development platforms for SQL in 2024

Use the comparison tool below to compare the top AI Development platforms for SQL on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

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    Google Cloud Vertex AI Workbench Reviews
    One development environment for all data science workflows. Natively analyze your data without the need to switch between services. Data to training at scale Models can be built and trained 5X faster than traditional notebooks. Scale up model development using simple connectivity to Vertex AI Services. Access to data is simplified and machine learning is made easier with BigQuery Dataproc, Spark and Vertex AI integration. Vertex AI training allows you to experiment and prototype at scale. Vertex AI Workbench allows you to manage your training and deployment workflows for Vertex AI all from one location. Fully managed, scalable and enterprise-ready, Jupyter-based, fully managed, scalable, and managed compute infrastructure with security controls. Easy connections to Google Cloud's Big Data Solutions allow you to explore data and train ML models.
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    Databricks Data Intelligence Platform Reviews
    The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.
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    LlamaIndex Reviews
    LlamaIndex, a "dataframework", is designed to help you create LLM apps. Connect semi-structured API data like Slack or Salesforce. LlamaIndex provides a flexible and simple data framework to connect custom data sources with large language models. LlamaIndex is a powerful tool to enhance your LLM applications. Connect your existing data formats and sources (APIs, PDFs, documents, SQL etc.). Use with a large-scale language model application. Store and index data for different uses. Integrate downstream vector stores and database providers. LlamaIndex is a query interface which accepts any input prompts over your data, and returns a knowledge augmented response. Connect unstructured data sources, such as PDFs, raw text files and images. Integrate structured data sources such as Excel, SQL etc. It provides ways to structure data (indices, charts) so that it can be used with LLMs.
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    Arch Reviews

    Arch

    Arch

    $0.75 per compute hour
    Stop wasting your time managing integrations and fighting the limitations of "black-box" "solutions". Instantly integrate data from any source into your app in the format you prefer. 500+ API & DB Sources, connector SDKs, OAuth flows and flexible data models. Instant vector embeddings. Managed transactional & analytic storage. Instant SQL, REST & GraphQL APIs. Arch allows you to build AI-powered features based on your customer's data, without having to worry and maintain bespoke data infrastructure.
  • 5
    Zerve AI Reviews
    With a fully automated cloud infrastructure, experts can explore data and write stable codes at the same time. Zerve’s data science environment gives data scientists and ML teams a unified workspace to explore, collaborate and build data science & AI project like never before. Zerve provides true language interoperability. Users can use Python, R SQL or Markdown in the same canvas and connect these code blocks. Zerve offers unlimited parallelization, allowing for code blocks and containers to run in parallel at any stage of development. Analysis artifacts can be automatically serialized, stored and preserved. This allows you to change a step without having to rerun previous steps. Selecting compute resources and memory in a fine-grained manner for complex data transformation.
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    Ikigai Reviews
    Simulations based on historical data can be used to improve models and update them incrementally. Data governance, access control, and versioning allow for easy collaboration. Ikigai has a wide range of integrations that make it easy to integrate with tools already in your workflow. Ikigai has 200+ connectors that allow you to connect to almost any data source. Want to push your ML to a dashboard or website? Integrate directly using Ikigai’s web integrations. Triggers can be used to run data synchronizations, and retrieve updates every time you run an automation flow. You can integrate Ikigai seamlessly by using your own APIs or creating APIs for your data stack.
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    Kognitos Reviews
    Create automations and manage exceptions in intuitive English. Automate in a simple and intuitive way processes that have large volumes of transactions, unstructured and structured data, and workflows with complex exceptions. RPA has historically had difficulty automating processes that encounter exceptions. Document-heavy workflows are a good example. Kognitos uses a fundamentally new approach, allowing users to teach automation how to handle exceptions by using natural language. Kognitos mimics how we teach each other to resolve errors and edge-cases by using intuitive prompting, which puts humans in charge. Automation can be trained just like you would train a human to work through experience and examples.
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    PromptQL Reviews
    PromptQL, a platform created by Hasura, allows Large Language Models to interact with structured data through agentic querying. This approach allows AI agents retrieve and process data using a human-like interface, improving their ability to handle real-world queries. PromptQL allows LLMs to manipulate and query data accurately by providing them with a Python interface and a standard SQL interface. The platform allows users to create AI assistants that are tailored to their needs by integrating with different data sources such as GitHub repositories or PostgreSQL database. PromptQL overcomes the limitations of traditional search retrieval methods, allowing AI agents to perform tasks like gathering relevant emails and identifying follow-ups more accurately. Users can start by connecting their data, adding the LLM API key and building with AI.
  • 9
    Unremot Reviews
    Unremot is the place to go for anyone who wants to build an AI-based product. With 120+ pre-built AIs, you can launch AI products at 1/3rd of the cost and 2X faster. Even the most complex AI product APIs can be launched and deployed in less than a minute, with minimal or no code. Unremot offers 120+ APIs. Choose the AI API you want to integrate into your product. Unremot will need your API private key in order to authenticate. Unremot's unique URL is the fastest way to connect your product API. The process can take minutes instead of days or weeks.
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