Business Software for Go

Bunny Database is a comprehensive, cloud-based SQL database solution provided by the bunny.net developer platform, designed to simplify the deployment, connection, scaling, and management of relational databases without the need for infrastructure oversight. Utilizing libSQL, a derivative of SQLite, it adheres to standard SQL syntax and is compatible with existing SQLite tools, ORMs, and SDKs, while taking care of replication and scaling automatically. Users can quickly create a database with a single click, select deployment locations globally, and connect their applications through an HTTP API, native SDKs (for TypeScript/JavaScript, Go, Rust, .NET), or widely-used ORMs. Additionally, it offers tools for data inspection, query execution, and performance tracking available on the dashboard. The service ensures global replication for rapid read access and integrates effortlessly with other bunny.net offerings like Edge Scripting and Magic Containers, optimizing compute and storage proximity to users. Moreover, its usage-based billing approach allows for cost efficiency by keeping databases idle when not in use, making it an ideal choice for developers looking for flexibility and scalability.

DeepSeek-V4 is an advanced open-source large language model engineered for efficient long-context processing and high-level reasoning tasks. Supporting a massive one million token context window, it enables developers to build applications that handle extensive data and complex workflows without fragmentation. The model is available in two versions: V4-Pro for maximum reasoning power and V4-Flash for faster, cost-efficient performance. DeepSeek-V4-Pro delivers top-tier results in coding, mathematics, and knowledge benchmarks, rivaling leading proprietary models. Its architecture incorporates innovative attention techniques that significantly improve efficiency while maintaining strong performance. The model is optimized for agent-based workflows, allowing seamless integration with tools and automation systems. It also supports dual reasoning modes, enabling users to switch between quick responses and deeper analytical outputs. DeepSeek-V4 is fully open-source, providing flexibility for customization and deployment across various environments. Overall, it offers a powerful and scalable solution for modern AI development.

Sprites by Fly.io is a stateful sandbox environment platform designed to run arbitrary code in isolated Linux computers. Each Sprite is a hardware-isolated execution environment that can persist across runs, making it useful for AI agents, uploaded binaries, developer tools, and application workloads. The platform is built around checkpoint and restore, allowing workloads to pause, resume, and keep state instead of rebuilding the environment repeatedly. Sprites provide a fast NVMe filesystem that syncs continuously to durable external object storage. This tiered storage approach gives users compatibility with normal Linux filesystem behavior while only charging for the data they actually use. Developers can start with the Sprites CLI by logging in, creating a Sprite, executing commands, and connecting to the console. The platform also supports REST API access and SDKs for JavaScript, Go, Elixir, and Python. Pricing is usage-based across CPU time, memory time, hot storage, and cold storage. By combining sandbox VMs, persistent filesystems, checkpointing, APIs, network policy, and pay-as-you-go pricing, Sprites gives developers a practical runtime for AI agents and untrusted code execution.

Octrafic is a command-line tool that leverages AI and is available as open source, aimed at simplifying the process of automated API testing and exploration by allowing users to communicate with APIs in natural language rather than having to write complex scripts or set up intricate testing frameworks. By simply directing the tool to any HTTP API or OpenAPI specification, users can articulate their testing requirements in straightforward English, prompting the integrated AI agent to create test scenarios, perform actual HTTP requests, verify responses, and generate organized results. This tool streamlines the entire testing process, encompassing endpoint discovery, request formulation, schema checks, and error identification, which enables developers to prioritize testing logic without getting bogged down by the underlying implementation specifics. Additionally, it accommodates real-time execution against live APIs, ensuring the accuracy of status codes and behaviors without the need for mock setups, and it can also produce aesthetically formatted PDF reports for effective communication with teams or stakeholders. With its user-friendly approach, Octrafic represents a significant advancement in making API testing more accessible and efficient.

TurboDocx is an innovative platform that leverages artificial intelligence to streamline document automation and templating, allowing businesses to swiftly produce, tailor, and oversee professional documents and presentations through the use of reusable templates, centralized content, and smart automation features. Users can effortlessly extract data from various sources, including customer relationship management systems, meeting notes, and project management tools, to fill templates with precise and current information, thereby minimizing manual data entry and mitigating the risk of errors. The platform accommodates both AI-driven and manual processes, giving users the flexibility to auto-fill fields, create personalized content sections, and modify tone and style, or compile documents by selecting approved materials from a communal knowledge base to maintain brand coherence. With seamless integration into applications like Microsoft Word, PowerPoint, Google Docs, and various cloud storage solutions, teams can operate within their preferred environments while benefiting from automated document creation, making the overall process more efficient and organized. This adaptability not only enhances productivity but also fosters collaboration among team members.

CoStrict is a sophisticated AI programming platform tailored for enterprises, aimed at supporting developers throughout all stages of the software development lifecycle by integrating code generation, coding assistance, code completion, and automated code review into one cohesive system. This platform embraces a "quality-first" development methodology, where features such as Strict Mode decompose requirements into organized phases, including analysis, architectural design, task planning, and automatic test creation prior to coding, thereby ensuring high-quality results right from the outset. It employs retrieval-augmented techniques to analyze entire codebases, enabling it to grasp project context, leverage existing standards, and deliver exceptionally relevant recommendations and enhancements. Additionally, it boasts an AI agent that can generate code, respond to queries, optimize logic, and enrich documentation in real-time, while its code completion functionalities significantly enhance the speed of development. By streamlining the entire process, CoStrict empowers developers to produce robust software solutions with greater efficiency and precision.

GPT-5.5 Pro is a next-generation AI model built for execution-heavy tasks across coding, research, business analysis, and scientific workflows. It can interpret complex instructions, break them into steps, and carry work through to completion using tools and automation. The model supports tasks such as generating documents, building applications, analyzing datasets, and navigating software environments. It is designed to operate across tools, enabling seamless workflows from idea to output. In addition, GPT-5.5 Pro integrates with workspace agents—customizable AI agents that automate recurring and multi-step processes across teams. These agents can handle tasks like lead research, reporting, and workflow automation, running independently or on schedules. Built with enterprise-grade safeguards, the model ensures secure and controlled automation. It helps organizations improve productivity by reducing manual effort and accelerating decision-making. GPT-5.5 Pro is ideal for teams looking to scale operations and handle complex workloads efficiently.

Outcron is an innovative hosted job scheduler crafted to offer a more dependable alternative to conventional cron configurations, eliminating the hassle of server maintenance and the cumbersome process of integrating scripts. This platform centralizes the scheduling and execution of essential jobs, delivering built-in reliability that guarantees tasks are carried out consistently without requiring manual intervention or the management of underlying infrastructure. With support for a variety of job types, Outcron features an adaptable scheduling system that transcends the limitations of standard cron syntax, facilitating the creation of intricate and flexible workflows. One of its standout functionalities is misfire recovery, which automatically identifies and retries missed or failed jobs, thereby minimizing the likelihood of unnoticed failures that can plague self-managed cron setups. Additionally, Outcron comes equipped with tools for execution history and observability, empowering users to monitor every job run, review logs, and gain insights into job performance over time. This comprehensive solution not only enhances reliability but also streamlines job management, making it an invaluable resource for teams looking to optimize their workflow automation.

Abliteration.ai serves as an AI platform tailored for developers, granting access to large language models without constraints, all while incorporating a governance layer that empowers teams to dictate model behavior instead of depending on preset limitations from providers. The platform features an API compatible with OpenAI, promoting effortless integration into current tools, SDKs, and processes without necessitating significant infrastructure modifications. Central to Abliteration.ai’s philosophy is the idea of being “unrestricted, not ungoverned,” which allows developers to leverage models with fewer censorships while implementing their own regulatory measures through a Policy Gateway that manages outputs in real-time, enabling actions like allowing, blocking, redacting, or escalating based on tailored policies. These policies are designed as code, facilitating auditing, simulation, and deployment, complemented by capabilities such as shadow testing and rollback measures for added security. Furthermore, Abliteration.ai caters to sophisticated applications, including security assessments, red teaming, synthetic data generation, and research workflows tailored to specific needs, thereby expanding the potential for innovative solutions in various fields. With its comprehensive approach, Abliteration.ai not only enhances the flexibility of AI usage but also ensures that developers maintain control over the ethical implications of their models.

RailPush is an innovative deployment service that effortlessly transitions your code from a repository to a fully operational application, complete with builds, HTTPS support, and a default URL right from the start. By simply connecting your repository, users can deploy their applications in a matter of minutes and receive a live URL, while RailPush efficiently manages deployments, data, and routing all in one place, allowing integration with GitHub and customization of build requirements. Each code push triggers a build process that checks the application's health and implements updates, providing instant URLs secured with TLS and offering preview links for testing. Users can initiate their first web service by linking their GitHub repository, choosing a specific repo and branch, and defining any necessary build or start commands, leading to an automatic deployment service. RailPush simplifies the development process by automatically identifying the runtime and creating an optimized Dockerfile, offering compatibility with popular languages such as Node.js, Python, Go, Ruby, Rust, Elixir, Java, and Docker. For those who prefer a hassle-free setup, pre-configured stacks are available, allowing users to deploy popular combinations like Next.js with Postgres, Django coupled with Redis, and Rails, among others, using straightforward templates that streamline the process even further. This all-in-one platform not only enhances productivity but also empowers developers to focus more on coding rather than the complexities of deployment.

Zavu serves as a unified API for managing all your messaging needs, allowing you to send and receive SMS, WhatsApp messages, Email, Voice calls, Telegram, and other forms of communication through a single integration. This solution enables developers to streamline the messaging process rather than deal with the complexities of maintaining multiple messaging infrastructures, effectively replacing various APIs, SDKs, authorization models, webhook structures, sender configurations, template approvals, and error management with just one SDK, a single webhook format, and an integrated dashboard. Designed to accommodate AI agents from the outset, Zavu empowers these agents to communicate globally via SMS, WhatsApp, Email, and Voice, while offering developers access to production-ready SDKs in programming languages like Node.js, Python, Ruby, Go, PHP, and Java. The platform's Smart Send and AI Routing capabilities intelligently select the appropriate messaging channel—be it SMS, WhatsApp, or Email—based on the recipient, optimizing delivery by leveraging platform-wide delivery intelligence and automatically redirecting to alternative channels when necessary. In this process, context is consistently maintained, duplicate deliveries are eliminated, and costs are meticulously monitored throughout the entire fallback sequence, ensuring both efficiency and clarity for users. Additionally, Zavu's comprehensive approach allows for seamless integration into existing workflows, enhancing the overall user experience.

PRFlow is an innovative AI-driven code review tool designed to identify bugs before they reach production. It efficiently indexes your entire codebase, examines dependencies across different files, and generates a comprehensive security review in less than three minutes for every pull request. Tailored to address the intricacies of complex codebases, PRFlow leverages semantic memory to grasp cross-repo dependencies and internal structures prior to analyzing the pull request. Instead of merely focusing on the differences or the entire file, it extracts pertinent context, including the modified function and its related dependencies. With a security-centric approach, PRFlow highlights vulnerabilities such as XSS, SSRF, SQL injection, authentication bypass, and race conditions by monitoring the flow of code across files. The tool reviews the entire pull request in one go, delivering a thorough structured analysis that includes a score, walkthrough, issues categorized by file, severity ratings, strengths, and suggestions for code improvements presented as inline comments on GitHub. Additionally, it facilitates ongoing conversations within the pull request thread, allowing for collaborative troubleshooting and enhancement of code quality.

Graphify serves as an innovative open source knowledge graph engine that converts diverse inputs such as code, documentation, research papers, meetings, images, browser tabs, and commits into a single, navigable graph with full recall capabilities. Designed to function as a persistent memory for AI coding assistants, it empowers tools like Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, Aider, Factory Droid, Kimi Code, Kiro, Pi, and Google Antigravity with a queryable grasp of a project, thereby eliminating the need for them to continuously search through files. Users can direct Graphify to any directory, where it generates an initial corpus through AST extraction, semantic analysis, and Leiden clustering, effectively converting an entire codebase or document collection into a comprehensive graph in a single operation. Unlike traditional RAG pipelines that require re-embedding for every modification, Graphify sustains a dynamic graph that only updates the affected nodes and edges when files are altered, allowing the remainder of the corpus to remain stable even at an enterprise scale. This capability not only enhances efficiency but also facilitates seamless collaboration among various AI tools, significantly improving the overall workflow for developers and researchers alike.

Hindsight is an innovative memory framework designed to enhance AI agents by enabling them to learn progressively rather than resetting their knowledge with each new interaction. Unlike traditional memory systems that primarily focus on recalling past conversations, Hindsight prioritizes the learning process, equipping agents with a persistent long-term memory through advanced biomimetic data structures. This functionality allows AI agents to keep track of essential facts, access relevant context, and engage in reflective reasoning based on their experiences. Hindsight is particularly beneficial for agents that require a deep understanding of user identities, previous discussions, evolving preferences, decision-making histories, and necessary behavioral adjustments across different sessions. To achieve this, it incorporates three fundamental operations: retain, which captures new information; recall, which accesses appropriate memories when required; and reflect, which aids agents in synthesizing observations, developing mental frameworks, and gaining insights from earlier interactions. By implementing these features, Hindsight ensures a more personalized and context-aware experience for users.

Dokploy is a self-hosted, open-source Platform as a Service designed to streamline the deployment and management of both applications and databases. Tailored for developers who desire greater control and flexibility, it allows teams to easily deploy their applications on personal infrastructure while avoiding vendor lock-in and the intricacies of Kubernetes. With a simple command installation, Dokploy enables project deployment in just minutes, bringing together application control, database management, logging, monitoring, backups, and multi-server environments within a unified interface. It accommodates both single services and multi-service applications, featuring native support for Docker Compose, Git-based deployments, custom Docker images, Dockerfiles, Nixpacks, and Buildpacks. This versatility empowers teams to select the most suitable build strategy for each project without the need to overhaul their existing pipeline, ultimately enhancing productivity and efficiency. Moreover, Dokploy's user-friendly design ensures that even those with limited technical expertise can manage their deployments with ease.

Ornith-1.0 represents an innovative family of models tailored specifically for coding tasks that require agentic capabilities. This family encompasses a wide range of models, from the compact 9B Dense versions ideal for deployment on edge devices to the expansive 397B MoE frontier-scale models designed for peak performance, including variants such as 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built upon the foundational strengths of pretrained models like Gemma 4 and Qwen 3.5, Ornith-1.0 excels in achieving top-tier performance among open-source models that are similar in size when evaluated against coding benchmarks. A significant breakthrough of this model is its self-improving training framework, which effectively learns to produce both solution rollouts and the tailored scaffolds that direct those rollouts. Rather than depending on static, human-crafted harnesses, Ornith-1.0 perceives the scaffold as a dynamic entity that evolves alongside the policy, enabling the model to optimize both the orchestration of tasks and the resulting solutions in tandem. This dual optimization approach enhances the model's adaptability and effectiveness in real-world coding scenarios.

Morph is an innovative platform that leverages AI to streamline the process of modernizing code by facilitating the migration of repositories from one technology stack to another, all while ensuring that engineering teams maintain oversight. Users can seamlessly integrate multiple GitHub repositories, articulate their objectives using straightforward language, and set up parameters for how the application is installed, built, executed, undergoes health checks, and is tested. The platform thoroughly examines the codebase, meticulously documenting its architecture, frameworks, dependencies, inter-component relationships, patterns, and conventions, ultimately producing a comprehensive Project Spec for team review and approval prior to any code generation. The modernization process is strategically segmented into manageable milestones instead of a single overwhelming change, with each milestone delivered as a pull request, allowing teams to review, comment, and merge at their discretion. Additionally, Project Knowledge offers a centralized repository for migration scope, lifecycle configuration, milestones, documentation, design choices, and enforceable guidelines, fostering a collaborative environment where agents share context that evolves throughout the project’s progression, ensuring clarity and consistency in decision-making. This approach not only enhances collaboration but also empowers teams to maintain control over the modernization journey.

Gemini 3.5 Flash-Lite stands out as the quickest model within Google's Gemini 3.5 lineup, specifically engineered for tasks requiring low latency and for enhancing developer workflows that demand high throughput, including agentic search, document processing, coding, and extensive data analysis. It boasts an impressive output capacity of 350 tokens per second and marks a significant enhancement over earlier Flash-Lite iterations in terms of both quality and agentic capabilities. Developers have the flexibility to adjust the model's thinking level to suit the demands of the task at hand: minimal or low thinking allows for rapid processing of large volumes, while elevated thinking levels accommodate more intricate, multi-step workflows involving subagents. Furthermore, the model is equipped with built-in computational skills, enabling it to interact effectively with various digital environments across compatible platforms. Additionally, Gemini 3.5 Flash-Lite excels in coding, comprehending long contexts, and executing real-world tasks, consistently outperforming its predecessor, Gemini 3.1 Flash-Lite, in critical assessments and even exceeding the performance of Gemini 3 Flash on multiple benchmarks related to agentic functions and software engineering. This impressive performance highlights its potential to transform how developers approach complex workflows and data-intensive tasks.

Voltra is an innovative Energy Cloud Platform designed to simplify intricate physical systems via software, overseeing the comprehensive lifecycle of sites and devices from their initial setup to ongoing maintenance. At its core is Voltra Fabric, which seamlessly links devices from various manufacturers, protocols, generations, and standards using protocol-agnostic adapters, effectively creating a unified, governed graph that serves as a live digital twin and reliable reference for the site. This model enables Fabric to ensure interoperability while keeping connections, data, and configurations up to date as firmware, sites, and assets develop over time. Users can access a complete view of their site through a web browser, allowing them to track faults, usage statistics, performance metrics, telemetry, and alerts in real-time, as well as securely manage device traffic or transfer data to external data lakes and observability platforms. Additionally, developers have the flexibility to control the same infrastructure via a scriptable command-line interface and through REST and OpenAPI protocols, enabling a versatile approach to managing energy systems. This multifaceted platform empowers operators and developers alike to optimize their energy management strategies and enhance operational efficiency.

Kastra serves as the crucial authorization framework for AI systems, determining the permissions of agents, models, and tools prior to their execution. Positioned along the execution path of all interactions such as prompts, tool calls, shell commands, database operations, and API requests, it evaluates each action based on deterministic, attribute-driven policies, rendering decisions to allow, deny, redact, or escalate in less than a millisecond. In contrast to monitoring solutions that only track AI actions post-execution, Kastra proactively prevents unauthorized activities before they can impact any tool, API, database, or production environment. Its comprehensive control plane integrates a policy engine, edge decision-making capabilities, various integrations, and a tamper-proof evidence vault that securely signs each decision for auditing and replay purposes. Furthermore, with Kastra Edge, local enforcement is extended to developer environments, safeguarding coding agents such as Claude Code, Cursor, and Codex CLI from harmful commands, unauthorized data extraction, unsafe file modifications, and improper tool usage. This proactive approach to authorization not only enhances security but also ensures compliance and accountability in AI-driven processes.

DevPod is an innovative open-source solution designed for the creation and management of reproducible developer environments as code, all without the need for a cumbersome server-side infrastructure. By leveraging the open devcontainer.json standard, it allows each workspace to be defined, enabling projects to maintain their development environments and provide a uniform experience across teams. Workspaces operate within isolated containers, which can be set up on a local laptop, an accessible remote server, a Kubernetes cluster, or various public and private cloud platforms through DevPod’s providers. This flexibility allows developers to effortlessly switch between local and cloud-based environments while maintaining consistent workspace management. As a client-only application, DevPod is available for use as both a desktop app and a programmable command-line interface, requiring no backend service. It seamlessly integrates with both public and private Git repositories, accommodates any programming language, and can intelligently analyze projects to generate an optimal environment even in the absence of a devcontainer configuration. Additionally, its user-friendly design simplifies the setup process, making it accessible for developers of all skill levels.

Encore serves as an automated infrastructure platform designed for both humans and AI agents, enabling developers to efficiently build, validate, and deploy applications without the delays associated with Terraform pull requests or platform tickets. By utilizing its open-source SDK, developers and agents can specify the necessary infrastructure for each feature directly within application code, while Encore autonomously provisions and verifies various resources such as databases, queues, buckets, and Pub/Sub, facilitating a seamless transition from development to production. Applications can be executed locally in an environment that closely resembles the cloud setup, enabling comprehensive testing of features and distributed systems with just a single command. When a new branch is pushed, Encore automatically generates a dedicated preview environment, allowing teams to assess workflows and external integrations independently of shared staging resources. Upon deployment, the required infrastructure is provisioned automatically within the organization’s own AWS or GCP account, VPC, and compliance parameters, streamlining the entire process. This innovative approach not only enhances efficiency but also ensures that developers can focus more on coding and less on infrastructure management.

Holo4 is H Company's series of generalist computer-use and agentic AI models built to perform multi-step work across software interfaces. It is available as Holo4 27B, a dense 27-billion-parameter model, and Holo4 35B-A3B, a Mixture-of-Experts model containing 35 billion total parameters with 3 billion active. Holo4 can interact with applications by clicking and typing through graphical interfaces, writing and executing code, or calling MCP and API tools. The same model can operate across desktops, websites, Android devices, code sandboxes, and business APIs without requiring developers to select a separate specialized model for each environment. H Company trained Holo4 using 127 billion supervised fine-tuning tokens, with approximately three-quarters consisting of successful agentic trajectories spanning desktop, web, MCP/API, and mobile tasks. Reinforcement learning then trained separate experts for desktop and web interaction and for terminal, MCP, and API work before merging them into a single model. Holo4 27B scored 85.2% on OSWorld, 61.7% on OSWorld 2.0, 45.4% on AutomationBench, and 85.1% on AndroidWorld in the evaluations reported by H Company. The models support a 256K context window, with the 27B model positioned for greater accuracy on long multi-step tasks and the 35B-A3B version positioned as a faster and less expensive alternative. Holo4 is available through a hosted API and downloadable model weights, enabling developers and enterprises to build agents that perform workflows spanning multiple applications and interaction methods.

Enhance your productivity by ensuring only high-quality code is released, as SonarQube Cloud (previously known as SonarCloud) seamlessly evaluates branches and enriches pull requests with insights. Identify subtle bugs to avoid unpredictable behavior that could affect users and address security vulnerabilities that threaten your application while gaining knowledge of application security through the Security Hotspots feature. Within moments, you can begin using the platform right where your code resides, benefiting from immediate access to the most current features and updates. Project dashboards provide vital information on code quality and readiness for release, keeping both teams and stakeholders in the loop. Showcase project badges to demonstrate your commitment to excellence within your communities. Code quality and security are essential across your entire technology stack, encompassing both front-end and back-end development. That’s why we support a wide range of 24 programming languages, including Python, Java, C++, and many more. The demand for transparency in coding practices is on the rise, and we invite you to be a part of this movement; it's completely free for open-source projects, making it an accessible opportunity for all developers! Plus, by participating, you contribute to a larger community dedicated to improving software quality.

The Fastest Code Analysis. 40X faster scan speeds so developers don't have to wait long for results after submitting a pull request. The Most Accurate Result. Qwiet AI is the only AI with the highest OWASP benchmark score. This is more than triple the commercial average, and more than twice the second highest score. Developer-Centric Security Processes. 96% of developers say that disconnected security and developer workflows hinder their productivity. Implementing developer-centric AppSec workflows decreases mean-time-to-remediation (MTTR), typically by 5X - enhancing both security and developer productivity. Automated Business Logic Flaws in Dev. Identify vulnerabilities unique to your codebase before they reach production. Achieve compliance. Maintain and demonstrate compliance with privacy and security regulations such as SOC 2 PCI-DSS GDPR and CCPA.