Business Software for Mistral AI - Page 7

Top Software that integrates with Mistral AI as of November 2025 - Page 7

  • 1
    Voxtral

    Voxtral

    Mistral AI

    Voxtral models are frontier open source speech‑understanding systems available in two sizes—a 24 B variant for production‑scale applications and a 3 B variant for local and edge deployments, both released under the Apache 2.0 license. They combine high‑accuracy transcription with native semantic understanding, supporting long‑form context (up to 32 K tokens), built‑in Q&A and structured summarization, automatic language detection across major languages, and direct function‑calling to trigger backend workflows from voice. Retaining the text capabilities of their Mistral Small 3.1 backbone, Voxtral handles audio up to 30 minutes for transcription or 40 minutes for understanding and outperforms leading open source and proprietary models on benchmarks such as LibriSpeech, Mozilla Common Voice, and FLEURS. Accessible via download on Hugging Face, API endpoint, or private on‑premises deployment, Voxtral also offers domain‑specific fine‑tuning and advanced enterprise features.
  • 2
    Artemis

    Artemis

    TurinTech AI

    Artemis leverages Generative AI, multi-agent collaboration, genetic optimization, and contextual insights to analyze, optimize, and validate codebases at scale, transforming existing repositories into production-ready solutions that improve performance, reduce technical debt, and ensure enterprise-quality outcomes. Integrating seamlessly with your tools and repositories, it uses advanced indexing and scoring to pinpoint optimization opportunities, orchestrates multiple LLMs and proprietary algorithms to generate tailored improvements, and performs real-time validation and benchmarking to guarantee secure, scalable results. A modular Intelligence Engine powers extensions for profilers and security tools, ML models for anomaly detection, and an evaluation suite for rigorous testing, all designed to lower costs, boost innovation, and accelerate time-to-market without disrupting existing workflows.
  • 3
    IREN Cloud
    IREN’s AI Cloud is a GPU-cloud platform built on NVIDIA reference architecture and non-blocking 3.2 TB/s InfiniBand networking, offering bare-metal GPU clusters designed for high-performance AI training and inference workloads. The service supports a range of NVIDIA GPU models with specifications such as large amounts of RAM, vCPUs, and NVMe storage. The cloud is fully integrated and vertically controlled by IREN, giving clients operational flexibility, reliability, and 24/7 in-house support. Users can monitor performance metrics, optimize GPU spend, and maintain secure, isolated environments with private networking and tenant separation. It allows deployment of users’ own data, models, frameworks (TensorFlow, PyTorch, JAX), and container technologies (Docker, Apptainer) with root access and no restrictions. It is optimized to scale for demanding applications, including fine-tuning large language models.
  • 4
    Gentoro

    Gentoro

    Gentoro

    Gentoro is a platform built to empower enterprises to adopt agentic automation by bridging AI agents with real-world systems securely and at scale. It uses the Model Context Protocol (MCP) as its foundation, allowing developers to automatically convert OpenAPI specs or backend endpoints into production-ready MCP Tools, without writing custom integration code. Gentoro takes care of runtime concerns like logging, retries, monitoring, and cost optimization, while enforcing secure access, auditability, and governance policies (e.g., OAuth support, policy enforcement) whether deployed in a private cloud or on-premises. It is model- and framework-agnostic, meaning it supports integration with various LLMs and agent architectures. Gentoro helps avoid vendor lock-in and simplifies tool orchestration in enterprise environments by managing tool generation, runtime, security, and maintenance in one stack.
  • 5
    Tune AI

    Tune AI

    NimbleBox

    Leverage the power of custom models to build your competitive advantage. With our enterprise Gen AI stack, go beyond your imagination and offload manual tasks to powerful assistants instantly – the sky is the limit. For enterprises where data security is paramount, fine-tune and deploy generative AI models on your own cloud, securely.
  • 6
    Qualcomm AI Hub
    The Qualcomm AI Hub is a resource portal for developers aiming to build and deploy AI applications optimized for Qualcomm chipsets. With a library of pre-trained models, development tools, and platform-specific SDKs, it enables high-performance, low-power AI processing across smartphones, wearables, and edge devices.
  • 7
    Azure Model Catalog
    The Azure Model Catalog within Azure AI Foundry is a unified hub for discovering, deploying, and managing AI models across Microsoft’s ecosystem. It features a curated selection of advanced models such as GPT-5, GPT-4.1, Sora-2, DeepSeek-R1, Phi-4-mini-instruct, and Mistral-Nemo. Each model is optimized for specific tasks—ranging from reasoning and analytics to video generation and coding—offering enterprises flexible, high-performance AI capabilities. The catalog connects seamlessly with Azure OpenAI, Microsoft’s proprietary models, and partner offerings from Meta, Cohere, Mistral, and NVIDIA. Designed for developers and data scientists, it supports model experimentation, fine-tuning, and secure deployment through Azure’s enterprise-grade infrastructure. With robust compliance and scalability, the Azure Model Catalog empowers users to design intelligent, trustworthy, and production-ready AI solutions.
  • 8
    C

    C

    C

    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.
  • 9
    HTML

    HTML

    HTML

    HTML, short for HyperText Markup Language, is the markup language that is used by every website on the internet. HTML is code that websites use to build and structure every part of their website and web pages. HTML5 is a markup language used for structuring and presenting content on the World Wide Web. It is the fifth and final major HTML version that is a World Wide Web Consortium (W3C) recommendation. The current specification is known as the HTML Living Standard. It is maintained by the Web Hypertext Application Technology Working Group (WHATWG), a consortium of the major browser vendors (Apple, Google, Mozilla, and Microsoft). HTML5 includes detailed processing models to encourage more interoperable implementations; it extends, improves, and rationalizes the markup available for documents and introduces markup and application programming interfaces (APIs) for complex web applications. For the same reasons, HTML5 is also a candidate for cross-platform mobile applications.
  • 10
    Deep Infra

    Deep Infra

    Deep Infra

    Powerful, self-serve machine learning platform where you can turn models into scalable APIs in just a few clicks. Sign up for Deep Infra account using GitHub or log in using GitHub. Choose among hundreds of the most popular ML models. Use a simple rest API to call your model. Deploy models to production faster and cheaper with our serverless GPUs than developing the infrastructure yourself. We have different pricing models depending on the model used. Some of our language models offer per-token pricing. Most other models are billed for inference execution time. With this pricing model, you only pay for what you use. There are no long-term contracts or upfront costs, and you can easily scale up and down as your business needs change. All models run on A100 GPUs, optimized for inference performance and low latency. Our system will automatically scale the model based on your needs.
    Starting Price: $0.70 per 1M input tokens