Best Artificial Intelligence Software for Python - Page 20
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Compare the Top Artificial Intelligence Software that integrates with Python as of September 2026 - Page 20
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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
RunInfra
RunInfra
RunInfra turns plain English into production AI inference endpoints. Describe your use case, and the AI agent builds, optimizes, deploys, and scales it for you; no YAML, no DevOps, no GPU configuration, just chat. It is built for shipping open source AI models as production APIs, selecting compatible models, benchmarking real GPUs, applying kernel optimizations, and deploying OpenAI-compatible HTTP endpoints. RunInfra can build LLM, speech-to-text, text-to-speech, embedding, vision-language, image-generation, RAG search, document AI, transcription, AI assistant, and multi-model reasoning pipelines when the selected model and runtime support the route. Its workflow moves from description to optimization to deployment to integration; tell RunInfra what you need, let it profile real GPUs from L4 to B200, search model variants such as AWQ, GPTQ, and FP8, tune kernels with Forge, and ship an endpoint that works with OpenAI Python and JavaScript SDKs.Starting Price: $100 per month -
2
Waterfall
Waterfall
Waterfall is a credit infrastructure for platforms building on large language models, designed to turn AI usage into a business model without requiring teams to build their own billing stack. It gives each user, agent, or team a stablecoin-backed credit wallet, then meters every model call by provider, model, token count, and cost. Requests can be routed through the Waterfall Gateway or integrated through TypeScript and Python SDKs, with usage attributed to the correct wallet in real time. Each API call settles atomically against the wallet as it happens, so credits decrease, and revenue is recognized per request instead of through delayed invoices and manual reconciliation. Waterfall supports more than 300 models across providers such as OpenAI, Anthropic, DeepSeek, and xAI, allowing products to use multiple AI services while maintaining one accounting layer.Starting Price: $20 per month -
3
Qwen3.8-Flash-Next
Alibaba
Qwen3.8-Flash-Next is an open-weight multimodal Mixture-of-Experts model and an early preview of the architecture planned for Qwen4. It systematically upgrades attention, residual connections, embeddings, and optimization to improve capability, computational efficiency, model capacity, and training stability. Its hybrid architecture combines Gated DeltaNet, which efficiently compresses historical information, with Qwen Sparse Attention, which selects important context at the micro-block level to reduce attention and indexing costs on long sequences. Gated Residual widens the residual stream into four branches and dynamically controls information flow across layers, while N-gram Embedding adds large-scale local-pattern memory with very little extra per-token computation and can be offloaded to host memory. The model uses a 125B-parameter main network plus 51B N-gram embedding parameters, while activating only 6B parameters per token.Starting Price: $2 per 1M (input) -
4
TrustedRouter
TrustedRouter
TrustedRouter is a privacy-first AI gateway that gives developers access to 600+ AI models from 90+ providers through one OpenAI-compatible API. It routes requests through an attested gateway that does not log prompt or output content, keeping the production prompt path separate from the dashboard and billing control plane so even its engineers cannot read requests. Developers can keep the OpenAI SDK and migrate by changing a single base URL, while choosing direct model IDs or routing aliases for healthy-provider rollover, zero-retention providers, confidential compute, EU-focused routing, and multi-model synthesis. Provider failover, regional routing, and continuous model health measurements help prevent a single upstream outage from becoming a product outage. TrustedRouter runs across GCP, AWS, and Azure and publishes latency, availability, source code, deployment infrastructure, SDKs, and trust evidence for inspection.Starting Price: $0.01 per million tokens -
5
Dial
Dial
Dial is a communication stack for AI agents that gives software its own real phone identity: a number it controls to place and receive voice calls, send and receive SMS, and message over WhatsApp through one REST API, MCP server, CLI, or SDK. It rebuilds a telephone stack originally designed around humans, SIM cards, carrier contracts, handsets, and verification flows so autonomous agents can communicate without dedicated hardware or manual carrier setup. Agents can provision a real phone number, make AI voice calls that follow instructions such as booking, confirming, or following up, and use live transcription with optional transfer to a human. Dial also supports two-way SMS and WhatsApp messaging, inbound calls and texts, AI receptionist behavior, and streamed inbound events. Agents can receive SMS verification codes for phone-gated workflows and react to communication events programmatically.Starting Price: $3 per month -
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Earthly Lunar
Earthly Lunar
Earthly Lunar is a guardrails engine for platform engineering teams that need to apply engineering standards consistently across repositories and CI/CD pipelines. It collects signals from code, configuration, dependencies, tests, builds, and deployments, then turns them into structured posture data for each service. Teams use guardrails as code to check that data against requirements for testing, reliability, operational readiness, and compliance. Lunar provides feedback on code changes and pull requests, with modes from reporting to blocking PRs or deployments. Central management lets platform teams roll out a standard across diverse pipelines without changing every repository. The same checks cover human-written and AI-generated code, while dashboards and an enforcement record show where teams meet standards and where gaps remain. More than 200 prebuilt guardrails provide a starting point; teams can add their own. -
7
TabPFN-3.5
Prior Labs
TabPFN-3.5 is a tabular foundation model built for state-of-the-art predictions on structured data. It supports a wide range of prediction tasks, including churn, fraud, pricing, demand forecasting, risk, and other real-world data science problems, allowing teams to serve multiple use cases with one model. The model works with data as it is, handling missing values, outliers, categorical features, multi-table datasets, free text as a feature, thousands of distinct IDs without encoding, and hundreds of measurements per row. Users can feed in raw data, skip feature engineering and preprocessing, and get production-grade predictions from the first predict call. TabPFN-3.5 performs predictions in a single forward pass and is designed for both accuracy and speed, with fast inference for latency-critical predictive workflows. It supports production-scale datasets of up to one million rows natively and delivers 20x faster inference than previous model versions. -
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Step 5 Preview
StepFun
Step 5 Preview is StepFun’s flagship model for agentic work, designed for real-world tasks across software engineering and professional knowledge work, with particular strength in finance. It natively supports text, image, and video input and provides a 1M-token context window, enabling tasks that require large amounts of information, tool calls, and continuous progress toward a deliverable. The model can analyze long documents, multiple source materials, and conversation history for cross-document question answering and research organization. For programming and software engineering, it works across multiple languages and can support troubleshooting, code changes, verification, and test creation. Its multi-step agent capabilities let applications provide tools for retrieving information, processing documents, conducting deep research, and producing analytical reports. Multimodal understanding combines images, video, and text for chart analysis, screenshot question answering, etc.Starting Price: $0.04 per input -
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Forsta
Forsta
The most powerful, flexible, connected, and most reliable experience & research tech platform. Forsta transcends methodological and data silos. All human experience is here. If it’s insightful, it’s measurable. Use customizable surveys to seek insight from any audience, from small teams to global communities. Take the data you need from any touchpoint or channel. Forsta comes packed with the tools to bring you better data and deeper insights. So you can push your business forward. If it’s insightful, it’s measurable. Use customizable surveys or moderated online conversations to seek insight from any audience – from small teams to global communities. Take the data you need from any touchpoint or channel. Bring all your data onto a single platform. So you can see the stories behind the statistics. Use advanced analytics tools to search, sort and filter in whatever way gets you to the answers you need. -
10
Google Cloud Vision AI
Google
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog. -
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Segments.ai
Segments.ai
Segments.ai is an advanced data labeling platform that allows users to label data from multiple sensors simultaneously, improving the speed and accuracy of labeling for robotics and autonomous vehicle (AV) applications. It supports 2D and 3D labeling, including point cloud annotation, and enables users to label moving and stationary objects with ease. The platform leverages smart automation tools like batch mode and ML-powered object tracking, streamlining workflows and reducing manual labor. By fusing 2D image data with 3D point cloud data, Segments.ai offers a more efficient and consistent labeling process, ideal for high-volume, multi-sensor projects. -
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Prefect
Prefect
Prefect is a workflow orchestration and automation platform designed for the modern context-driven era. It enables teams to turn Python functions into production-ready workflows with minimal effort. Prefect provides open-source foundations alongside managed platforms for enterprise-scale automation. The platform supports building and orchestrating data pipelines, workflows, and AI applications with full observability. Prefect Cloud offers managed orchestration with autoscaling, enterprise authentication, and built-in governance. Prefect Horizon extends automation to AI infrastructure by enabling deployment of MCP servers for AI agents. Trusted by leading organizations, Prefect helps teams scale automation without operational complexity. -
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AiXcoder
AiXcoder
Leave Artificial Intelligence to AIXcoder. Leave Real Intelligence to Human. The offline version is released! Your code is safe on your computer locally. AiXcoder works in smooth locally with state of art deep learning model compression techniques. The models are trained with a massive amount of open source code. And adapted to several areas. A search window is seamlessly integrated into IDE with the ability to search open-source code on GitHub. Deep learning is used to filter high-quality code as search results. Search API usage and examples. Search similar code to avoid duplicated coding. Project Level Personalized Training: Train models on personal project and computer. Enterprise Level Customized Training: Train models on code base and enterprise server. Based on standard model, personalized and customized training will learn the patterns and rules in your proprietary code. -
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binds.co
binds.co
Responsive questionnaires designed to provide a personalized experience, whether on mobile or desktop. Customers give very powerful feedback through unstructured survey text. The Text Analysis Tool uses Artificial Intelligence techniques to automatically analyze these text feedbacks, so you can understand the most critical points of the journey. Engage customers, employees and managers, and increase customer response time with automatic customer journey alerts by email or SMS. With Close the Loop Chat You can meet the real-time demands of customer satisfaction survey responses. The news is that this feature allows the company to interact with the consumer through a chat, available on the platform, and the customer receives feedback in their email as in a conversation.Starting Price: $50.99 per month -
15
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. -
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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. -
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AlphaCode
Google 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. -
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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. -
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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. -
20
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. -
21
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. -
22
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. -
23
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. -
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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. -
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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.
