Business Software for GitHub Copilot - Page 5

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.

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.

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.

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.

GitHub Actions is a powerful automation tool that enables developers to streamline their software workflows directly within GitHub. It allows teams to build, test, and deploy code automatically using CI/CD pipelines triggered by events such as code pushes or pull requests. With support for multiple programming languages and environments, developers can run workflows across Linux, macOS, and Windows. GitHub Actions also provides hosted and self-hosted runners for flexible execution. It simplifies repetitive tasks like code reviews, issue management, and deployment processes. With real-time logs and built-in secret management, it ensures transparency and security. Overall, GitHub Actions helps teams automate development processes and deliver software faster.

XHawk is an AI-native developer platform designed to transform scattered code, documentation, and team knowledge into a unified, searchable system of context. It captures every coding session, commit, and decision, automatically organizing them into a living knowledge graph that evolves with the codebase. It converts code changes and development activity into structured, indexed documentation, ensuring that knowledge stays synchronized with every pull request and eliminating gaps between code and documentation. It provides a shared context layer that enables both humans and AI coding agents to plan, code, review, test, and operate systems with a consistent understanding, reducing hallucinations caused by missing context. XHawk includes features such as session intelligence, where every git commit syncs session history and agent reasoning, creating a permanent, searchable record of how software is built.

Agensi is a curated marketplace for AI agent skills. Every skill is security-scanned, works across 20+ agents (Claude Code, Codex CLI, Cursor, Gemini CLI, Copilot, and more), and comes from an accountable creator. Skills are one-time purchases. Buy once, own forever. No subscriptions, no license keys. All skills use the open SKILL.md standard, so one purchase works across every compatible agent. Every submission goes through an 8-point automated security scan covering prompt injection, data exfiltration, dangerous commands, secret detection, and obfuscated code. Creators keep 80% of each sale with instant Stripe payouts. Downloads are buyer-fingerprinted for IP protection. Agensi also offers a MCP subscription ($9/month or $90/year) that gives AI agents live access to the full catalog. Your agent connects to Agensi via MCP, searches available skills, and loads the right one mid-conversation. No downloads, no file management. New skills are available the moment they go live.

Matters.AI is the first AI Security Engineer for Data, built for the AI and data layer to autonomously see, understand, and resolve data misuse before the SOC opens a ticket. It protects what truly matters wherever data lives or travels, functioning like an AI security engineer that understands context, monitors behavior, and protects sensitive data autonomously across cloud, SaaS, endpoints, microservices, and AI pipelines. Matters is built on semantic intelligence, nearest neighbor search, data lineage modeling, and predictive behavior analysis, so it does not just detect threats; it understands context, anticipates risk, and takes action proactively. Instead of relying on static rules, regexes, dashboards, and noisy alerts, Matters reads between the lines, traces risk in motion, and never sleeps. It identifies sensitive data not just by how it looks, but by what it represents, tracking data across cloud, SaaS, endpoints, and beyond using fingerprinting and eBPF.

MAI-Thinking-1 is Microsoft AI’s reasoning model, built for complex problems that matter most, with competitive reasoning and strong software engineering performance in its weight class. It is a 35B-active, approximately 1T-total-parameter sparse Mixture of Experts model, giving it a smaller inference footprint than much larger models while still matching leading models on key software engineering benchmarks. Microsoft trained MAI-Thinking-1 from the ground up on enterprise-grade, clean, commercially licensed data, without distillation from third-party models, so its capabilities are learned rather than inherited. The model is part of Microsoft AI’s Hill-Climbing Machine, a co-designed development pipeline built to make every component of model development continually and reliably improve over time. MAI-Thinking-1 is designed for agentic coding environments where models must read code, edit files, run tests, observe failures, and recover from intermediate mistakes.

MAI-Code-1-Flash is a Microsoft coding model built for fast, efficient assistance in everyday developer workflows. Built end-to-end by Microsoft using clean and appropriately licensed data, the model is rolling out to GitHub Copilot individual users in Visual Studio Code through the model picker and the default Auto picker. It is designed around the goal of delivering high-quality coding help with better efficiency, helping engineering teams write better code faster through a lightweight, agentic model integrated into GitHub Copilot and VS Code. MAI-Code-1-Flash was trained directly with GitHub Copilot production harnesses, allowing it to interact with surrounding tools and systems in real developer environments rather than being optimized only for static benchmarks. It supports agentic coding, strong instruction-following across single-turn and multi-turn scenarios, repository question answering, refactoring, telemetry-grounded tasks, and adaptive thinking.

GuardionAI is an Agent and MCP Security Gateway that provides unified security for AI agents and Model Context Protocol tools operating on enterprise data. It sits in the execution path to discover, redact sensitive data, enforce protection, and give teams visibility into actions that traditional SIEM, DLP, and identity layers cannot see. Every agent action is inspected, enforced, and logged at the protocol level across AI agents, LLM apps, RAG systems, chatbots, coding agents, MCP servers, internal tools, databases, operating systems, and cloud environments. GuardionAI protects against critical AI threats such as prompt injection, system override, web attacks, MCP tool poisoning, malicious code execution, NSFW content, PII and credential exposure, confidential data leakage, off-topic drift, and unauthorized access, mapped to OWASP LLM Top 10 and agentic AI threat frameworks. Its gateway provides four layers of protection.

Pillar Security is a unified AI security platform for securing the agentic workforce across the entire AI lifecycle, from development to deployment and runtime protection. It connects business context across discovery, testing, and protection so security intelligence compounds across AI applications, agents, models, prompts, frameworks, tools, MCP servers, skills, coding agents, SaaS, cloud, code, and endpoints. Pillar helps organizations discover and manage AI assets everywhere, including shadow AI and unapproved systems, assess supply chain and posture risks, map agentic attack surfaces, and validate the vulnerabilities that actually matter. Its AI Security Posture Management capabilities analyze connected agents, tools, permissions, data sources, prompts, models, and supply chain components to expose risky paths, policy violations, misconfigurations, coding agent risks, and blast radius when a single component is compromised.

MAI-Image-2.5-Pro is Microsoft AI’s highest-fidelity image model to date, designed for creative work where visual quality, control, and accuracy are the priority. It generates high-quality, photorealistic, and design-ready images from simple text prompts or uploaded photos, with natural lighting, accurate skin tones, and fine material details suited to professional use. The model is built for hero imagery, branding, product visuals, commercial design, and other workflows that require polished output with less post-processing. Its precise editing capabilities let users make natural-language changes while keeping the surrounding image coherent, preserving layout and composition, and adapting objects or environments in context. MAI-Image-2.5-Pro also provides robust object consistency, stronger visual reasoning, and better world knowledge, helping edits and generations stay logically grounded across complex scenes.

GPT-5.4 is an advanced artificial intelligence model developed by OpenAI to support complex professional and technical work. The model combines improvements in reasoning, coding, and agent-based workflows into a single system designed for real-world productivity tasks. GPT-5.4 can generate, analyze, and edit documents, spreadsheets, presentations, and other work outputs with greater accuracy and efficiency. It also features improved tool integration, enabling the model to interact with software environments and external tools to complete multi-step workflows. With enhanced context capabilities supporting up to one million tokens, GPT-5.4 can process and reason over very large amounts of information. The model also improves factual accuracy and reduces errors compared to earlier versions. By combining strong reasoning, coding ability, and tool use, GPT-5.4 helps users complete complex tasks faster and with fewer iterations.

C is a programming language created in 1972 which remains very important and widely used today. C is a general-purpose, imperative, procedural language. The C language can be used to develop a wide variety of different software and applications including operating systems, software applications, code compilers, databases, and more.

Quickly write code by translating your comments into code, like in this example where we quickly create a Plotly bar chart. Create entire functions with ease, without searching for library methods and parameters. In this example, we created a function that loads df to AWS bucket in parquet format. Write SQL queries by providing CodeSquire with simple instructions on what you want to pull, join, and group by, like in the following example where we are trying to determine the top 10 most common names. CodeSquire can even help you understand someone else’s code, just ask to explain the function above, and get your explanation in plain text. CodeSquire can help you create complex functions that involve several logic steps. Brainstorm with it by starting simple and adding more complex features as you go.

MAI-Voice-2-Flash is Microsoft AI’s fast, efficient text-to-speech model for high-volume voice experiences where responsiveness is essential. It produces high-fidelity, natural, and expressive speech while preserving the prosody, acoustic quality, human-like rhythm, intonation, and emotional nuance of MAI-Voice-2. The model is optimized for real-time synthesis and runs twice as fast as MAI-Voice-2, making it suitable for voice agents, assistants, interactive applications, call centers, and IVR systems that must respond without noticeable delay. It supports 15 languages across 18 locales and includes a library of licensed, curated voices that can be used immediately. Developers can control speaking style and emotion through SSML, shaping delivery with expressions such as joy, excitement, empathy, sadness, whispering, or shouting to match different conversational situations and brand experiences.