Business Software for Langflow

Introducing Mistral NeMo, our latest and most advanced small model yet, featuring a cutting-edge 12 billion parameters and an expansive context length of 128,000 tokens, all released under the Apache 2.0 license. Developed in partnership with NVIDIA, Mistral NeMo excels in reasoning, world knowledge, and coding proficiency within its category. Its architecture adheres to industry standards, making it user-friendly and a seamless alternative for systems currently utilizing Mistral 7B. To facilitate widespread adoption among researchers and businesses, we have made available both pre-trained base and instruction-tuned checkpoints under the same Apache license. Notably, Mistral NeMo incorporates quantization awareness, allowing for FP8 inference without compromising performance. The model is also tailored for diverse global applications, adept in function calling and boasting a substantial context window. When compared to Mistral 7B, Mistral NeMo significantly outperforms in understanding and executing detailed instructions, showcasing enhanced reasoning skills and the ability to manage complex multi-turn conversations. Moreover, its design positions it as a strong contender for multi-lingual tasks, ensuring versatility across various use cases.

The Mixtral 8x22B represents our newest open model, establishing a new benchmark for both performance and efficiency in the AI sector. This sparse Mixture-of-Experts (SMoE) model activates only 39B parameters from a total of 141B, ensuring exceptional cost efficiency relative to its scale. Additionally, it demonstrates fluency in multiple languages, including English, French, Italian, German, and Spanish, while also possessing robust skills in mathematics and coding. With its native function calling capability, combined with the constrained output mode utilized on la Plateforme, it facilitates the development of applications and the modernization of technology stacks on a large scale. The model's context window can handle up to 64K tokens, enabling accurate information retrieval from extensive documents. We prioritize creating models that maximize cost efficiency for their sizes, thereby offering superior performance-to-cost ratios compared to others in the community. The Mixtral 8x22B serves as a seamless extension of our open model lineage, and its sparse activation patterns contribute to its speed, making it quicker than any comparable dense 70B model on the market. Furthermore, its innovative design positions it as a leading choice for developers seeking high-performance solutions.

In honor of Archimedes, whose 2311th anniversary we celebrate this year, we are excited to introduce our inaugural Mathstral model, a specialized 7B architecture tailored for mathematical reasoning and scientific exploration. This model features a 32k context window and is released under the Apache 2.0 license. Our intention behind contributing Mathstral to the scientific community is to enhance the pursuit of solving advanced mathematical challenges that necessitate intricate, multi-step logical reasoning. The launch of Mathstral is part of our wider initiative to support academic endeavors, developed in conjunction with Project Numina. Much like Isaac Newton during his era, Mathstral builds upon the foundation laid by Mistral 7B, focusing on STEM disciplines. It demonstrates top-tier reasoning capabilities within its category, achieving remarkable results on various industry-standard benchmarks. Notably, it scores 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, showcasing the performance differences by subject between Mathstral 7B and its predecessor, Mistral 7B, further emphasizing the advancements made in mathematical modeling. This initiative aims to foster innovation and collaboration within the mathematical community.

Mistral AI has launched two cutting-edge models designed for on-device computing and edge applications, referred to as "les Ministraux": Ministral 3B and Ministral 8B. These innovative models redefine the standards of knowledge, commonsense reasoning, function-calling, and efficiency within the sub-10B category. They are versatile enough to be utilized or customized for a wide range of applications, including managing complex workflows and developing specialized task-focused workers. Capable of handling up to 128k context length (with the current version supporting 32k on vLLM), Ministral 8B also incorporates a unique interleaved sliding-window attention mechanism to enhance both speed and memory efficiency during inference. Designed for low-latency and compute-efficient solutions, these models excel in scenarios such as offline translation, smart assistants that don't rely on internet connectivity, local data analysis, and autonomous robotics. Moreover, when paired with larger language models like Mistral Large, les Ministraux can effectively function as streamlined intermediaries, facilitating function-calling within intricate multi-step workflows, thereby expanding their applicability across various domains. This combination not only enhances performance but also broadens the scope of what can be achieved with AI in edge computing.

Mistral AI has unveiled two cutting-edge models specifically designed for on-device computing and edge use cases, collectively referred to as "les Ministraux": Ministral 3B and Ministral 8B. These innovative models stand out due to their capabilities in knowledge retention, commonsense reasoning, function-calling, and overall efficiency, all while remaining within the sub-10B parameter range. They boast support for a context length of up to 128k, making them suitable for a diverse range of applications such as on-device translation, offline smart assistants, local analytics, and autonomous robotics. Notably, Ministral 8B incorporates an interleaved sliding-window attention mechanism, which enhances both the speed and memory efficiency of inference processes. Both models are adept at serving as intermediaries in complex multi-step workflows, skillfully managing functions like input parsing, task routing, and API interactions based on user intent, all while minimizing latency and operational costs. Benchmark results reveal that les Ministraux consistently exceed the performance of similar models across a variety of tasks, solidifying their position in the market. As of October 16, 2024, these models are now available for developers and businesses, with Ministral 8B being offered at a competitive rate of $0.1 for every million tokens utilized. This pricing structure enhances accessibility for users looking to integrate advanced AI capabilities into their solutions.

On September 17, 2024, Mistral AI revealed a series of significant updates designed to improve both the accessibility and efficiency of their AI products. Among these updates was the introduction of a complimentary tier on "La Plateforme," their serverless platform that allows for the tuning and deployment of Mistral models as API endpoints, which gives developers a chance to innovate and prototype at zero cost. In addition, Mistral AI announced price reductions across their complete model range, highlighted by a remarkable 50% decrease for Mistral Nemo and an 80% cut for Mistral Small and Codestral, thereby making advanced AI solutions more affordable for a wider audience. The company also launched Mistral Small v24.09, a model with 22 billion parameters that strikes a favorable balance between performance and efficiency, making it ideal for various applications such as translation, summarization, and sentiment analysis. Moreover, they released Pixtral 12B, a vision-capable model equipped with image understanding features, for free on "Le Chat," allowing users to analyze and caption images while maintaining strong text-based performance. This suite of updates reflects Mistral AI's commitment to democratizing access to powerful AI technologies for developers everywhere.

Combine the rapid performance of in-memory solutions with the reliability of disk storage to unlock a variety of applications that extend beyond mere caching. By utilizing global databases with multi-region replication, you can enhance your system’s resilience. Experience true Serverless Kafka where costs can dwindle to zero, as you only incur charges based on your usage with a per-request pricing model. This allows you to produce and consume Kafka topics from virtually anywhere through a user-friendly built-in REST API. Begin with a free tier, and only pay for what you utilize, ensuring that costly server instances are a thing of the past. With Upstash, you can scale as needed without ever exceeding your predetermined cap price, providing peace of mind. The Upstash REST API also facilitates seamless integration with Cloudflare Workers and Fastly Compute@Edge. Thanks to the global database functionality, you can enjoy low-latency access to your data from any location. The combination of fast data access, ease of use, and flexible pay-per-request pricing position Upstash as an ideal solution for Jamstack and Serverless applications. Unlike traditional server models where you are charged by the hour or at a fixed rate, the Serverless approach ensures you only pay for what you request, making it a cost-effective alternative. This paradigm shift allows developers to focus on innovation rather than infrastructure management.

Airbyte is a data integration platform that operates on an open-source model, aimed at assisting organizations in unifying data from diverse sources into their data lakes, warehouses, or databases. With an extensive library of over 550 ready-made connectors, it allows users to craft custom connectors with minimal coding through low-code or no-code solutions. The platform is specifically designed to facilitate the movement of large volumes of data, thereby improving artificial intelligence processes by efficiently incorporating unstructured data into vector databases such as Pinecone and Weaviate. Furthermore, Airbyte provides adaptable deployment options, which help maintain security, compliance, and governance across various data models, making it a versatile choice for modern data integration needs. This capability is essential for businesses looking to enhance their data-driven decision-making processes.

Hugging Face is an AI community platform that provides state-of-the-art machine learning models, datasets, and APIs to help developers build intelligent applications. The platform’s extensive repository includes models for text generation, image recognition, and other advanced machine learning tasks. Hugging Face’s open-source ecosystem, with tools like Transformers and Tokenizers, empowers both individuals and enterprises to build, train, and deploy machine learning solutions at scale. It offers integration with major frameworks like TensorFlow and PyTorch for streamlined model development.

Chroma is an open-source embedding database that is designed specifically for AI applications. It provides a comprehensive set of tools for working with embeddings, making it easier for developers to integrate this technology into their projects. Chroma is focused on developing a database that continually learns and evolves. You can contribute by addressing an issue, submitting a pull request, or joining our Discord community to share your feature suggestions and engage with other users. Your input is valuable as we strive to enhance Chroma's functionality and usability.

Ollama stands out as a cutting-edge platform that prioritizes the delivery of AI-driven tools and services, aimed at facilitating user interaction and the development of AI-enhanced applications. It allows users to run AI models directly on their local machines. By providing a diverse array of solutions, such as natural language processing capabilities and customizable AI functionalities, Ollama enables developers, businesses, and organizations to seamlessly incorporate sophisticated machine learning technologies into their operations. With a strong focus on user-friendliness and accessibility, Ollama seeks to streamline the AI experience, making it an attractive choice for those eager to leverage the power of artificial intelligence in their initiatives. This commitment to innovation not only enhances productivity but also opens doors for creative applications across various industries.

The Mixtral 8x7B model is an advanced sparse mixture of experts (SMoE) system that boasts open weights and is released under the Apache 2.0 license. This model demonstrates superior performance compared to Llama 2 70B across various benchmarks while achieving inference speeds that are six times faster. Recognized as the leading open-weight model with a flexible licensing framework, Mixtral also excels in terms of cost-efficiency and performance. Notably, it competes with and often surpasses GPT-3.5 in numerous established benchmarks, highlighting its significance in the field. Its combination of accessibility, speed, and effectiveness makes it a compelling choice for developers seeking high-performing AI solutions.

Zep guarantees that your assistant retains and recalls previous discussions when they are pertinent. It identifies user intentions, creates semantic pathways, and initiates actions in mere milliseconds. Rapid and precise extraction of emails, phone numbers, dates, names, and various other elements ensures that your assistant maintains a flawless memory of users. It can categorize intent, discern emotions, and convert conversations into organized data. With retrieval, analysis, and extraction occurring in milliseconds, users experience no delays. Importantly, your data remains secure and is not shared with any external LLM providers. Our SDKs are available for your preferred programming languages and frameworks. Effortlessly enrich prompts with summaries of associated past dialogues, regardless of their age. Zep not only condenses and embeds but also executes retrieval workflows across your assistant's conversational history. It swiftly and accurately classifies chat interactions while gaining insights into user intent and emotional tone. By directing pathways based on semantic relevance, it triggers specific actions and efficiently extracts critical business information from chat exchanges. This comprehensive approach enhances user engagement and satisfaction by ensuring seamless communication experiences.

We are excited to unveil Codestral, our inaugural code generation model. This open-weight generative AI system is specifically crafted for tasks related to code generation, enabling developers to seamlessly write and engage with code via a unified instruction and completion API endpoint. As it becomes proficient in both programming languages and English, Codestral is poised to facilitate the creation of sophisticated AI applications tailored for software developers. With a training foundation that encompasses a wide array of over 80 programming languages—ranging from widely-used options like Python, Java, C, C++, JavaScript, and Bash to more niche languages such as Swift and Fortran—Codestral ensures a versatile support system for developers tackling various coding challenges and projects. Its extensive language capabilities empower developers to confidently navigate different coding environments, making Codestral an invaluable asset in the programming landscape.

Meta AI serves as a sophisticated assistant, adept at intricate reasoning, adhering to directions, visualizing concepts, and addressing subtle challenges. Built upon Meta's cutting-edge model, it is tailored to respond to a wide array of inquiries, assist in writing tasks, offer detailed guidance, and generate images for sharing with others. This versatile tool is accessible across Meta's suite of applications, smart eyewear, and online platforms, ensuring users have support at their fingertips. With its diverse functionalities, Meta AI aims to enhance creativity and streamline problem-solving for its users.

Mistral Large stands as the premier language model from Mistral AI, engineered for sophisticated text generation and intricate multilingual reasoning tasks such as text comprehension, transformation, and programming code development. This model encompasses support for languages like English, French, Spanish, German, and Italian, which allows it to grasp grammar intricacies and cultural nuances effectively. With an impressive context window of 32,000 tokens, Mistral Large can retain and reference information from lengthy documents with accuracy. Its abilities in precise instruction adherence and native function-calling enhance the development of applications and the modernization of tech stacks. Available on Mistral's platform, Azure AI Studio, and Azure Machine Learning, it also offers the option for self-deployment, catering to sensitive use cases. Benchmarks reveal that Mistral Large performs exceptionally well, securing its position as the second-best model globally that is accessible via an API, just behind GPT-4, illustrating its competitive edge in the AI landscape. Such capabilities make it an invaluable tool for developers seeking to leverage advanced AI technology.

Instructor serves as a powerful tool for developers who wish to derive structured data from natural language input by utilizing Large Language Models (LLMs). By integrating seamlessly with Python's Pydantic library, it enables users to specify the desired output structures through type hints, which not only streamlines schema validation but also enhances compatibility with various integrated development environments (IDEs). The platform is compatible with multiple LLM providers such as OpenAI, Anthropic, Litellm, and Cohere, thus offering a wide range of implementation options. Its customizable features allow users to define specific validators and tailor error messages, significantly improving the data validation workflow. Trusted by engineers from notable platforms like Langflow, Instructor demonstrates a high level of reliability and effectiveness in managing structured outputs driven by LLMs. Additionally, the reliance on Pydantic and type hints simplifies the process of schema validation and prompting, requiring less effort and code from developers while ensuring smooth integration with their IDEs. This adaptability makes Instructor an invaluable asset for developers looking to enhance their data extraction and validation processes.

Collection Management streamlines the accounts receivable process within Microsoft Dynamics 365 Business Central by capturing each customer's preferred payment method during the creation of orders, invoices, or credit memos, while also automating direct-debit payment suggestions. This system promotes timely invoice payments by transforming the payment experience into straightforward, guided workflows that eliminate unnecessary steps, thereby enhancing user confidence and improving cash flow. Users enjoy the advantages of efficient debt collection and can easily monitor and manage agreement statuses through a centralized dashboard in Business Central. Robust integrations with top Danish collection service providers facilitate smooth communication from the initiation of payments to real-time status updates, effectively removing worries about format discrepancies. The solution is designed to scale effortlessly, catering to both B2B and B2C operations under a consistent interface, and it consolidates various service endpoints into a single, efficient collection provider, ensuring flexibility and ease of use. Moreover, this comprehensive approach not only streamlines the payment process but also fosters stronger relationships between businesses and their customers.

We are an intelligent HelpDesk. We will optimize your management processes, increase productivity of your team, and increase the efficiency in your support. Your customers will have more options by opening tickets from different devices. You have more control over how you configure your customers' SLA. The inventory management app can be used to monitor and control the entire equipment park of customers. You can increase the productivity of your technical support staff with intelligent and automated inventory management. Optimize your customer relationship and management! Receive alerts about key machine features via your dashboard. Automation, workflow and ticket triggers. Password Vault, satisfaction survey and ticket scheduling. Follow customer, service catalog, follow tickets, ticket conference, advanced dashboard.

A leading platform for business news globally, delivering essential updates along with live broadcasts each weekday. Yahoo Finance offers complimentary stock quotes, current news, tools for portfolio management, worldwide market information, charting options, social engagement, and mortgage rates that assist you in overseeing your financial well-being effectively. With a comprehensive suite of resources, it aims to empower individuals in their financial journeys.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

Vectara offers LLM-powered search as-a-service. The platform offers a complete ML search process, from extraction and indexing to retrieval and re-ranking as well as calibration. API-addressable for every element of the platform. Developers can embed the most advanced NLP model for site and app search in minutes. Vectara automatically extracts text form PDF and Office to JSON HTML XML CommonMark, and many other formats. Use cutting-edge zero-shot models that use deep neural networks to understand language to encode at scale. Segment data into any number indexes that store vector encodings optimized to low latency and high recall. Use cutting-edge, zero shot neural network models to recall candidate results from millions upon millions of documents. Cross-attentional neural networks can increase the precision of retrieved answers. They can merge and reorder results. Focus on the likelihood that the retrieved answer is a probable answer to your query.

Pixtral Large is an expansive multimodal model featuring 124 billion parameters, crafted by Mistral AI and enhancing their previous Mistral Large 2 framework. This model combines a 123-billion-parameter multimodal decoder with a 1-billion-parameter vision encoder, allowing it to excel in the interpretation of various content types, including documents, charts, and natural images, all while retaining superior text comprehension abilities. With the capability to manage a context window of 128,000 tokens, Pixtral Large can efficiently analyze at least 30 high-resolution images at once. It has achieved remarkable results on benchmarks like MathVista, DocVQA, and VQAv2, outpacing competitors such as GPT-4o and Gemini-1.5 Pro. Available for research and educational purposes under the Mistral Research License, it also has a Mistral Commercial License for business applications. This versatility makes Pixtral Large a valuable tool for both academic research and commercial innovations.

Composio serves as an integration platform aimed at strengthening AI agents and Large Language Models (LLMs) by allowing easy connectivity to more than 150 tools with minimal coding efforts. This platform accommodates a diverse range of agentic frameworks and LLM providers, enabling efficient function calling for streamlined task execution. Composio boasts an extensive repository of tools such as GitHub, Salesforce, file management systems, and code execution environments, empowering AI agents to carry out a variety of actions and respond to multiple triggers. One of its standout features is managed authentication, which enables users to control the authentication processes for every user and agent through a unified dashboard. Additionally, Composio emphasizes a developer-centric integration methodology, incorporates built-in management for authentication, and offers an ever-growing collection of over 90 tools ready for connection. Furthermore, it enhances reliability by 30% through the use of simplified JSON structures and improved error handling, while also ensuring maximum data security with SOC Type II compliance. Overall, Composio represents a robust solution for integrating tools and optimizing AI capabilities across various applications.

AI Crypto-Kit enables developers to create crypto agents by effortlessly connecting with top Web3 platforms such as Coinbase and OpenSea, facilitating the automation of various real-world crypto and DeFi workflows. In just minutes, developers can design AI-driven crypto automation solutions, which encompass applications like trading agents, community reward systems, management of Coinbase wallets, portfolio tracking, market analysis, and yield farming strategies. The platform is equipped with features tailored for crypto agents, including comprehensive management of agent authentication that accommodates OAuth, API keys, and JWT, along with automatic token refresh capabilities; optimization for LLM function calling to guarantee enterprise-level reliability; compatibility with over 20 agentic frameworks, including Pippin, LangChain, and LlamaIndex; integration with more than 30 Web3 platforms such as Binance, Aave, OpenSea, and Chainlink; and it also provides SDKs and APIs for seamless interactions with agentic applications, available in both Python and TypeScript. Additionally, the robust framework of AI Crypto-Kit allows developers to scale their projects efficiently, enhancing the overall potential for innovation in the crypto space.