Best Artificial Intelligence Software for Python - Page 20
View:
Compare the Top Artificial Intelligence Software that integrates with Python as of July 2026 - Page 20
Sort By:
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.
-
1
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. -
2
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. -
3
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. -
4
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 -
5
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. -
6
Enable hybrid cloud developers of all experience levels to write code with AI-generated recommendations. What if you could translate plain English to code? IBM watsonx Code Assistant allows you to do just that. Powered by IBM watsonx.ai foundation models (FM), IBM watsonx Code Assistant makes it easier for anyone to write code with AI-generated recommendations, bringing the power of IT automation to your entire organization as a strategic, accessible asset for more users—not just the subject-matter experts. This means automatically suggesting code for developers based on natural language inputs. IBM watsonx Code Assistant is infused with watsonx.ai FMs that are purpose-built, created with deployment efficiency in mind, and which enable organizations to customize the models, while also applying enterprise standards and best practices.
-
7
NVIDIA Holoscan
NVIDIA
NVIDIA® Holoscan is a domain-agnostic AI computing platform that delivers the accelerated, full-stack infrastructure required for scalable, software-defined, and real-time processing of streaming data running at the edge or in the cloud. Holoscan supports a camera serial interface and front-end sensors for video capture, ultrasound research, data acquisition, and connection to legacy medical devices. Use the NVIDIA Holoscan SDK’s data transfer latency tool to measure complete, end-to-end latency for video processing applications. Access AI reference pipelines for radar, high-energy light sources, endoscopy, ultrasound, and other streaming video applications. NVIDIA Holoscan includes optimized libraries for network connectivity, data processing, and AI, as well as examples to create and run low-latency data-streaming applications using either C++, Python, or Graph Composer. -
8
Cirrascale
Cirrascale
Our high-throughput storage systems can serve millions of small, random files to GPU-based training servers accelerating overall training times. We offer high-bandwidth, low-latency networks for connecting distributed training servers as well as transporting data between storage and servers. Other cloud providers squeeze you with extra fees and charges to get your data out of their storage clouds, and those can add up fast. We consider ourselves an extension of your team. We work with you to set up scheduling services, help with best practices, and provide superior support. Workflows can vary from company to company. Cirrascale works to ensure you get the right solution for your needs to get you the best results. Cirrascale is the only provider that works with you to tailor your cloud instances to increase performance, remove bottlenecks, and optimize your workflow. Cloud-based solutions to accelerate your training, simulation, and re-simulation time.Starting Price: $2.49 per hour -
9
Yamak.ai
Yamak.ai
Train and deploy GPT models for any use case with the first no-code AI platform for businesses. Our prompt experts are here to help you. If you're looking to fine-tune open source models with your own data, our cost-effective tools are specifically designed for the same. Securely deploy your own open source model across multiple clouds without the need to rely on third-party vendors for your valuable data. Our team of experts will deliver the perfect app tailored to your specific requirements. Our tool enables you to effortlessly monitor your usage and reduce costs. Partner with us and let our expert team address your pain points effectively. Efficiently classify your customer calls and automate your company’s customer service with ease. Our advanced solution empowers you to streamline customer interactions and enhance service delivery. Build a robust system that detects fraud and anomalies in your data based on previously flagged data points. -
10
Kolena
Kolena
Kolena AI is an enterprise automation platform designed for real estate, financial services, and insurance brands. It streamlines workflows by converting complex documents into structured, actionable outputs in minutes. Prebuilt AI agents handle tasks like lease abstractions, investment memos, rent roll spreadsheets, and compliance checklists, reducing manual effort and increasing accuracy. The platform also supports custom agents, allowing businesses to tailor automation to their unique workflows. With precision extraction, compliance validation, and integration into systems like Salesforce, Kolena AI enhances efficiency and consistency. Trusted by leading companies, it helps teams scale smarter by replacing manual reviews and legacy OCR with AI-powered automation. -
11
Ntropy
Ntropy
Ship faster integrating with our Python SDK or Rest API in minutes. No prior setups or data formatting. You can get going straight away as soon as you have incoming data and your first customers. We have built and fine-tuned custom language models to recognize entities, automatically crawl the web in real-time and pick the best match, as well as assign labels with superhuman accuracy in a fraction of the time. Everybody has a data enrichment model that is trying to be good at one thing, US or Europe, business or consumer. These models are poor at generalizing and are not capable of human-level output. With us, you can leverage the power of the world's largest and most performant models embedded in your products, at a fraction of cost and time. -
12
Definitive
Definitive
A one-shot prompt-to-visualization API that seamlessly integrates with enterprise & public data, enabling users to instantly & accurately retrieve visually rich answers to their questions. Enables enterprises to engage in dynamic conversations with their own data, fostering efficient collaboration and informed decision-making. Supports Python code generation and joining of disparate data sets. An autonomous data science agent, providing comprehensive support in data analysis, predictive modeling, and advanced analytics. Create the enterprise AI sidekick experience that works best for your organization. Public LLMs are not currently trained on an enterprise's unique, proprietary data sets. Your sidekick unlocks workplace productivity. A more engaging interface for complex analysis is now accessible to all members of the organization, regardless of technical ability. Through API-level access, your sidekick integrates with your existing products, systems, and workflows. -
13
Code to Flowchart
Code to Flowchart
Turn code into interactive flowcharts with AI, and simplify complex logic instantly.Starting Price: Free -
14
Second State
Second State
Fast, lightweight, portable, rust-powered, and OpenAI compatible. We work with cloud providers, especially edge cloud/CDN compute providers, to support microservices for web apps. Use cases include AI inference, database access, CRM, ecommerce, workflow management, and server-side rendering. We work with streaming frameworks and databases to support embedded serverless functions for data filtering and analytics. The serverless functions could be database UDFs. They could also be embedded in data ingest or query result streams. Take full advantage of the GPUs, write once, and run anywhere. Get started with the Llama 2 series of models on your own device in 5 minutes. Retrieval-argumented generation (RAG) is a very popular approach to building AI agents with external knowledge bases. Create an HTTP microservice for image classification. It runs YOLO and Mediapipe models at native GPU speed. -
15
SuperDuperDB
SuperDuperDB
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, and HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands. -
16
WhyLabs
WhyLabs
Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks. -
17
Martian
Martian
By using the best-performing model for each request, we can achieve higher performance than any single model. Martian outperforms GPT-4 across OpenAI's evals (open/evals). We turn opaque black boxes into interpretable representations. Our router is the first tool built on top of our model mapping method. We are developing many other applications of model mapping including turning transformers from indecipherable matrices into human-readable programs. If a company experiences an outage or high latency period, automatically reroute to other providers so your customers never experience any issues. Determine how much you could save by using the Martian Model Router with our interactive cost calculator. Input your number of users, tokens per session, and sessions per month, and specify your cost/quality tradeoff. -
18
Shakker
Shakker
With Shakker you can turn your imagination into images, in seconds. AI image generation doesn't have to be clunky when you use Shakker. Whether you want to create images, change styles, combine components, or paint any parts, Shakker makes it smoother than ever for you with prompt suggestions and precise designs. Shakker revolutionizes image creation, you can simply upload a reference photo, and it recommends styles from a library of vast images, making it easy to craft the perfect image. Beyond style transformation, Shakker offers advanced editing tools like segmentation, quick selection, and lasso for precise inpainting. Shakker.AI operates on sophisticated AI algorithms that analyze input and generate images accordingly. It interprets user commands or prompts to produce images that align with specified styles and themes. The underlying technology seamlessly blends AI's computational power with artistic creativity, delivering both unique and high-quality outputs. -
19
UbiOps
UbiOps
UbiOps is an AI infrastructure platform that helps teams to quickly run their AI & ML workloads as reliable and secure microservices, without upending their existing workflows. Integrate UbiOps seamlessly into your data science workbench within minutes, and avoid the time-consuming burden of setting up and managing expensive cloud infrastructure. Whether you are a start-up looking to launch an AI product, or a data science team at a large organization. UbiOps will be there for you as a reliable backbone for any AI or ML service. Scale your AI workloads dynamically with usage without paying for idle time. Accelerate model training and inference with instant on-demand access to powerful GPUs enhanced with serverless, multi-cloud workload distribution. -
20
Gemma
Google
Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs. -
21
Zama
Zama
Improve patient care while maintaining privacy by allowing secure, confidential data sharing between healthcare providers. Facilitate secure financial data analysis for risk management and fraud detection, keeping client information encrypted and safe. Create targeted advertising and campaign insights in a post-cookie era, ensuring user privacy through encrypted data analysis. Enable data collaboration between different agencies, while keeping it confidential from each other, enhancing efficiency and data security, without revealing secrets. Give the ability to create user authentication applications without having to reveal their identities. Enable governments to create digitized versions of their services without having to trust cloud providers. -
22
Superlinked
Superlinked
Combine semantic relevance and user feedback to reliably retrieve the optimal document chunks in your retrieval augmented generation system. Combine semantic relevance and document freshness in your search system, because more recent results tend to be more accurate. Build a real-time personalized ecommerce product feed with user vectors constructed from SKU embeddings the user interacted with. Discover behavioral clusters of your customers using a vector index in your data warehouse. Describe and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook. -
23
Anon
Anon
Anon offers two powerful ways to integrate your applications with services that lack APIs, enabling you to build innovative solutions and automate workflows like never before. The API packages pre-built automation on popular services that don’t offer APIs and are the simplest way to use Anon. The toolkit to build user-permissions integrations for sites without APIs. Using Anon, developers can enable agents to authenticate and take actions on behalf of users across the most popular sites on the internet. Programmatically interact with the most popular messaging services. The runtime SDK is an authentication toolkit that lets AI agent developers build their own integrations on popular services that don’t offer APIs. Anon simplifies the work of building and maintaining user-permission integrations across platforms, languages, auth types, and services. We build the annoying infra so you can build amazing apps. -
24
Abstra
Abstra
Securely authenticate users with SSO or SAML providers and manage permissions to any app with advanced, custom granular control. Securely authenticate users with SSO or SAML providers and manage permissions to any app with advanced, custom granular control. Deploy on-premise to benefit from our fast-building tools while ensuring every piece of data stays within your network. Be that for customer-facing or internal processes, make sure your onboarding has the perfect fit. Integrate to your favorite services or manage it all inside Abstra. Skip error-prone, repetitive work by creating automated tasks. Combine dynamic forms and workflows to streamline information gathering, reminders and transactions. Save time and guarantee your data quality and transparency by automating your reconciliation workflow. -
25
3LC
3LC
Light up the black box and pip install 3LC to gain the clarity you need to make meaningful changes to your models in moments. Remove the guesswork from your model training and iterate fast. Collect per-sample metrics and visualize them in your browser. Analyze your training and eliminate issues in your dataset. Model-guided, interactive data debugging and enhancements. Find important or inefficient samples. Understand what samples work and where your model struggles. Improve your model in different ways by weighting your data. Make sparse, non-destructive edits to individual samples or in a batch. Maintain a lineage of all changes and restore any previous revisions. Dive deeper than standard experiment trackers with per-sample per epoch metrics and data tracking. Aggregate metrics by sample features, rather than just epoch, to spot hidden trends. Tie each training run to a specific dataset revision for full reproducibility. -
26
GaiaNet
GaiaNet
The API approach allows any agent application in the OpenAI ecosystem, which is 100% of AI agents today, to use GaiaNet as an alternative to OpenAI. Furthermore, while the OpenAI API is backed by a handful of models to give generic responses, each GaiaNet node can be heavily customized with a finetuned model supplemented by domain knowledge. GaiaNet is a decentralized computing infrastructure that enables everyone to create, deploy, scale, and monetize their own AI agents that reflect their styles, values, knowledge, and expertise. It allows individuals and businesses to create AI agents. Each GaiaNet node provides. A distributed and decentralized network of GaiaNodes. Fine-tuned large language models with private data. Proprietary knowledge base that individuals or enterprises have to improve the performance of the model. Decentralized AI apps that utilize the API of the distributed GaiaNet infrastructure. Offers personal AI teaching assistants, ready to enlighten at any place & time. -
27
Gemma 2
Google
A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content. -
28
ModelOp
ModelOp
ModelOp is the leading AI governance software that helps enterprises safeguard all AI initiatives, including generative AI, Large Language Models (LLMs), in-house, third-party vendors, embedded systems, etc., without stifling innovation. Corporate boards and C‑suites are demanding the rapid adoption of generative AI but face financial, regulatory, security, privacy, ethical, and brand risks. Global, federal, state, and local-level governments are moving quickly to implement AI regulations and oversight, forcing enterprises to urgently prepare for and comply with rules designed to prevent AI from going wrong. Connect with AI Governance experts to stay informed about market trends, regulations, news, research, opinions, and insights to help you balance the risks and rewards of enterprise AI. ModelOp Center keeps organizations safe and gives peace of mind to all stakeholders. Streamline reporting, monitoring, and compliance adherence across the enterprise. -
29
KaneAI
TestMu AI
Advanced AI-powered platform built on modern Large Language Models (LLMs). A unique approach to create, debug, and evolve end to end tests using natural language. Test generation & evolution effortlessly using natural language inputs, simplifying the testing process with intelligent automation. Intelligent test planner automatically generates and automates test steps using high-level objectives. Multi-language code export converts your automated tests in all major languages and frameworks. Convert your actions into natural language instructions to generate bulletproof tests. Express sophisticated conditions and assertions in natural language. As easy as conversing and communicating with your team. Convey the same instructions to KaneAI and watch it automate your tests. Generate your tests with just high-level objectives. Develop tests across your stack on both web and mobile devices for extensive test coverage. -
30
StackGen
StackGen
Generate context-aware, secure IaC from application code without code changes. We love infrastructure as code, but that doesn’t mean there isn’t room for improvement. StackGen uses an application’s code to generate consistent, secure, and compliant IaC. Remove bottlenecks, liabilities, and error-prone manual processes between DevOps, developers, and security to get your application to market faster. Allow developers a better, more productive experience without becoming infrastructure experts. Consistency, security, and policy guardrails are incorporated by default when IaC is auto-generated. Context-aware IaC is auto-generated, with no code changes required, supported, and rightsized with least-privileged access controls. No need to rebuild your pipelines. StackGen works alongside your existing workflows to remove silos between teams. Enable developers to auto-generate IaC that complies with your provisioning checklist.