Best AI Development Platforms for PostgreSQL

Retool is a platform that enables developers to combine the benefits of traditional software development with a drag-and-drop editor and AI to build internal tools faster. Every tool can be deployed anywhere, debugged with your toolchain, and shared reliably at any scale—ensuring good software by default. Retool is used by industry leaders such as Amazon, American Express, and OpenAI for mission critical custom software across operations, billing, and customer support.

AI agents that interact and answer questions with users and complete tasks using your data and APIs. AI that can answer questions, summarize and extract insights from any long document. Transfer styles and formats, as well as tags and summaries between documents and data sources. Stack AI is used by developer teams to automate customer service, process documents, qualify leads, and search libraries of data. With a single button, you can try multiple LLM architectures and prompts. Collect data, run fine-tuning tasks and build the optimal LLM to fit your product. We host your workflows in APIs, so that your users have access to AI instantly. Compare the fine-tuning services of different LLM providers.

Akira AI provides the best explainability, accuracy and scalability in their application. Responsible AI can help you create applications that are transparent, robust, reliable, and fair. Transforming enterprise work with computer vision techniques, machine learning solutions and end-to-end deployment of models. ML model problems can be solved with actionable insights. Build AI systems that are compliant and responsible with proactive bias monitoring capabilities. Open the AI blackbox to optimize and understand the correct inner workings. Intelligent automation-enabled process reduce operational hindrances, and optimize workforce productivity. Build AI-quality AI solutions that optimize, monitor, and explain ML models. Improve performance, transparency and robustness. Model velocity can improve AI outcomes and model performance.

PostgresML is an entire platform that comes as a PostgreSQL Extension. Build simpler, faster and more scalable model right inside your database. Explore the SDK, and test open-source models in our hosted databases. Automate the entire workflow, from embedding creation to indexing and Querying for the easiest (and fastest) knowledge based chatbot implementation. Use multiple types of machine learning and natural language processing models, such as vector search or personalization with embeddings, to improve search results. Time series forecasting can help you gain key business insights. SQL and dozens regression algorithms allow you to build statistical and predictive models. ML at database layer can detect fraud and return results faster. PostgresML abstracts data management overheads from the ML/AI cycle by allowing users to run ML/LLM on a Postgres Database.

OpenPipe provides fine-tuning for developers. Keep all your models, datasets, and evaluations in one place. New models can be trained with a click of a mouse. Automatically record LLM responses and requests. Create datasets using your captured data. Train multiple base models using the same dataset. We can scale your model to millions of requests on our managed endpoints. Write evaluations and compare outputs of models side by side. You only need to change a few lines of code. OpenPipe API Key can be added to your Python or Javascript OpenAI SDK. Custom tags make your data searchable. Small, specialized models are much cheaper to run than large, multipurpose LLMs. Replace prompts in minutes instead of weeks. Mistral and Llama 2 models that are fine-tuned consistently outperform GPT-4-1106 Turbo, at a fraction the cost. Many of the base models that we use are open-source. You can download your own weights at any time when you fine-tune Mistral or Llama 2.

Use AI algorithms to receive intelligent suggestions about your API design. Automated recommendations tailored to your project will accelerate development. AI can automatically generate your database. Streamline deployment and increase productivity. Create and implement automated workflows to ensure a smooth, efficient development cycle. Customize automation processes to meet your project requirements. Workflows that are adaptable will allow you to create a personalized experience. Enjoy the flexibility to manage diverse data sources in a single, organized workspace. Workspaces can be designed to reflect the structure of projects. Create dedicated workspaces that can house multiple data sources seamlessly. Streamlining tasks by automating processes, increasing efficiency, and reducing the amount of manual effort. Each user has their own instance(s). Custom logic can be used to handle complex data operations.

Our open-source research efforts are focused on both the new "ware" (middleware and "software" which will wrap and integrate LLMs) as well as building high quality, automation-focused enterprise model available in Hugging Face. LLMWare is also a coherent, high quality, integrated and organized framework for developing LLM-applications in an open system. This provides the foundation for creating LLM-applications that are designed for AI Agent workflows and Retrieval Augmented Generation. Our LLM framework was built from the ground-up to handle complex enterprise use cases. We can provide pre-built LLMs tailored to your industry, or we can fine-tune and customize an LLM for specific domains and use cases. We provide an end-toend solution, from a robust AI framework to specialized models.

A managed PaaS that includes a low-code visual editor, VectorDB and integrations with apps and models to build, test, and deploy high-performance AI applications on the edge. Eliminate costly and error-prone work. Drag and drop agents, apps, data and models to find the best solution. Deployment in less than 60 seconds, and a 50% reduction in latency. Observe, iterate, and test seamlessly. Visibility and tools are essential for accuracy and reliability. Use data-driven decision making with reports on usage, LLM and request. View real-time traces per node. Experiments allow you to optimize embeddings and prompts, models and more. All you need to launch and iterate at large scale. Community of smart-minded builders who share their insights, experiences & feedback. Distilling the most useful tips, tricks and techniques for AI application developers. A platform that allows you to build agentic systems as if you were a 100-person team. A simple and intuitive frontend for managing AI applications and collaborating with them.

DataChain connects your unstructured cloud files with AI models, APIs and foundational models to enable instant data insights. Its Pythonic stack accelerates the development by tenfold when switching to Python-based data wrangling, without SQL data islands. DataChain provides dataset versioning to ensure full reproducibility and traceability for each dataset. This helps streamline team collaboration while ensuring data integrity. It allows you analyze your data wherever it is stored, storing raw data (S3, GCP or Azure) and metadata in inefficient datawarehouses. DataChain provides tools and integrations which are cloud-agnostic in terms of both storage and computing. DataChain allows you to query your multi-modal unstructured data. You can also apply intelligent AI filters for training data and snapshot your unstructured dataset, the code used for data selection and any stored or computed meta data.

Diaflow is a platform that allows you to scale AI across your entire organization. It enables everyone to deploy AI workflows which drive innovation. Create powerful apps and workflows using any data source to automate manual processes or create fully automated ones. Automate manual business processes in a way that your team will enjoy. Diaflow's intuitive components and interfaces allow you to create powerful AI-driven apps for your business that you can be proud of. Diaflow AI-powered editor offers a new way to create and edit documents. Your expertise can be leveraged to provide 24/7 support. With a built-in AI spreadsheet solution, you can easily manage and transform your data. Diaflow makes it easy to create amazing products for your business. Diaflow allows you to create apps and workflows without coding in just minutes.

An end-to-end solution gives you all the tools your data science team needs to scale your machine learning development, from research to production. cnvrg.io, the world's leading data science platform for MLOps (model management) is a leader in creating cutting-edge machine-learning development solutions that allow you to build high-impact models in half the time. In a collaborative and clear machine learning management environment, bridge science and engineering teams. Use interactive workspaces, dashboards and model repositories to communicate and reproduce results. You should be less concerned about technical complexity and more focused on creating high-impact ML models. The Cnvrg.io container based infrastructure simplifies engineering heavy tasks such as tracking, monitoring and configuration, compute resource management, server infrastructure, feature extraction, model deployment, and serving infrastructure.

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.

Declarative machine-learning systems offer the best combination of flexibility and simplicity, allowing for the fastest way to implement state-of-the art models. The system works by asking users to specify the "what" and then the system will figure out the "how". Start with smart defaults and iterate down to the code level on parameters. With Ludwig at Uber, and Overton from Apple, our team pioneered declarative machine-learning systems in industry. You can choose from our pre-built data connectors to support your databases, data warehouses and lakehouses as well as object storage. You can train state-of the-art deep learning models without having to manage infrastructure. Automated Machine Learning achieves the right balance between flexibility and control in a declarative manner. You can train and deploy models quickly using a declarative approach.

There are many e-mails you receive daily, but only a few that need your immediate attention. The email classifier below will help you keep an organized inbox. We summarize customer complaints and notify #customersupport on Slack. #customer-relation is for delayed orders. You want to be informed about what happened after a customer call with your support representative. Instead of listening to the entire call, create a Waveline flow which summarizes the key points. Many people have writer's block when they write text. Waveline allows you to quickly build an internal tool that automatically collects information from LinkedIn and Google searches about the recipient to create a highly personalized draft. Unstructured data can be repackaged into a structured format. Waveline uses LLMs for extracting information from text, images and other sources.

Everything you need to turn your ideas into AI apps within minutes. Our platform is easy to use and anyone can create next-generation AI-powered applications in just 10 minutes. Integrate APIs such as ChatGPT, Dalle-2 and Codex from Open AI seamlessly and even create custom ML models. To manage inventory, sales, contracts, and other functions, you can create a custom admin client or CRUD functionality. Dynamic dashboards can be created to transform data into actionable insights, and drive innovation for your business. Create a chatbot with multiple integrations to improve customer service and create an omnichannel experience. All-in-one cloud platform that combines low-code/no code tools with edge technologies. This makes your web application easy to manage, secure, and scalable. Our no-code/low code platform is perfect for both professional and business developers.

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.

Savvi is a powerful tool that can help you solve business challenges quickly and easily. Increase operational efficiency and empower your team for success. Start with the decision, prediction or recommendation that you would like to automate using AI. With a single line of code, you can easily integrate existing data into your app or run a cold start on data. Savvi manages your AI App from start to finish. Define your prediction or decision options. Identify business goals. Savvi collects data, trains ML models, builds your objective functions, and deploys your AI App. Savvi will learn continuously to improve according to your goals. Savvi will securely collect data and train a ML model from your product in less than few weeks. Savvi code can be dropped in and you're ready to go. You don't need to start with a data architecture project in order to use AI.

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.

Discover. Analyze. Optimize. Use [impaction.ai]’s intuitive semantic search to easily sift conversational data. Type 'find me conversation where ...', and let our engine handle the rest. Meet Columbus, your intelligent data co-pilot. Columbus analyzes conversations and highlights key trends. It can even recommend which dialogues you should pay attention to. Take data-driven action to improve user engagement and create a smarter and more responsive AI product. Columbus is not only a great source of information, but also offers suggestions on how to improve the situation.