1504 Integrations with Python
View a list of Python integrations and software that integrates with Python below. Compare the best Python integrations as well as features, ratings, user reviews, and pricing of software that integrates with Python. Here are the current Python integrations in 2026:
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1
Draftt
Draftt
Draftt is a proactive tech stack governance software that continuously monitors every component’s lifecycle and configuration across clouds, workloads, runtimes, and code to help teams stay ahead of technical debt and avoid unexpected end-of-life risks. It provides full-stack visibility with a unified control plane that maps all technologies, versions, dependencies, and Kubernetes clusters in one place, replacing manual audits and static spreadsheets with live inventory and context. Draftt uses secure, read-only integrations with cloud and developer tools to collect lifecycle metadata, detect version drift, and identify compatibility conflicts early. With AI-driven prioritization and impact scoring, it highlights upgrade risks based on urgency, effort, and business impact, and generates detailed remediation plans tailored to your environment. It delivers structured, step-by-step upgrade paths, prebuilt actions, and automated workflows that can be executed directly from Draftt. -
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Shadeform
Shadeform
Shadeform is a GPU cloud marketplace that provides a single platform, unified console, and API for finding, comparing, launching, and managing on-demand GPU instances across numerous cloud providers, making it easier to develop, train, and deploy AI models without juggling multiple accounts or provider interfaces. It lets users view live pricing and availability for GPUs across clouds, launch instances in either their own cloud accounts or in Shadeform-managed accounts, and manage a cross-cloud fleet from one place with standardized tooling such as curl, Python, or Terraform. It aggregates GPU capacity and pricing data so teams can optimize compute spend, deploy containerized workloads with consistent interfaces, centralize billing and account management, and avoid vendor-specific complexity by using a unified API that supports multiple providers. Shadeform also offers scheduling and automated provisioning so that users can secure resources when they become available.Starting Price: $0.15 per hour -
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NexaSDK
NexaSDK
Nexa SDK is a unified developer toolkit that lets you run and ship any AI model locally on virtually any device with support for NPUs, GPUs, and CPUs, offering seamless deployment without needing cloud connectivity; it provides a fast command-line interface, Python bindings, mobile (Android and iOS) SDKs, and Linux support so you can integrate AI into apps, IoT devices, automotive systems, and desktops with minimal setup and one line of code to run models, while also exposing an OpenAI-compatible REST API and function calling for easy integration with existing clients. Powered by the company’s custom NexaML inference engine built from the kernel up for optimal performance on every hardware stack, the SDK supports multiple model formats including GGUF, MLX, and Nexa’s proprietary format, delivers full multimodal support for text, image, and audio tasks (including embeddings, reranking, speech recognition, and text-to-speech), and prioritizes Day-0 support for the latest architectures. -
4
EasyOCR
EURESYS
Euresys EasyOCR is an optical character recognition software library within the Open eVision suite that provides teachable, template-based printed text recognition designed to read short text such as part numbers, serial numbers, expiry dates, manufacturing dates, and lot codes from images or parts in machine vision applications; it uses a font-dependent template matching algorithm that can be trained with custom character examples and comes with pre-defined fonts, enabling reliable recognition even when characters vary in size, are poorly printed, broken, or connected, and supports separation of adjacent text elements in challenging conditions. It is size-invariant and rapid, and can be trained on sample images to build a character database (font) that improves recognition performance for specific industrial text styles. EasyOCR is typically embedded into vision inspection systems via the Open eVision API. -
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ContextForge MCP Gateway is an open source Model Context Protocol (MCP) gateway, registry, and proxy platform that provides a unified endpoint for AI clients to discover and access tools, resources, prompts, and REST or MCP services in complex AI ecosystems. It sits in front of multiple MCP servers and REST APIs to federate and unify discovery, authentication, rate-limiting, observability, and traffic routing across diverse backends, with support for transports such as HTTP, JSON-RPC, WebSocket, SSE, stdio, and streamable HTTP, and can virtualize legacy APIs as MCP-compliant tools. It includes an optional Admin UI for real-time configuration, monitoring, and log visibility, and is designed to scale from standalone deployments to multi-cluster Kubernetes environments with Redis-backed federation and caching for performance and resilience.
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GPT-5.3-Codex
OpenAI
GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, designed to handle complex professional work on a computer. It combines frontier-level coding performance with advanced reasoning and real-world task execution. The model is faster than previous Codex versions and can manage long-running tasks involving research, tools, and deployment. GPT-5.3-Codex supports real-time interaction, allowing users to steer progress without losing context. It excels at software engineering, web development, and terminal-based workflows. Beyond code generation, it assists with debugging, documentation, testing, and analysis. GPT-5.3-Codex acts as an interactive collaborator rather than a single-turn coding tool. -
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Strategy Mosaic
Strategy Software
Strategy Mosaic is an AI-powered universal semantic data layer and analytics foundation that sits on top of an organization’s existing data systems to unify, govern, and accelerate access to business data for analytics, AI, and reporting without costly restructuring. It creates a single source of truth with consistent business definitions, metrics, and security policies across tools and sources, harmonizing data from hundreds of systems so insights are reliable and comparable everywhere. Built with AI-assisted data modeling (Mosaic Studio), Mosaic automates data preparation, cleansing, enrichment, and modeling, reducing the time and effort needed to build robust data products and semantic models. Its universal connectors let users access governed data via SQL, REST, Python, or through popular BI and productivity tools like Power BI, Tableau, Excel, and Google Sheets, while an in-memory acceleration engine delivers fast query performance across diverse sources. -
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Gemini 3.1 Pro
Google
Gemini 3.1 Pro is Google’s upgraded core intelligence model designed for complex tasks that require advanced reasoning. Building on the Gemini 3 series, it delivers significant improvements in problem-solving performance and logical pattern recognition. On the ARC-AGI-2 benchmark, Gemini 3.1 Pro achieved a verified score of 77.1%, more than doubling the reasoning performance of Gemini 3 Pro. The model is engineered for challenges where simple answers are insufficient, enabling deeper analysis, synthesis, and creative output. It can generate practical outputs such as animated, website-ready SVGs directly from text prompts, combining intelligence with real-world usability. Gemini 3.1 Pro is rolling out in preview across consumer, developer, and enterprise platforms including the Gemini app, NotebookLM, Gemini API, Gemini Enterprise Agent Platform, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for agentic workflows. -
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Code Metal
Code Metal
CodeMetal is an AI-enabled code translation and deployment platform designed to help engineering teams automatically convert high-level reference code into optimized, hardware-specific implementations for edge and embedded environments. It allows developers to write algorithms in familiar languages such as Python, MATLAB, or Julia and then automatically generates low-level code tailored to the target runtime, including embedded C/C++, Rust, CUDA, or FPGA languages. Its agentic workflow analyzes module dependencies, maps equivalents across architectures, and produces a transpilation and deployment plan that developers can review or execute directly. CodeMetal emphasizes verifiable AI by combining generative techniques with formal methods to ensure translated code is tested, compliant, and production-ready, addressing the reliability concerns common in safety-critical industries. -
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Gemini 3.1 Flash-Lite
Google
Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building. -
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GPT-5.3 Instant
OpenAI
GPT-5.3 Instant is an updated version of ChatGPT’s most-used model, designed to make everyday conversations more fluid, helpful, and accurate. The release focuses on improving tone, relevance, and conversational flow based directly on user feedback. It reduces unnecessary refusals and cuts back on overly cautious disclaimers, delivering clearer and more direct answers when appropriate. The model also improves how it integrates web results, providing better-contextualized information rather than long lists of loosely connected links. Accuracy has been strengthened, with measurable reductions in hallucinations across both high-stakes domains and everyday queries. GPT-5.3 Instant enhances creative writing capabilities, producing more textured, emotionally resonant prose. It is available to all ChatGPT users and developers via the API under ‘gpt-5.3-chat-latest,’ with legacy versions scheduled for retirement. -
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GPT-5.4 Pro
OpenAI
GPT-5.4 Pro is an advanced AI model developed by OpenAI to deliver high-performance capabilities for professional and complex tasks. It combines improvements in reasoning, coding, and agent-based workflows into a single unified system. The model is designed to work efficiently across professional tools such as spreadsheets, presentations, documents, and development environments. GPT-5.4 Pro also includes native computer-use capabilities, enabling AI agents to interact with software, websites, and operating systems to complete tasks. With support for up to one million tokens of context, it can manage long workflows and large datasets more effectively than previous models. The model also improves tool usage, allowing it to search for and select the right tools during multi-step processes. By delivering more accurate outputs with fewer tokens, GPT-5.4 Pro helps professionals complete complex work faster and more efficiently. -
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GPT‑5.4 Thinking
OpenAI
GPT-5.4 Thinking is an advanced reasoning-focused AI model available within ChatGPT, designed to help users complete complex professional tasks more effectively. It combines improvements in reasoning, coding, and agent-based workflows to provide more accurate and reliable outputs. The model can present an upfront outline of its reasoning process, allowing users to adjust instructions while it is generating a response. This capability helps produce results that better align with user goals without requiring multiple follow-up prompts. GPT-5.4 Thinking also improves deep web research, enabling it to locate and synthesize information from multiple sources more efficiently. With stronger context management, it can handle longer conversations and complex problem-solving tasks with greater coherence. These capabilities make GPT-5.4 Thinking well suited for professional knowledge work and advanced analytical tasks. -
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Factify
Factify
Factify is a document technology platform designed to transform traditional digital files into intelligent, governed records built for the age of artificial intelligence. Instead of treating documents as static files such as PDFs, it introduces a “Document-as-Infrastructure” model in which each document becomes an active, managed asset containing built-in identity, permissions, version history, and automation capabilities. These intelligent documents remain controlled and traceable wherever they are shared, allowing organizations to track who accessed them, manage authorization, and maintain a single authoritative version even after distribution. Unlike conventional files that lose governance once sent outside an organization, Factify documents retain embedded access control and contextual information that can be updated or restricted in real time. -
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GPT-5.4 mini
OpenAI
GPT-5.4 mini is a fast and efficient AI model designed for high-performance tasks such as coding, reasoning, and multimodal understanding. It delivers strong capabilities similar to larger models while maintaining lower latency and cost. The model is optimized for responsive applications where speed is critical, including coding assistants and real-time workflows. GPT-5.4 mini supports advanced features such as tool use, function calling, and image interpretation. It performs well on complex tasks while running significantly faster than previous mini models. The model is also suitable for subagent systems, where it handles smaller tasks within larger AI workflows. By combining speed, efficiency, and strong performance, GPT-5.4 mini enables scalable AI applications across various use cases. -
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GPT-5.4 nano
OpenAI
GPT-5.4 nano is a lightweight and highly efficient AI model designed for fast, cost-effective task execution. It is optimized for simple and high-volume tasks such as classification, data extraction, and basic coding support. The model delivers quick responses with minimal latency, making it ideal for real-time and large-scale applications. GPT-5.4 nano improves significantly over previous nano models in both performance and efficiency. It supports essential capabilities like tool use and structured data processing. The model is commonly used as a supporting component within larger AI systems. By focusing on speed and affordability, GPT-5.4 nano enables scalable automation across various workflows. -
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Raven
Raven
Raven is a runtime application security platform designed to protect cloud-native applications by operating directly inside the application during execution, rather than relying on external defenses. It provides real-time visibility into how code actually runs, allowing it to understand execution flows, libraries, and function-level behavior in order to detect and stop malicious activity before it occurs. Unlike traditional tools such as WAF or EDR that monitor from the outside, Raven embeds itself within the application, enabling it to prevent exploits, supply chain attacks, and zero-day threats even when no known vulnerability or CVE exists. It continuously monitors runtime behavior, identifies abnormal patterns or misuse of legitimate logic, and responds immediately to block harmful execution. It also helps teams prioritize security efforts by filtering out the majority of irrelevant vulnerabilities and focusing only on those that are truly exploitable. -
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Open Wallet
Open Wallet
OpenWallet is an open standard designed for secure local wallet storage and seamless agent access, providing a unified interface that works across all blockchain networks, tools, and autonomous agents. It focuses on simplifying how digital wallets interact with modern systems by creating a consistent layer that allows developers and AI agents to access, manage, and utilize wallet data locally without relying on fragmented integrations. The standard enables interoperability across multiple chains, ensuring that a single interface can handle different blockchain environments without requiring custom implementations for each one. By prioritizing local storage, it enhances security and control, reducing exposure to external vulnerabilities while allowing direct interaction between wallets and applications. OpenWallet is built to support emerging agent-based ecosystems, where AI tools and automation systems need reliable, standardized access to financial or blockchain assets. -
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ProxyLite
ProxyLite
ProxyLite is a residential proxy and web data collection platform that provides access to a large global network of over 72 million real IP addresses across more than 190 locations, enabling users to collect public data, automate workflows, and access localized content without being blocked. It offers multiple proxy types, including rotating residential proxies, static residential proxies, datacenter proxies, and ISP proxies, all designed to deliver high anonymity, fast response times, and stable connections for large-scale operations. It supports unlimited sessions and high concurrency, allowing users to send frequent requests without bandwidth or usage restrictions, while maintaining a reported high success rate and uptime for consistent performance. It includes an all-in-one web scraping API that simplifies data extraction by handling request routing, IP rotation, and response processing within a single interface. -
20
Simaril
Simaril
Silmaril is a self-healing prompt injection defense designed to protect AI systems from increasingly complex, multi-step attacks that traditional guardrails fail to stop. It operates by wrapping inference calls and evaluating whether an execution sequence is leading toward a harmful outcome, rather than simply filtering inputs. It uses a multihead classifier that analyzes user intent, application context, and execution states together, enabling it to detect indirect injection, multi-turn attack chains, context poisoning, and tool abuse before damage occurs. Silmaril continuously strengthens its defenses through autonomous threat hunting agents that probe systems, discover vulnerabilities, and generate synthetic training data from real attack scenarios. These insights are used to retrain the model automatically, deploying updated protections in under an hour and propagating anonymized defenses across all deployments. -
21
LakeSail
LakeSail
LakeSail is a unified, cloud-native data and AI platform designed to transform how organizations process, analyze, and act on large-scale data by combining all workloads into a single, high-performance system. At its core is Sail, a Rust-native distributed computation engine that serves as a drop-in replacement for Apache Spark, enabling teams to run existing SQL and Python workloads without rewriting code while eliminating JVM overhead and improving efficiency. It unifies batch processing, stream processing, ad-hoc queries, and AI workloads into one runtime, allowing data pipelines and intelligent systems to operate seamlessly on the same infrastructure. It introduces a multimodal lakehouse architecture capable of handling structured and unstructured data, including PDFs, images, and video, within a single environment, making it suitable for modern AI-driven use cases. -
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GraphBit
GraphBit
GraphBit is an enterprise-grade agentic AI framework built to run critical AI systems with security, governance, and predictable production performance. It combines a Rust execution core with a Python wrapper to give developers high-performance orchestration with the accessibility of Python, helping teams build reliable multi-agent workflows with minimal CPU and memory usage. GraphBit is designed around the layers that reduce risk, including interfaces, configuration, models, tools, actions, memory, orchestration, and observability. It integrates into existing apps, powers custom AI interfaces, and lets users interact through familiar workflows with controlled actions. Teams can define policies, rules, and guardrails centrally, while GraphBit enforces behavior without changing application code. It supports LLMs and multimodal models from multiple providers, allowing teams to swap models freely without breaking workflows or governance. -
23
Kelviq
Kelviq
Kelviq is the home of global software monetization, bringing payments, usage billing, tax, and Merchant of Record into one system built for SaaS and AI companies. It gives teams one platform for payments, tax, pricing, and feature access, so they can sell globally without stitching together billing infrastructure. Kelviq supports flexible pricing models, including flat fee, per seat, usage, volume, credits, one-time payments, overages, and hybrid pricing. It also unifies checkout, real-time usage metering, entitlements, tax compliance, and global payments, allowing teams to run subscriptions, usage, and one-time payments side by side while keeping invoices synced to real usage. Businesses can meter API calls, tokens, AI agents, storage, compute units, active users, or custom units in real time, with invoice line items linked back to raw event logs. -
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SAS Studio
SAS
SAS Studio provides a web browser-based programming environment, so writing and interacting with SAS code is easier and faster, wherever you are. It helps teams build efficient data pipelines with a data engineering experience designed for seamless collaboration, low-code work, and open source integration. SAS Studio connects to leading cloud data platforms such as AWS Redshift and S3, Google BigQuery and Cloud Storage, and Azure Data Lake Storage, as well as relational and nonrelational databases, including Oracle, Snowflake, Teradata, SingleStore, MongoDB, and other sources. It also works with file formats such as Excel, text, Parquet, and ORC. Users can choose no code, low code, or code by creating end-to-end data pipelines with drag-and-drop steps, developing Python and SAS code assets in SAS Studio or another IDE, and embedding them into SAS Studio flows for secure, centralized access to data sources and governed execution. SAS Studio supports ELT and ETL approaches. -
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3PO
Dualboot Partners
3PO Code Translator helps transform legacy software into modern technology by migrating outdated systems to modern technology stacks with an AI-powered legacy code translator. It is designed for legacy platforms, proprietary languages, outdated trading systems, back-office operations, and custom applications that need a seamless transition to modern languages and platforms. 3PO analyzes and interprets legacy code using advanced algorithms and machine learning capabilities, streamlining translation with accuracy, efficiency, and precision every step of the way. It works from source code, documentation, and requirements to generate scaffolding and new source code, helping teams turn legacy software into a stronger business asset. Its translation process preserves existing functionality while enhancing performance, documenting legacy code, suggesting structures for the migrated application, and providing suggested code. -
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PromptUnit
PromptUnit
PromptUnit is an AI inference proxy that reduces AI costs automatically by sitting between an app and its AI providers with no code changes required. Teams swap the base URL, keep the same SDK, endpoints, response parsing, and error handling, then PromptUnit handles routing, failover, cost tracking, and quality validation. It logs every API call by model, feature, user segment, token count, latency, and cost, giving real-time visibility into where AI spend is going before any routing changes go live. In observation mode, PromptUnit watches traffic, shadow-classifies requests, forecasts savings, and explains routing decisions so teams can see exact savings before enabling live routing. Once enabled, Smart Routing uses task classification to route each request to the cheapest model that clears the configured quality bar. PromptUnit also includes prompt compression, token inflation defense, prompt efficiency scoring, semantic request caching, and multi-model consensus. -
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Inquir Compute
Inquir Compute
Inquir Compute is a cloud platform for deploying and running server-side code without managing servers, Kubernetes, CI/CD, or DevOps infrastructure. It lets developers create functions, APIs, webhooks, cron jobs, background tasks, and multi-step workflows directly from a browser-based editor or API. Users can write code in Node.js, Python, or Go, configure runtime settings such as memory, CPU, timeout, environment variables, and network access, then deploy and invoke it in isolated containers. Functions can be exposed through an API Gateway, triggered manually, scheduled, or combined into pipelines where one step passes data to another. The platform is designed for long-running workloads such as AI agents, scraping, document processing, data enrichment, integrations, and automation. It includes logs, traces, invocation history, error tracking, route management, API keys, tenant isolation, and observability tools. -
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Google GenAI SDK
Google
The Gemini API libraries provide official, production-ready Google GenAI SDKs for building with the Gemini API in popular programming languages. Google recommends using the Google GenAI SDK when building with Gemini, since these libraries are developed and maintained by Google, used across official documentation and examples, and are generally available for production use. The SDKs are available for Python, JavaScript/TypeScript, Go, Java, and C#, with installation through standard package managers such as pip install google-genai, npm install google/genai, Maven dependencies for google genai, and dotnet add package Google GenAI. They provide access to the latest Gemini API features and are designed to offer the best performance when working with Gemini models. Google strongly recommends migrating from legacy libraries to the new Google GenAI SDK because the legacy libraries are not actively maintained. -
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Qwen3.7-Plus
Alibaba
Qwen3.7-Plus is a multimodal agent model that unifies vision and language into a single, versatile agent foundation. Building on Qwen3.7’s agentic intelligence, it extends Qwen’s capabilities into visual understanding, visual reasoning, grounded interaction, and multimodal tool use, enabling agents to perceive, analyze, and act across text, images, documents, screens, and complex real-world contexts. It is designed for tasks that require more than static question answering, including visual search, document comprehension, chart and table analysis, screen understanding, GUI interaction, image-grounded reasoning, and agent workflows that combine perception with planning and execution. Qwen3.7-Plus strengthens the connection between language reasoning and visual evidence, allowing users to ask questions about images, interpret dense multimodal inputs, extract structured information, and generate responses that reflect both context and visual details. -
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Diom
Svix
Diom is a backend components platform for building robust services, offering a set of well-integrated infrastructure primitives for backend and data engineers, including caching, key-value storage, rate-limiting, idempotency, queues, and streams. It is designed so engineers no longer need to build fragile, slow, and hard-to-maintain solutions on top of Redis, Postgres, or other data stores, and can instead rely on powerful, performant, well-tested components built for common backend patterns. Diom can replace multiple services such as Redis, RabbitMQ, and Kafka for many use cases, reducing service dependencies, operational complexity, monitoring overhead, backups, configuration work, and deployment costs. Its components support low-latency operations, minimal round-trip, HTTP-based APIs, SDKs for popular languages, and deployment in common backend environments. -
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Gray Swan
Gray Swan
Gray Swan is an enterprise AI security and evaluation platform that helps organizations deploy AI with confidence by protecting LLM applications, agents, and model deployments from emerging threats, policy violations, and harmful content. It integrates with any LLM provider to add security without disrupting existing workflows, combining automated adversarial testing, continuous red teaming, runtime monitoring, and adaptive protections. Gray Swan tests beyond known attacks by using threat intelligence from 15,000+ adversarial researchers and more than three million attack attempts generated through its Arena, helping teams discover vulnerabilities before they appear in public databases. Its core products include Shade, an advanced AI vulnerability assessment platform that continuously probes LLMs like a security researcher working 24/7, and Cygnal, a runtime monitoring and protection layer for AI interactions. -
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Rapidminer AI Studio
Siemens
RapidMiner AI Studio is a dedicated environment for rapidly developing and prototyping AI solutions, helping teams unify the complete data science lifecycle from data exploration and machine learning to model operations and visualization. It allows data scientists and engineers to build, train, and test AI models locally, giving organizations full control and flexibility for initial exploration and development. It connects directly to enterprise data sources, including files, databases, data lakes, cloud data platforms, warehouses, SQL databases, and Internet of Things data streams, helping teams unify data, prevent errors, and power accurate, explainable AI. RapidMiner AI Studio supports both domain experts and technical teams: users without coding experience can quickly build effective machine learning models with an intuitive drag-and-drop canvas, while data scientists can create complex models in a fully integrated notebook environment using Python and R. -
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CapRover
CapRover
CapRover is a scalable, free, and self-hosted platform as a service built to make app, database, and web server management extremely easy. It is designed for Node.js, Python, PHP, ASP.NET, Ruby, MySQL, MongoDB, Postgres, WordPress, and many other applications, giving developers a simple way to move from localhost to a live HTTPS domain in seconds. CapRover is blazingly fast and very robust because it uses Docker, Nginx, Let’s Encrypt, and NetData under the hood, while keeping the experience simple through a web GUI and a CLI for automation and scripting. It helps developers avoid spending hours setting up servers, build tools, SSL certificates, Nginx rules, and deployment scripts, so they can focus more on writing application code and less on server work. It supports any language, one-click apps, free SSL with automatic HTTP-to-HTTPS redirection, and several deployment methods, including uploading source from the dashboard, using the CapRover deploy command. -
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Easypanel
Easypanel
Easypanel is a next-generation server control panel powered by Docker, built to deploy applications, manage databases, and provision SSL certificates through an intuitive interface. Unlike many other panels, Easypanel can run any application, creating Docker images for Node.js, Ruby, Python, PHP, Go, and Java apps using Heroku Buildpacks, while still allowing users to bring their own Dockerfile when they need greater control. Developers can push to GitHub and let Easypanel get the code, build it, and deploy it automatically, with support for zero-downtime deployments so updates happen seamlessly without interruptions for users. It also supports Cloud Native Buildpacks, Paketo Buildpacks, Nixpacks, and Dockerfile-based builds, giving teams several ways to turn source code into Docker images. Databases are first-class citizens in Easypanel, with support for MySQL, PostgreSQL, MongoDB, and Redis, plus web-based tools to inspect logs or connect to the database CLI. -
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Concentrate AI
Concentrate AI
Concentrate AI is the LLM gateway for fast-growing teams, one API for every major LLM provider, with routing, spend, logs, and controls in one place. It helps teams securely access, use, and manage AI through a single API, so every request can find the smarter, faster, cheaper model for the workflow or task. Teams can access 130+ models, benchmark speed, quality, and cost, and route each workload to the best fit without wiring separate provider APIs into every environment. Support bots, coding agents, internal tools, chat, and batch jobs do not need the same model or the same route, so Concentrate lets teams pick a model slug, limit allowed providers, sort by live latency, use fallbacks, and reroute traffic when a provider slows down, errors, or hits a rate limit. It also gives engineering, finance, security, and leadership a shared view of AI usage with request-level logs, models, provider, duration, token counts, spend, error rates, alerts, and exports. -
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Seed Audio 1.0
BytePlus
Seed Audio 1.0 is a non-streaming audio generation API based on HTTP, designed to generate complete audio from text prompts, reference audio, or reference images. It supports text-only generation, where audio is created directly from the prompt; reference-audio generation, where uploaded reference clips guide the output; and reference-image generation, where an image reference can be passed to generate audio from the text to be synthesized. Built as part of BytePlus Seed Speech, Audio 1.0 uses the seed-audio-1.0 model version and is positioned as an audio creation capability rather than a standard speech-only endpoint. It can generate voice, music, and sound effects in a single pass, making it useful for producing richer audio scenes without separately creating and mixing every track. The API is intended for developers building audio generation into applications, workflows, and production systems, with a request-based structure that lets teams submit prompts. -
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GPT-5.6 Sol Ultrafast
OpenAI
GPT-5.6 Sol Ultrafast is a new OpenAI API service tier that runs GPT-5.6 Sol up to 14× faster than Standard processing, bringing frontier intelligence to products and workflows where every second matters. Powered by Cerebras, it can generate up to 750 output tokens per second, allowing advanced reasoning to operate at real-time speeds without requiring a smaller or more specialized model. It is designed for time-sensitive business workflows where faster responses can change what AI can realistically do. Applications include incident response, where models can analyze logs, code changes, traces, and engineer reports while an outage is unfolding; financial research and security, where changing market signals and suspicious transactions can be assessed quickly; and customer support and voice, where complex issues can be resolved without interrupting a live conversation. In commerce, it can answer product questions, check inventory, and personalize recommendations. -
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Qwen3.8-2.4T-A95B
Alibaba
Qwen3.8-2.4T-A95B is the largest open model in the Qwen3.8 family, bringing Qwen-Max-class capabilities to an open release. Built on the architectural foundation of Qwen3.5, it delivers substantial improvements across coding, professional work, research, and long-horizon agentic tasks, with a focus on carrying complex, multi-step work through to completion more reliably. The causal language model uses a mixture-of-experts architecture with 2.4 trillion total parameters and 95 billion activated parameters, including 512 experts with 10 routed and one shared expert active at a time. It supports a native context length of 262,144 tokens that can be extended to approximately 1.01 million tokens. Agent execution is strengthened through better autonomous planning and improved handling of environment feedback, while broader compatibility with popular agent harnesses and development tools simplifies integration into existing stacks. -
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Gemini 3.8 Flash
Google
Gemini 3.8 Flash is Google’s most intelligent Flash workhorse model, delivering significant improvements over 3.7 Flash across software engineering, agentic tasks, and critical multi-step reasoning in specialized domains. Built for long-horizon coding and autonomous agents, it can solve complex engineering problems end to end and delivers the dependability required for critical enterprise autonomy across specialized knowledge domains. The model shows stronger performance in quantitative and professional fields that require advanced analysis and reporting, as well as multi-step reasoning across STEM, humanities, and professional subjects. Its gains stem from a core design choice: Gemini 3.8 Flash works harder on complex tasks, executing additional reasoning steps and calling tools iteratively to maximize performance. At higher effort levels, it may use more tokens to pursue stronger results, while developers can select lower effort levels. -
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Gemini 3.8 Flash Cyber
Google
Gemini 3.8 Flash Cyber is Google’s most capable cybersecurity model, providing frontier-level performance in vulnerability detection and automated patching with the speed needed for quick iteration. It is designed specifically for trusted defenders and is available through the Fairwind Program. On CyberGym, a standard industry benchmark for finding vulnerabilities, the model demonstrates frontier-level autonomous vulnerability discovery and surpasses both Gemini 3.5 Flash Cyber and significantly larger frontier models. Google also evaluated it on an internal benchmark covering complex codebases across 20 programming languages, where it achieved a success rate exceeding 70% in discovering a wide range of vulnerabilities. Gemini 3.8 Flash Cyber prioritizes vulnerability fixing over offensive capabilities such as exploitation, equipping defenders with expert capabilities that can help them maintain an advantage over attackers. -
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oMLX
oMLX
oMLX is a macOS-native MLX server designed to make local AI faster and more practical on Apple Silicon. Built for the way coding agents actually work, it uses paged SSD KV caching to persist cache blocks to disk, allowing previously seen prefixes to be restored across requests and server restarts instead of being recomputed from scratch. This can reduce time to first token on long contexts from 30–90 seconds to under five seconds after the first turn. Continuous batching handles concurrent requests through mlx-lm’s BatchGenerator, improving generation throughput without forcing requests to wait behind a single job. oMLX can serve LLMs, vision-language models, embedding models, and rerankers simultaneously, using LRU eviction when memory runs low. It supports any MLX-format model from Hugging Face, including Qwen, LLaMA, Mistral, Gemma, DeepSeek, MiniMax, and GLM, and can reuse models already stored in the standard Hugging Face cache, LM Studio folders, or custom directories. -
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Grok 4.8
SpaceXAI
Grok 4.8 is an upcoming AI model from xAI expected to advance the Grok family in reasoning, coding, agentic workflows, and professional knowledge work. Elon Musk has described the model as having approximately 2.5 trillion parameters and being trained using a new C++ software stack. The model is expected to complete its initial training before entering reinforcement learning, with final capabilities and performance still subject to change. Grok 4.8 is anticipated to build on Grok 4.7’s strengths in software development, tool calling, configurable reasoning, multimodal input, and long-running agentic tasks. xAI has not yet released official benchmarks, pricing, context-window specifications, API identifiers, or a public launch date for Grok 4.8. The model is expected to target developers, researchers, enterprises, and advanced AI users who need high-capability reasoning and autonomous task execution. -
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Earthly Lunar
Earthly Lunar
Earthly Lunar is a guardrails engine for engineering teams that turns wikis, AI prompts, AGENTS.md files, infrastructure rules, checklists, compliance requirements, and postmortem findings into deterministic enforcement across code repositories and CI/CD. It watches code and CI/CD systems to collect SDLC data from source and configuration files, dependencies, test results, IaC, deployment configurations, security scans, SBOMs, build scripts, API specs, and more, then normalizes that information into a structured view of each application. Guardrails-as-code continuously evaluate the data against an organization’s engineering standards and provide real-time feedback on every code change. The same policies can run during AI-assisted authoring, on pull requests, and at deployment gates, with enforcement ranging from visibility and PR comments to blocking non-compliant changes. -
44
Checkmarx
Checkmarx
The Checkmarx Software Security Platform provides a centralized foundation for operating your suite of software security solutions for Static Application Security Testing (SAST), Interactive Application Security Testing (IAST), Software Composition Analysis (SCA), and application security training and skills development. Built to address every organization’s needs, the Checkmarx Software Security Platform provides the full scope of options: including private cloud and on-premises solutions. Allowing a range of implementation options ensures customers can start securing their code immediately, rather than going through long processes of adapting their infrastructure to a single implementation method. The Checkmarx Software Security Platform transforms the standard for secure application development, providing one powerful resource with industry-leading capabilities. -
45
gedit
The GNOME Project
gedit is the text editor of the GNOME desktop environment. The first goal of gedit is to be easy to use, with a simple interface by default. More advanced features are available by enabling plugins. A flexible plugin system which can be used to dynamically add new advanced features. -
46
CodePatrol
Claranet
Automated code reviews driven by security. CodePatrol performs powerful SAST scans on your project source code and identifies security flaws early. Powered by Claranet and Checkmarx. CodePatrol provides support for a wide variety of languages and scans your code with multiple SAST engines for better results. Stay up-to-date with the latest code flaws in your project using automated alerting and user-defined filter rules. CodePatrol uses industry-leading SAST software provided by Checkmarx and expertise from Claranet Cyber Security to identify the latest threat vectors. Multiple code scanning engines are frequently triggered on your code base and perform in-depth analysis on your project. You may access CodePatrol anytime and retrieve the aggregated scan results in order to fix your project security flaws. -
47
CodePeer
AdaCore
The Most Comprehensive Static Analysis Toolsuite for Ada. CodePeer helps developers gain a deep understanding of their code and build more reliable and secure software systems. CodePeer is an Ada source code analyzer that detects run-time and logic errors. It assesses potential bugs before program execution, serving as an automated peer reviewer, helping to find errors easily at any stage of the development life-cycle. CodePeer helps you improve the quality of your code and makes it easier for you to perform safety and/or security analysis. CodePeer is a stand-alone tool that runs on Windows and Linux platforms and may be used with any standard Ada compiler or fully integrated into the GNAT Pro development environment. It can detect several of the “Top 25 Most Dangerous Software Errors” in the Common Weakness Enumeration. CodePeer supports all versions of Ada (83, 95, 2005, 2012). CodePeer has been qualified as a Verification Tool under the DO-178B and EN 50128 software standards. -
48
Jtest
Parasoft
Meet Agile development cycles while maintaining high-quality code. Use Jtest’s comprehensive set of Java testing tools to ensure defect-free coding through every stage of software development in the Java environment. Streamline Compliance With Security Standards. Ensure your Java code complies with industry security standards. Have compliance verification documentation automatically generated. Release Quality Software, Faster. Integrate Java testing tools to find defects faster and earlier. Save time and money by mitigating complicated and expensive problems down the line. Increase Your Return From Unit Testing. Achieve code coverage targets by creating a maintainable and optimized suite of JUnit tests. Get faster feedback from CI and within your IDE using smart test execution. Parasoft Jtest integrates tightly into your development ecosystem and CI/CD pipeline for real-time, intelligent feedback on your testing and compliance progress. -
49
CodeSonar
CodeSecure
CodeSonar employs a unified dataflow and symbolic execution analysis that examines the computation of the complete application. By not relying on pattern matching or similar approximations, CodeSonar's static analysis engine is extraordinarily deep, finding 3-5 times more defects on average than other static analysis tools. Unlike many software development tools, such as testing tools, compilers, configuration management, etc., SAST tools can be integrated into a team's development process at any time with ease. SAST technologies like CodeSonar simply attach to your existing build environments to add analysis information to your verification process. Like a compiler, CodeSonar does a build of your code using your existing build environment, but instead of creating object code, CodeSonar creates an abstract model of your entire program. From the derived model, CodeSonar’s symbolic execution engine explores program paths, reasoning about program variables and how they relate. -
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Codepad
Codepad
Codepad is a place for developers to share & save code snippets. It's a remarkable community of developers that can help you with your code snippets to save time on your projects. Share snippets with entire community. You can choose the programming language and the type of snippet: public, private or part private. Organise your code snippets in a beautiful way, easy add and categories them in collections. You can follow and control the snippets version. Don't lose the previous written code. If you are a freelancer or a company you can receive the job or collaboration offers directly to your registered email. Find the best developers on Codepad and follow their profile. You will see their new code snippets directly in your timeline.
