Business Software for Python - Page 38
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String.com
Pipedream
String is the first text-to-agent platform by Pipedream that lets you prompt, run, edit, and deploy AI agents in seconds, no drag-and-drop canvases, just natural language commands that generate production-ready code. Backed by Pipedream’s five years of experience building thousands of app integrations and Internet-scale agent infrastructure, String connects to over 2,700 APIs and embeds 10,000+ tools with managed authentication, so your agents can solve ten times more use cases than typical no-code builders. The intuitive web interface guides you through creating agents that monitor GitHub issues and automate ticket creation, schedule meetings, analyze data, send Slack messages, post to social media, update databases, and much more, all with full audit trails, customizable queues, and built-in data stores. Real-time dashboards display agent performance, logs, and metrics, while built-in security and privacy controls (SOC 2 Type II, ISO 27001, HIPAA, GDPR) ensure safe operation. -
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XBOW
XBOW
XBOW is an AI-powered offensive security platform that autonomously discovers, verifies, and exploits vulnerabilities in web applications without human intervention. By executing high-level commands against benchmark descriptions and reviewing outputs it solves a wide array of challenges, from CBC padding oracle and IDOR attacks to remote code execution, blind SQL injection, SSTI bypasses, and cryptographic exploits, achieving success rates up to 75 percent on standard web security benchmarks. Given only general instructions, XBOW orchestrates reconnaissance, exploit development, debugging, and server-side analysis, drawing on public exploits and source code to craft custom proofs-of-concept, validate attack vectors, and generate detailed exploit traces with full audit trails. Its ability to adapt to novel and modified benchmarks demonstrates robust scalability and continuous learning, dramatically accelerating penetration-testing workflows. -
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Grok 4 Heavy
xAI
Grok 4 Heavy is the most powerful AI model offered by xAI, designed as a multi-agent system to deliver cutting-edge reasoning and intelligence. Built on the Colossus supercomputer, it achieves a 50% score on the challenging HLE benchmark, outperforming many competitors. This advanced model supports multimodal inputs including text and images, with plans to add video capabilities. Grok 4 Heavy targets power users such as developers, researchers, and technical enthusiasts who require top-tier AI performance. Access is provided through the premium “SuperGrok Heavy” subscription priced at $300 per month. xAI has enhanced moderation and removed problematic system prompts to ensure responsible and ethical AI use. -
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Sim Studio
Sim Studio
Sim Studio is a powerful, AI-native platform for designing, testing, and deploying agentic workflows through an intuitive, Figma-like visual editor that eliminates boilerplate code and infrastructure overhead. Developers can immediately start building multi-agent applications with full control over system prompts, tool definitions, sampling parameters, and structured output formatting, while maintaining the flexibility to switch seamlessly among OpenAI, Anthropic, Claude, Llama, Gemini, and other LLM providers without refactoring. The platform supports full local development via Ollama integration for privacy and cost efficiency during prototyping, then enables scalable cloud deployment when you’re ready. Sim Studio connects your agents to existing tools and data sources in seconds, importing knowledge bases automatically and offering over 40 pre-built integrations. -
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ThirdLine
ThirdLine
ThirdLine is a modern oversight platform built to audit, report, and optimize government ERP operations for local governments and schools by providing hundreds of no‑code analytics across finance, accounting, audit, and IT. It integrates seamlessly with leading ERP systems, including Tyler Enterprise ERP powered by Munis, Oracle Fusion and Workday, and supports modules such as accounts payable, accounts receivable, general ledger, payroll, purchasing, purchasing card, roles & permissions, travel and entertainment, vendor and human resources to deliver continuous monitoring, risk assessment, compliance reporting and real‑time budget‑to‑actual variance analysis. Key features include continuous audit and fraud detection with nightly analytics, segregation‑of‑duties enforcement, duplicate invoice recovery, pending requisition tracking, quick monthly close, automated alerts via email, interactive dashboards that trace each transaction’s origin, approval history, and participants. -
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Naptha
Naptha
Naptha is a modular AI platform for autonomous agents that empowers developers and researchers to build, deploy, and scale cooperative multi‑agent systems on the agentic web. Its core innovations include Agent Diversity, which continuously upgrades performance by orchestrating diverse models, tools, and architectures; Horizontal Scaling, which supports collaborative networks of millions of AI agents; Self‑Evolved AI, where agents learn and optimize themselves beyond human‑designed capabilities; and AI Agent Economies, which enable autonomous agents to generate useful goods and services. Naptha integrates seamlessly with popular frameworks and infrastructure, LangChain, AgentOps, CrewAI, IPFS, NVIDIA stacks, and more, via a Python SDK that upgrades existing agent frameworks with next‑generation enhancements. Developers can extend or publish reusable components on the Naptha Hub, run full agent stacks anywhere a container can execute on Naptha Nodes. -
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Macrobond
Macrobond
From the first question to the final chart, Macrobond powers the entire research process by centralizing data management, advanced analysis, visualization, and reporting in a seamless workflow. Users consolidate their work by tapping into a clean, searchable library of over 2,400 global financial and economic sources; analyze in‑platform using built‑in calculation and comparison functions without exporting data; visualize results instantly with customizable charting tools that communicate insights clearly; and publish polished, up‑to‑date reports ready for presentation. Macrobond’s end‑to‑end platform streamlines research steps, accelerates time to insight, and ensures consistency and accuracy across projects, so teams can think fast and make faster, data‑driven decisions. -
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Droidrun
Droidrun
Droidrun is a native mobile agent platform that gives users natural-language control over real Android devices to automate any mobile app workflow, from logins and bookings to purchases and data extraction, including access to mobile-only content behind app logins, rate limits, or platform restrictions. Its cloud offering lets users spin up agents in seconds with preinstalled apps, run tasks in parallel across multiple devices, and compose complex, multi-step conditional workflows using conversational commands; recorded workflows can be auto-replayed at high speed. Credential management securely stores login information once for reuse, and the system integrates with existing stacks like LLMs, N8N, or custom scripts to inject real app execution into broader automation pipelines. Developers get SDK examples (including Python integrations with Gemini or Ollama) for embedding Droidrun into their tooling. -
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Azure DevOps Labs
Microsoft
Azure DevOps Labs is a free, community-driven collection of self-paced, hands-on tutorials designed to teach every aspect of the Azure DevOps toolchain and related DevOps practices. From configuring Agile planning with Azure Boards and version control in Azure Repos to defining build and release pipelines as code with YAML, enabling CI/CD in Azure Pipelines, managing packages in Azure Artifacts, and orchestrating tests with Azure Test Plans, each lab provides step-by-step exercises and sample code repositories. You can spin up ready-made projects using the Azure DevOps Demo Generator, explore end-to-end scenarios like deploying Docker-based web applications, integrating Terraform for infrastructure-as-code, scanning for security vulnerabilities, monitoring performance with Application Insights, and automating database changes with Redgate. Prerequisites include an Azure DevOps organization and an Azure subscription, but no prior experience is required. -
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gpt-oss-20b
OpenAI
gpt-oss-20b is a 20-billion-parameter, text-only reasoning model released under the Apache 2.0 license and governed by OpenAI’s gpt-oss usage policy, built to enable seamless integration into custom AI workflows via the Responses API without reliance on proprietary infrastructure. Trained for robust instruction following, it supports adjustable reasoning effort, full chain-of-thought outputs, and native tool use (including web search and Python execution), producing structured, explainable answers. Developers must implement their own deployment safeguards, such as input filtering, output monitoring, and usage policies, to match the system-level protections of hosted offerings and mitigate risks from malicious or unintended behaviors. Its open-weight design makes it ideal for on-premises or edge deployments where control, customization, and transparency are paramount. -
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gpt-oss-120b
OpenAI
gpt-oss-120b is a reasoning model engineered for deep, transparent thinking, delivering full chain-of-thought explanations, adjustable reasoning depth, and structured outputs, while natively invoking tools like web search and Python execution via the API. Built to slot seamlessly into self-hosted or edge deployments, it eliminates dependence on proprietary infrastructure. Although it includes default safety guardrails, its open-weight architecture allows fine-tuning that could override built-in controls, so implementers are responsible for adding input filtering, output monitoring, and governance measures to achieve enterprise-grade security. As a community–driven model card rather than a managed service spec, it emphasizes transparency, customization, and the need for downstream safety practices. -
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Claude Opus 4.1
Anthropic
Claude Opus 4.1 is an incremental upgrade to Claude Opus 4 that boosts coding, agentic reasoning, and data-analysis performance without changing deployment complexity. It raises coding accuracy to 74.5 percent on SWE-bench Verified and sharpens in-depth research and detailed tracking for agentic search tasks. GitHub reports notable gains in multi-file code refactoring, while Rakuten Group highlights its precision in pinpointing exact corrections within large codebases without introducing bugs. Independent benchmarks show about a one-standard-deviation improvement on junior developer tests compared to Opus 4, mirroring major leaps seen in prior Claude releases. Opus 4.1 is available now to paid Claude users, in Claude Code, and via the Anthropic API (model ID claude-opus-4-1-20250805), as well as through Amazon Bedrock and Google Cloud Vertex AI, and integrates seamlessly into existing workflows with no additional setup beyond selecting the new model. -
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GPT-5 pro
OpenAI
GPT-5 Pro is OpenAI’s most advanced AI model, designed to tackle the most complex and challenging tasks with extended reasoning capabilities. It builds on GPT-5’s unified architecture, using scaled, efficient parallel compute to provide highly comprehensive and accurate responses. GPT-5 Pro achieves state-of-the-art performance on difficult benchmarks like GPQA, excelling in areas such as health, science, math, and coding. It makes significantly fewer errors than earlier models and delivers responses that experts find more relevant and useful. The model automatically balances quick answers and deep thinking, allowing users to get expert-level insights efficiently. GPT-5 Pro is available to Pro subscribers and powers some of the most demanding applications requiring advanced intelligence. -
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GPT-5 thinking
OpenAI
GPT-5 Thinking is the deeper reasoning mode within the GPT-5 unified AI system, designed to tackle complex, open-ended problems that require extended cognitive effort. It works alongside the faster GPT-5 model, dynamically engaging when queries demand more detailed analysis and thoughtful responses. This mode significantly reduces hallucinations and improves factual accuracy, producing more reliable answers on challenging topics like science, math, coding, and health. GPT-5 Thinking is also better at recognizing its own limitations, communicating clearly when tasks are impossible or underspecified. It incorporates advanced safety features to minimize harmful outputs and provide nuanced, helpful answers even in ambiguous or sensitive contexts. Available to all users, it helps bring expert-level intelligence to everyday and advanced use cases alike. -
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Lucidic AI
Lucidic AI
Lucidic AI is a specialized analytics and simulation platform built for AI agent development that brings much-needed transparency, interpretability, and efficiency to often opaque workflows. It provides developers with visual, interactive insights, including searchable workflow replays, step-by-step video, and graph-based replays of agent decisions, decision tree visualizations, and side‑by‑side simulation comparisons, that enable you to observe exactly how your agent reasons and why it succeeds or fails. The tool dramatically reduces iteration time from weeks or days to mere minutes by streamlining debugging and optimization through instant feedback loops, real‑time “time‑travel” editing, mass simulations, trajectory clustering, customizable evaluation rubrics, and prompt versioning. Lucidic AI integrates seamlessly with major LLMs and frameworks and offers advanced QA/QC mechanisms like alerts, workflow sandboxing, and more. -
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LangMem
LangChain
LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows. -
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Paid.ai
Paid.ai
Paid.ai is a purpose-built platform that enables AI agent developers to seamlessly monetize, track costs, and automate billing for their autonomous agents. By capturing usage signals via lightweight SDKs, it provides real-time monitoring of LLM/API costs, margin visibility per agent, and alerts for cost spikes. Its flexible workflows facilitate multiple billing models, including per-agent, per-action, per-workflow, and outcome-based pricing, aligned with the way AI agents deliver business value. Paid.ai supports comprehensive revenue operations by automating invoice generation, offering pricing simulation tools, managing orders and payments, and embedding live value dashboards through its “Blocks” feature. Developers can integrate Paid.ai quickly into their systems using Node.js, Python, Go, or Ruby SDKs, enabling fast deployment of both cost tracking (free for the first year) and billing automation. -
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Google Cloud Universal Ledger (GCUL) is a next-generation, permissioned layer-1 blockchain platform designed for financial institutions to manage commercial bank money and tokenized assets with unprecedented simplicity, flexibility, and security. It offers a programmable, multi-currency distributed ledger accessible via a unified API, eliminates the complexity of traditional payment infrastructure, and supports atomic settlement for near-instant transfers. Built with compliance in mind, the platform enforces KYC-verified accounts, transparent transaction fees, and private, auditable governance, while also fostering automation through programmatic workflows and integration with familiar developer tools like Python-based smart contracts. CE reactions and institutional testing underscore its real-world applicability; CME Group is piloting GCUL for tokenized settlement workflows in areas like collateral and margin processing.
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PyMuPDF
Artifex
PyMuPDF is a high-performance, Python-centric library for reading, extracting, and manipulating PDFs with ease and precision. It enables developers to access text, images, fonts, annotations, metadata, and structural layout of PDF documents, and to perform tasks such as extracting content, editing objects, rendering pages, searching text, modifying page content, and manipulating PDF components like links and annotations. PyMuPDF also supports advanced operations like splitting, merging, inserting, or deleting pages; drawing and filling shapes; handling color spaces; and converting between formats. The library is lightweight but robust, optimized for speed and low memory overhead. On top of the base PyMuPDF, PyMuPDF Pro adds support for reading and writing Microsoft Office-format documents and enhanced functionality for integrating Large Language Model (LLM) pipelines and Retrieval Augmented Generation (RAG). -
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Ghostscript
Artifex
Ghostscript is a powerful PostScript and PDF interpreter developed by Artifex, offering a rendering engine and comprehensive graphics library for high-quality document processing. It handles interpreting, processing, and rendering PostScript files and PDFs, supports complex page description language features, and includes utilities for converting, rasterizing, and manipulating documents. Ghostscript also has .NET bindings (Ghostscript.NET) so it can be integrated into .NET applications, and there’s an enterprise version (Ghostscript Enterprise) that extends capabilities to reading and processing common office documents like Word, PowerPoint, and Excel. The product is designed for precision rendering, color space management, and reliable output, making it suitable for both programmatic document workflows and production environments. -
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Sudo
Sudo
Sudo offers “one API for all models”, a unified interface so developers can integrate multiple large language models and generative AI tools (for text, image, audio) through a single endpoint. It handles routing between different models to optimize for things like latency, throughput, cost, or whatever criteria you choose. The platform supports flexible billing and monetization options; subscription tiers, usage-based metered billing, or hybrids. It also supports in-context AI-native ads (you can insert context-aware ads into AI outputs, controlling relevance and frequency). Onboarding is quick: you create an API key, install their SDK (Python or TypeScript), and start making calls to the AI endpoints. They emphasize low latency (“optimized for real-time AI”), better throughput compared with some alternatives, and avoiding vendor lock-in. -
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Claude Sonnet 4.5
Anthropic
Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection. -
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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. -
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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. -
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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. -
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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. -
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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. -
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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. -
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Jedi
Jedi
Jedi is a static analysis tool for Python that is typically used in IDEs/editors plugins. Jedi has a focus on autocompletion and goto functionality. Other features include refactoring, code search and finding references. Jedi has a simple API to work with. There is a reference implementation as a VIM-Plugin. Autocompletion in your REPL is also possible, IPython uses it natively and for the CPython REPL you can install it. Jedi is well tested and bugs should be rare. A Script is the base for completions, goto or whatever you want to do with Jedi. The counter part of this class is Interpreter, which works with actual dictionaries and can work with a REPL. This class should be used when a user edits code in an editor. Most methods have a line and a column parameter. Lines in Jedi are always 1-based and columns are always zero based. To avoid repetition they are not always documented.