1463 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
Claude Opus 4.5
Anthropic
Claude Opus 4.5 is Anthropic’s newest flagship model, delivering major improvements in reasoning, coding, agentic workflows, and real-world problem solving. It outperforms previous models and leading competitors on benchmarks such as SWE-bench, multilingual coding tests, and advanced agent evaluations. Opus 4.5 also introduces stronger safety features, including significantly higher resistance to prompt injection and improved alignment across sensitive tasks. Developers gain new controls through the Claude API—like effort parameters, context compaction, and advanced tool use—allowing for more efficient, longer-running agentic workflows. Product updates across Claude, Claude Code, the Chrome extension, and Excel integrations expand how users interact with the model for software engineering, research, and everyday productivity. Overall, Claude Opus 4.5 marks a substantial step forward in capability, reliability, and usability for developers, enterprises, and end users. -
2
Parallel Domain Replica Sim
Parallel Domain
Parallel Domain Replica Sim enables the creation of high-fidelity, fully annotated, simulation-ready environments from users’ own captured data (photos, videos, scans). With PD Replica, you can generate near-pixel-perfect reconstructions of real-world scenes, transforming them into virtual environments that preserve visual detail and realism. PD Sim provides a Python API through which perception, machine learning, and autonomy teams can configure and run large-scale test scenarios and simulate sensor inputs (camera, lidar, radar, etc.) in either open- or closed-loop mode. These simulated sensor feeds come with full annotations, so developers can test their perception systems under a wide variety of conditions, lighting, weather, object configurations, and edge cases, without needing to collect real-world data for every scenario. -
3
GPT-5.2
OpenAI
GPT-5.2 is the newest evolution in the GPT-5 series, engineered to deliver even greater intelligence, adaptability, and conversational depth. This release introduces enhanced model variants that refine how ChatGPT reasons, communicates, and responds to complex user intent. GPT-5.2 Instant remains the primary, high-usage model—now faster, more context-aware, and more precise in following instructions. GPT-5.2 Thinking takes advanced reasoning further, offering clearer step-by-step logic, improved consistency on multi-stage problems, and more efficient handling of long or intricate tasks. The system automatically routes each query to the most suitable variant, ensuring optimal performance without requiring user selection. Beyond raw intelligence gains, GPT-5.2 emphasizes more natural dialogue flow, stronger intent alignment, and a smoother, more humanlike communication style. -
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SMART TS XL
IN-COM Data Systems
SMART TS XL is an enterprise-grade application discovery and “software intelligence” platform that enables organizations to search, analyze, and visualize dependencies across all their codebases, regardless of platform or language. It ingests source code, database schemas, configuration files, documentation, ticketing logs, JCL, and other assets, from legacy mainframes (COBOL, JCL, PL/I, AS/400, etc.) to modern distributed environments (Java, .NET, Python, JavaScript, C++, databases, scripts, text files), and catalogs everything into a centralized, searchable repository. With patented indexing technology, SMART TS XL can process millions or even billions of lines of code and return results in seconds, allowing users to instantly locate where particular fields, error messages, modules, or logic are used enterprise-wide. It generates interactive visualizations like control-flow diagrams, cross-reference graphs, and impact-analysis maps. -
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Relevance Lab SPECTRA
Relevance Lab
SPECTRA is an AI-driven data analytics and integration platform designed to intelligently collect, harmonize, process, and move data across multiple systems so organizations can unlock business value from disparate data sources. It helps centralize data that is often spread across applications and geographies, enabling smoother functionality, faster insights, and reduced operational friction. SPECTRA supports advanced data extraction and management services, builds scalable data lakes that serve as a single source of truth, and modernizes data warehouses to improve speed, efficiency, and analytical capability. It can ingest structured and unstructured data and apply AI-enhanced analytics to help businesses derive actionable insights and improve decision-making across functions. By consolidating and standardizing data with tools such as optical character recognition and intelligent data labeling, SPECTRA accelerates analytics initiatives, enhances R&D and compliance efforts. -
6
BrainWave 6
3Brain AG
BrainWave 6 is an efficient, scalable electrophysiology software designed for recording, playback, and analysis of data from single- and multi-well high-density microelectrode arrays (HD-MEAs), providing unified tools to go from acquisition to insight with streamlined automation and enhanced analytics. It supports real-time visualization of HD-MEA data across up to 24 wells with full control of experimental setup and timing, and lets users navigate recordings, review raw or processed data, and annotate events directly within the software. BrainWave 6 offers hundreds of metrics for neuronal and cardiac activity, area-based intra-well segmentation for multi-spheroid and organoid analysis, and AI-enhanced spike detection. It is scalable for high-throughput workflows, compatible with all 3Brain systems, and supports robotic automation when paired with HyperCAM Delta. Additional modules enable automated long-term potentiation protocols with real-time readouts. -
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Grok 4.1 Thinking
SpaceXAI
Grok 4.1 Thinking is xAI’s advanced reasoning-focused AI model designed for deeper analysis, reflection, and structured problem-solving. It uses explicit thinking tokens to reason through complex prompts before delivering a response, resulting in more accurate and context-aware outputs. The model excels in tasks that require multi-step logic, nuanced understanding, and thoughtful explanations. Grok 4.1 Thinking demonstrates a strong, coherent personality while maintaining analytical rigor and reliability. It has achieved the top overall ranking on the LMArena Text Leaderboard, reflecting strong human preference in blind evaluations. The model also shows leading performance in emotional intelligence and creative reasoning benchmarks. Grok 4.1 Thinking is built for users who value clarity, depth, and defensible reasoning in AI interactions. -
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GPT-5.2-Codex
OpenAI
GPT-5.2-Codex is OpenAI’s most advanced agentic coding model, built for complex, real-world software engineering and defensive cybersecurity work. It is a specialized version of GPT-5.2 optimized for long-horizon coding tasks such as large refactors, migrations, and feature development. The model maintains full context over extended sessions through native context compaction. GPT-5.2-Codex delivers state-of-the-art performance on benchmarks like SWE-Bench Pro and Terminal-Bench 2.0. It operates reliably across large repositories and native Windows environments. Stronger vision capabilities allow it to interpret screenshots, diagrams, and UI designs during development. GPT-5.2-Codex is designed to be a dependable partner for professional engineering workflows. -
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trail
trail
Trail ML is an AI governance copilot platform that helps organizations build trustworthy, compliant, and transparent AI systems by automating manual governance and documentation tasks. It centralizes AI registry, policy creation, risk management, automated documentation, development tracking, audit trails, and compliance workflows under one system, enabling teams to classify and manage all AI use cases, trace decisions from data and model to outcomes, and reduce the overhead of manual documentation and governance processes. It integrates governance frameworks and templates, supports creation of custom AI policies, and guides teams through identifying and mitigating risks, preparing for audits and standards like ISO 42001 and regulation such as the EU AI Act. Trail uses curated knowledge, risk libraries, and AI-powered automation to orchestrate governance tasks, translate regulatory requirements into actionable to-dos, and streamline collaboration between stakeholders. -
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E-ICEBLUE
E-ICEBLUE
E-iceblue provides a comprehensive suite of professional development libraries and APIs designed to enable developers to create, read, write, edit, convert, print, manipulate and view a wide range of document formats programmatically across multiple programming environments without relying on external applications like Microsoft Office or Adobe Acrobat. Its product range includes Spire.Office and individual components for .NET platforms (such as Spire.Doc, Spire.XLS, Spire.Presentation, Spire.PDF, Spire.Barcode, Spire.Email and Spire.OCR) that handle Word, Excel, PowerPoint, PDF, barcode generation and email operations in C#, VB.NET, ASP.NET, .NET Core, Xamarin and WPF applications, plus viewer libraries for embedded document display. E-iceblue also offers equivalent APIs for Java, C++, Python and JavaScript, as well as mobile and cloud libraries (including Spire.Cloud.Office with HTML5 browser support for Word and Excel), supporting document processing tasks. -
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TURBOARD
TURBOARD
TURBOARD is a comprehensive business intelligence and data analytics tool that brings scattered business data together into unified, visual dashboards and reports with an intuitive drag-and-drop interface and conversational AI assistant to make analysis fast and accessible. It lets users connect to all major data sources, automatically transform raw data into clear charts, scorecards, and key performance indicators, and explore insights using built-in AI by asking questions in natural language. TURBOARD supports advanced analytics including predictive modeling, trend tracking, SQL-based expressions, extended filtering, what-if simulations, spreadsheet-like calculations, and geospatial visualization with interactive map layers. It also offers flexible export options, conditional formatting, customizable themes, and integration capabilities for embedding dashboards into external systems. -
12
LightningChart
LightningChart
LightningChart is a high-performance data visualization framework designed for building real-time, data-intensive applications. It provides GPU-accelerated charting components capable of rendering massive datasets with exceptional speed and precision. LightningChart supports modern application development across web, desktop, mobile, cloud, IoT, and embedded environments. The framework uses advanced graphics technologies such as WebGL and DirectX to ensure ultra-fast rendering and smooth user interaction. Developers can create customizable dashboards and visualizations without compromising performance. LightningChart offers extensive chart types, templates, and examples to accelerate development. Overall, it enables organizations to build visually stunning, mission-critical data visualization applications. -
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ProVision
IPv4.Global
ProVision is an API-first, multi-tenant, multi-cloud network automation software that simplifies planning, provisioning, assigning, allocating, and managing modern network infrastructure by automating DNS, DHCP, and IP address management workflows and reducing complexity at scale. It offers a unified DDI (DNS, DHCP, IPAM) solution with comprehensive IPv4 and IPv6 support, including subnet allocation and host-level assignments, advanced features such as VRF and VLAN management, and dynamic tagging, templates, and rules to handle topology-aware assignments. ProVision integrates seamlessly with existing tools and infrastructure through a rich Connector Library and REST API, enabling smooth automation across hybrid and distributed environments without requiring data migration. It includes modules for IP address management with overlapping and duplicate space support, DHCP controllers with multi-vendor integration, and DNS controllers with granular role-based permissions. -
14
Qualisys Track Manager
Qualisys
Qualisys Track Manager (QTM) is a user-friendly motion capture software that serves as the central platform for capturing, processing, and managing movement data with Qualisys systems, supporting precise 2D, 3D, and 6DOF tracking of markers, rigid bodies, and skeletal models in real time with low latency. It integrates and synchronizes seamlessly with external hardware such as force plates, EMG devices, eye trackers, video, and IMUs, and it can stream data in real time to third-party applications through built-in real-time server and SDK support while also handling calibration, system setup, and trajectory editing within a single intuitive interface. QTM’s advanced motion capture algorithms and robust inverse kinematics solver handle occlusions and multi-actor scenarios, and its trajectory editor, automatic marker identification (AIM), labeling, filtering, gap filling, and measurement tools make data processing efficient. -
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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. -
18
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. -
21
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. -
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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. -
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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. -
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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. -
42
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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Gemini 3.5 Pro
Google
Gemini 3.5 Pro is Google’s anticipated next-generation Pro model in the Gemini 3.5 series, designed for advanced reasoning, coding, multimodal understanding, and agentic workflows. It is expected to build on Google’s Gemini 3 family with stronger performance for complex tasks that require planning, context handling, tool use, and deep problem solving. The model is aimed at users who need more power than faster Flash models for demanding development, research, automation, and enterprise AI use cases. Gemini 3.5 Pro is expected to support sophisticated workflows across text, code, files, multimodal inputs, and connected tools. Developers and organizations will likely use it through Google’s AI platforms for building assistants, agents, coding tools, analysis systems, and productivity applications. As an upcoming Pro-tier model, Gemini 3.5 Pro is positioned for high-value workloads where accuracy, reasoning quality, and advanced task execution matter more than maximum speed. -
44
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. -
45
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. -
46
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. -
47
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. -
48
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. -
49
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. -
50
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.