Best Artificial Intelligence Software for Python - Page 15
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Compare the Top Artificial Intelligence Software that integrates with Python as of November 2025 - Page 15
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This a list of Artificial Intelligence software that integrates with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.
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1
Feast
Tecton
Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution. -
2
Zepl
Zepl
Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github. -
3
AlphaCode
DeepMind
Creating solutions to unforeseen problems is second nature in human intelligence, a result of critical thinking informed by experience. The machine learning community has made tremendous progress in generating and understanding textual data, but advances in problem-solving remain limited to relatively simple maths and programming problems, or else retrieving and copying existing solutions. As part of DeepMind’s mission to solve intelligence, we created a system called AlphaCode that writes computer programs at a competitive level. AlphaCode achieved an estimated rank within the top 54% of participants in programming competitions by solving new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding. AlphaCode uses transformer-based language models to generate code at an unprecedented scale, and then smartly filters to a small set of promising programs. -
4
Sirius
Data Semantics
The all-in-one chatbot platform that outshines all conversational platforms. Sirius is designed to optimize the workflow of employees and increase transactional conversions from conversations with your customers while having a delightful conversation flow. This chatbot platform is designed to offer complete control to administrative teams and can be deployed on multiple channels and sources within a few hours! Dive right in to explore the uber-cool, Sirius. Get the usage analytics of your user behavior with the most relevant metrics on the dashboard of SiriuBOT. Get your Power BI KPIs and reports on any channels of the bot’s chat interface withing seconds, anytime, anywhere. SiriusBOT is smart enough to understand the intent of users and enables you to completely manage them from the backend. Identify the unanswered queries by the bot and train it to become smarter for your users, with every interaction. -
5
Lexalytics
Lexalytics
Integrate our text analytics APIs to add world-leading NLP into your product, platform, or application. The most feature-complete NLP feature stack on the market, 19 years in development and constantly being improved with new libraries, configurations, and models. Determine whether a piece of writing is positive, negative, or neutral. Sort and organize documents into customizable groups. Determine the expressed intent of customers and reviewers. Find people, places, dates, companies, products, jobs, titles, and more. Deploy our text analytics and NLP systems across any combination of on-premise, private cloud, hybrid cloud, and public cloud infrastructure. Our core text analytics and natural language processing software libraries are at your command. Suitable for data scientists and architects who want complete access to the underlying technology or who need on-premise deployment for security or privacy reasons. -
6
Salience
Lexalytics
Text analytics and NLP software libraries for on-premise deployment or integration. Integrate Salience into your enterprise business intelligence architecture or white label it inside your own data analytics product. Salience can process 200 tweets per second while scaling from single process cores to entire data centers with a small memory footprint. Use Java, Python, .NET/C# bindings for higher level ease or the native C/C++ interface for maximum speed. Enjoy full access to the underlying technology. Tune every text analytics function and NLP feature, from tokenization and part of speech tagging to sentiment scoring, categorization, theme analysis, and more. Built on a pipeline model of NLP rules and machine learning models. When issues arise, see exactly where they are in the pipeline. Adjust specific features without disrupting the larger system. Salience runs entirely on your servers while staying flexible enough to offload insensitive data to cloud servers. -
7
MindMeld
Cisco DevNet
The MindMeld Conversational AI Platform is a Python-based machine learning framework that encompasses all of the algorithms and utilities required for building production-quality conversational applications. Evolved over several years of building and deploying dozens of advanced interfaces, MindMeld is optimized for building conversational assistants which demonstrate deep understanding of a particular use case or domain while providing highly useful and versatile conversational experiences. Powerful command-line utilities and Python APIs with the flexibility to accommodate nearly any product requirements. Access to state-of-the-art machine learning algorithms and streamlined management of large sets of custom training data. Enhanced entity recognition and resolution to deal with automatic speech recognition (ASR) errors. -
8
Kodezi
Kodezi
Let Kodezi auto-summarize your code in seconds. Kodezi is Grammarly for programmers. Generate, ask, search, and code anything in your codebase with KodeziChat. Your personal AI coding assistant! Kodezi doesn't just fix your code for you, it tells you why it’s wrong and how to prevent future bugs. Reduce unnecessary lines of code and syntax to ensure clean end results. Optimize your code for optimum efficiency. Debug code with detailed explanations. Swap from one framework or language to another in an instant, without losing context. When writing code, commenting and explanations are crucial for future maintenance. Generate code from text, input a project question or create an entire function all in seconds! Generate your code documentation. Translate code to another language. Optimize your code for optimum efficiency. Use our extension within your own IDE, never have to rely on opening up new tabs ever again. -
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SourceAI
SourceAI
Open to all (even for non-developers), straightforward and simple to use, clear and intuitive interface. Save time in development, generate your code in one click and use your time more efficiently. Powered by GPT-3 and Codex, the most advanced AI technology, and next-generation development. Sometimes SourceAI will have trouble understanding what you want, so you'll have to explain it in more detail. At SourceAI, we are a close-knit team of empathetic and optimistic developers who care deeply about accelerating human progress by making programming accessible to all. Our mission is to give everyone the opportunity to create valuable customized software. We build a self-contained system that can create software at the level of the world's most skilled engineers. We have developed a stand-alone system based on the GPT-3 language model. SourceAI is a tool that can generate code for you in any language from a plain text description. -
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MakerSuite
Google
MakerSuite is a tool that simplifies this workflow. With MakerSuite, you’ll be able to iterate on prompts, augment your dataset with synthetic data, and easily tune custom models. When you’re ready to move to code, MakerSuite will let you export your prompt as code in your favorite languages and frameworks, like Python and Node.js. -
11
Steamship
Steamship
Ship AI faster with managed, cloud-hosted AI packages. Full, built-in support for GPT-4. No API tokens are necessary. Build with our low code framework. Integrations with all major models are built-in. Deploy for an instant API. Scale and share without managing infrastructure. Turn prompts, prompt chains, and basic Python into a managed API. Turn a clever prompt into a published API you can share. Add logic and routing smarts with Python. Steamship connects to your favorite models and services so that you don't have to learn a new API for every provider. Steamship persists in model output in a standardized format. Consolidate training, inference, vector search, and endpoint hosting. Import, transcribe, or generate text. Run all the models you want on it. Query across the results with ShipQL. Packages are full-stack, cloud-hosted AI apps. Each instance you create provides an API and private data workspace. -
12
Avanzai
Avanzai
Avanzai helps accelerate your financial data analysis by letting you use natural language to output production-ready Python code. Avanzai speeds up financial data analysis for both beginners and experts using plain English. Plot times series data, equity index members, and even stock performance data using natural prompts. Skip the boring parts of financial analysis by leveraging AI to generate code with relevant Python packages already installed. Further edit the code if you wish, once you're ready copy and paste the code into your local environment and get straight to business. Leverage commonly used Python packages for quant analysis such as Pandas, Numpy, etc using plain English. Take financial analysis to the next level, quickly pull fundamental data and calculate the performance of nearly all US stocks. Enhance your investment decisions with accurate and up-to-date information. Avanzai empowers you to write the same Python code that quants use to analyze complex financial data. -
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Amazon SageMaker provides all the tools and libraries you need to build ML models, the process of iteratively trying different algorithms and evaluating their accuracy to find the best one for your use case. In Amazon SageMaker you can pick different algorithms, including over 15 that are built-in and optimized for SageMaker, and use over 150 pre-built models from popular model zoos available with a few clicks. SageMaker also offers a variety of model-building tools including Amazon SageMaker Studio Notebooks and RStudio where you can run ML models on a small scale to see results and view reports on their performance so you can come up with high-quality working prototypes. Amazon SageMaker Studio Notebooks help you build ML models faster and collaborate with your team. Amazon SageMaker Studio notebooks provide one-click Jupyter notebooks that you can start working within seconds. Amazon SageMaker also enables one-click sharing of notebooks.
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Amazon SageMaker Studio Lab
Amazon
Amazon SageMaker Studio Lab is a free machine learning (ML) development environment that provides the compute, storage (up to 15GB), and security, all at no cost, for anyone to learn and experiment with ML. All you need to get started is a valid email address, you don’t need to configure infrastructure or manage identity and access or even sign up for an AWS account. SageMaker Studio Lab accelerates model building through GitHub integration, and it comes preconfigured with the most popular ML tools, frameworks, and libraries to get you started immediately. SageMaker Studio Lab automatically saves your work so you don’t need to restart in between sessions. It’s as easy as closing your laptop and coming back later. Free machine learning development environment that provides the computing, storage, and security to learn and experiment with ML. GitHub integration and preconfigured with the most popular ML tools, frameworks, and libraries so you can get started immediately. -
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Gradio
Gradio
Build & Share Delightful Machine Learning Apps. Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that lets them interact with the model on your computer remotely from their own devices. Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share. -
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MosaicML
MosaicML
Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest, orchestration, efficiency, node failures, and infrastructure. Simple and scalable. MosaicML enables you to easily train and deploy large AI models on your data, in your secure environment. Stay on the cutting edge with our latest recipes, techniques, and foundation models. Developed and rigorously tested by our research team. With a few simple steps, deploy inside your private cloud. Your data and models never leave your firewalls. Start in one cloud, and continue on another, without skipping a beat. Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs. Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud-agnostic, and enterprise proved. -
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Quadratic
Quadratic
Quadratic enables your team to work together on data analysis to deliver faster results. You already know how to use a spreadsheet, but you’ve never had this much power. Quadratic speaks Formulas and Python (SQL & JavaScript coming soon). Use the language you and your team already know. Single-line formulas are hard to read. In Quadratic you can expand your recipes to as many lines as you need. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. The last line of code is returned to the spreadsheet. Raw values, 1/2D arrays, and Pandas DataFrames are supported by default. Pull or fetch data from an external API, and it updates automatically in Quadratic's cells. Navigate with ease, zoom out for the big picture, and zoom in to focus on the details. Arrange and navigate your data how it makes sense in your head, not how a tool forces you to do it. -
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UnionML
Union
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. -
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Dify
Dify
Dify is an open-source platform designed to streamline the development and operation of generative AI applications. It offers a comprehensive suite of tools, including an intuitive orchestration studio for visual workflow design, a Prompt IDE for prompt testing and refinement, and enterprise-level LLMOps capabilities for monitoring and optimizing large language models. Dify supports integration with various LLMs, such as OpenAI's GPT series and open-source models like Llama, providing flexibility for developers to select models that best fit their needs. Additionally, its Backend-as-a-Service (BaaS) features enable seamless incorporation of AI functionalities into existing enterprise systems, facilitating the creation of AI-powered chatbots, document summarization tools, and virtual assistants. -
20
Granica
Granica
The Granica AI efficiency platform reduces the cost to store and access data while preserving its privacy to unlock it for training. Granica is developer-first, petabyte-scale, and AWS/GCP-native. Granica makes AI pipelines more efficient, privacy-preserving, and more performant. Efficiency is a new layer in the AI stack. Byte-granular data reduction uses novel compression algorithms, cutting costs to store and transfer objects in Amazon S3 and Google Cloud Storage by up to 80% and API costs by up to 90%. Estimate in 30 mins in your cloud environment, on a read-only sample of your S3/GCS data. No need for budget allocation or total cost of ownership analysis. Granica deploys into your environment and VPC, respecting all of your security policies. Granica supports a wide range of data types for AI/ML/analytics, with lossy and fully lossless compression variants. Detect and protect sensitive data even before it is persisted into your cloud object store. -
21
Wherobots
Wherobots
Wherobots enables users to easily develop, test, and deploy geospatial data analytics and AI pipelines within the user's existing data stack. That can be deployed in the cloud. Users do not have to worry about the hassle of resource administration, workload scalability, and geospatial processing support/optimization. Connect your Wherobots account to the cloud database where the data is stored using our SaaS web interface. Develop your geospatial data science, machine learning, or analytics application using Sedona Developer Tool. Schedule automatic deployment of your geospatial pipeline to the cloud data platform and monitor the performance in Wherobots. Consume the outcome of your geospatial analytics task. The consumption model can be through a single geospatial map visualization or API calls. -
22
Editor.do
Editor.do
Editor.do is an all-in-one online IDE and hosting platform that allows you to create, code, host and deploy stunning & fast static websites in seconds. You can easily deploy your site files or a zip containing all your project files to our NVMe SSD storage servers, ensuring the fastest possible loading speed for your site. Our IDE supports over 150 programming languages with real-time code rendering and a panel of shortcuts and tools to search, replace, cut, select, and quickly manipulate your code. Editor.do offers over 1000 free and open-source templates covering a wide range of categories and libraries that can be imported directly from GitHub. Plus, ChatGPT is integrated and is always close at hand to help you correct, complete, or improve your code or text. Editor.do is an ideal platform for developers and designers of all skill levels who want to create stunning, fast, and secure websites in a fraction of the time.Starting Price: $3 per month -
23
Sweep AI
Sweep AI
Spend time reviewing code generated by AI, not writing it. Sweep generates repository-level code at your command. Cut down your dev time on mundane tasks, like tests, documentation, and refactoring. Review all changes by Sweep, directly in Github, and comment if any changes need to be made. Push the commit if all looks good. All you have to do is write a ticket, and Sweep will do all of the heavy-lifting for you, allowing you to focus on the more important engineering problems. -
24
Parsagon
Parsagon
Tell Parsagon what you want to do - our AI will write code to do it. -
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Monster API
Monster API
Effortlessly access powerful generative AI models with our auto-scaling APIs, zero management required. Generative AI models like stable diffusion, pix2pix and dreambooth are now an API call away. Build applications on top of such generative AI models using our scalable rest APIs which integrate seamlessly and come at a fraction of the cost of other alternatives. Seamless integrations with your existing systems, without the need for extensive development. Easily integrate our APIs into your workflow with support for stacks like CURL, Python, Node.js and PHP. We access the unused computing power of millions of decentralised crypto mining rigs worldwide and optimize them for machine learning and package them with popular generative AI models like Stable Diffusion. By harnessing these decentralized resources, we can provide you with a scalable, globally accessible, and, most importantly, affordable platform for Generative AI delivered through seamlessly integrable APIs. -
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dstack
dstack
dstack is an orchestration layer designed for modern ML teams, providing a unified control plane for development, training, and inference on GPUs across cloud, Kubernetes, or on-prem environments. By simplifying cluster management and workload scheduling, it eliminates the complexity of Helm charts and Kubernetes operators. The platform supports both cloud-native and on-prem clusters, with quick connections via Kubernetes or SSH fleets. Developers can spin up containerized environments that link directly to their IDEs, streamlining the machine learning workflow from prototyping to deployment. dstack also enables seamless scaling from single-node experiments to distributed training while optimizing GPU usage and costs. With secure, auto-scaling endpoints compatible with OpenAI standards, it empowers teams to deploy models quickly and reliably. -
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Vaex
Vaex
At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine. -
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AskYourDatabase
AskYourDatabase
Forget complex SQL or Python scripts, connect your database, and start chatting with your data. This plugin is a ChatGPT demo for further development. It only supports PostgreSQL, but you can copy and use it as a starting point for developing your own plugin. After you install it, you can try it with your PostgreSQL database, if you don't have one, you can try Vercel Postgres and get a free Postgres DB. -
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Ever Efficient AI
Ever Efficient AI
Ever Efficient AI offers a powerful yet accessible AI automation platform helping businesses maximize efficiency - without hiring a full-time AI engineer on the team. Their flexible subscription plans connect you with AI experts who build customized data solutions tailored to your specific workflows and industry. No complex modeling or coding is required on your end. The collaborative process lets those with domain expertise guide tool development. EverEfficientAI's team manages the technical complexity behind the scenes, converting your datasets and processes into optimized AI systems. Bi-weekly agile sprints adapt the tools over time while providing transparency. With a focus on usability and rapid integration, EverEfficientAI makes advanced AI easily actionable by any organization. The future of work is here - are you ready to let your data work smarter for you?Starting Price: $3,497 per month -
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StableCode
Stability AI
StableCode offers a unique way for developers to become more efficient by using three different models to help in their coding. The base model was first trained on a diverse set of programming languages from the stack-dataset (v1.2) from BigCode and then trained further with popular languages like Python, Go, Java, Javascript, C, markdown and C++. In total, we trained our models on 560B tokens of code on our HPC cluster. After the base model had been established, the instruction model was then tuned for specific use cases to help solve complex programming tasks. ~120,000 code instruction/response pairs in Alpaca format were trained on the base model to achieve this result. StableCode is the ideal building block for those wanting to learn more about coding, and the long-context window model is the perfect assistant to ensure single and multiple-line autocomplete suggestions are available for the user. This model is built to handle a lot more code at once.
