On-Premises Business Software

When it comes to converting HTML files into PDFs, there are numerous factors to consider in order to achieve exceptional print quality. Whether you're transforming a webpage or utilizing Database Publishing, there exist methods to convert even intricate HTML into PDF format. PDFreactor offers a robust solution as an HTML to PDF converter, boasting an extensive array of features that surpass the capabilities of most other tools, thereby elevating your PDF conversion experience. With ease, you can convert HTML to PDF while enjoying support for HTML5, CSS3, and JavaScript. The software features APIs compatible with various programming languages, including JavaScript, Java, PHP, .NET, Python, Ruby, Perl, Node.js, and both SOAP and REST protocols, along with a Docker Image option. Additionally, a free personal license is available, making PDFreactor an ideal choice for web applications such as Database Publishing, Web-to-Print, PIM, DMS, MDM, DAM, WCMS, and VDP. Typically, it is employed for server-side HTML to PDF conversions, which can range from documents driven by dynamic data—like reports, invoices, and forms—to creating sophisticated, high-quality PDFs suitable for various purposes. Ultimately, PDFreactor empowers users to efficiently handle diverse printing needs while maintaining high standards of quality.

Wordly delivers live AI translation, captioning, transcription, and interpretation for in-person, virtual, and hybrid meetings and events. It instantly translates speakers into audio and captions for dozens of languages, eliminating the need for human interpreters or specialized gear. Additionally, Wordly offers video translation, video subtitles, audio translation, and audio transcription services. Attendees simply select their preferred language and use their phone, tablet, or computer to access the live translation. The platform is available on-demand 24/7, integrates seamlessly with all major video conferencing and virtual platforms, and requires no IT support for implementation. With Wordly, it’s fast, easy, and affordable to boost inclusivity, engagement, and learning. Thousands of businesses and millions of attendees have used Wordly across tech, financial services, healthcare, manufacturing, education, government, religious, and non-profit sectors. Its secure, cloud-based platform ensures scalability for events of any size, from small meetings to large global conferences. This innovative solution truly removes language barriers, fostering a more connected and productive global environment.

Introducing a no-code platform designed for data cleaning, preparation, and machine learning tailored specifically for business applications, with options for on-premise installation to ensure data privacy. You can take advantage of Sweephy's complimentary modules right away, which offer no-code tools powered by machine learning. Simply provide the data and the keywords you wish to analyze, and our model will generate a comprehensive report based on those keywords. Beyond just a basic word check, our advanced model conducts semantic and grammatical classification to enhance accuracy. We can also assist in identifying duplicate or similar records within your database, facilitating the creation of a consolidated user database from various data sources using the Sweephy Dedupu API. Additionally, with our API, you can effortlessly develop object detection models by fine-tuning existing pre-trained models; just share your use cases and we will craft a suitable model tailored to your needs. This could include tasks like classifying documents, PDFs, receipts, or invoices. Simply upload your image dataset, and our model will efficiently eliminate any noise from the images or develop a specialized model to meet your specific business requirements. Our commitment to customer satisfaction ensures you receive a solution perfectly aligned with your goals.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

Threat, incident and event reports for security teams. SIRV's award winning artificial intelligence solution visualises threats to your organisation. Monitor situational risk and learn about activism, crime and adjacent threats. Prepare, handle and recover from major incidents. Drive risk based safety and security decisions: Combine open source intelligence with the SIRV field report platform Founded in 2012: Systematic Intelligence Risk Valuation (SIRV)

Introducing Activaire Curator, the most creative and enjoyable solution for playing music at your business venues. Whether you operate a major corporation or a local establishment, our team of curators is dedicated to providing music that perfectly matches your atmosphere. Every track is carefully selected by a human expert and comes with the necessary licensing for commercial use. To access Activaire Curator, you need to be an active subscriber to our services. Our expertly chosen playlists are crafted by enthusiasts who align with your brand's essence, making the process incredibly straightforward. With exceptional service, we engage with you to gain insight into your brand and target audience. Our skilled team of music lovers curates selections that resonate with your unique sonic identity. Simply connect Activaire’s Epicentre hardware to your sound system and download our Curator app to start enjoying the tunes. We’re here to support you every step of the way, providing unmatched customer service, while you can relax knowing we manage all licensing requirements for you. Enjoy a seamless musical experience tailored specifically to your business needs.

LIBRA is an integrated ERP system that includes all the standard ERP modules. The system was designed to meet today's complex business requirements. It has a robust, yet flexible accounting structure that will satisfy the most demanding accountants. LIBRA gives you a complete view of your business activities, including inventory, warehouse, and financial management, as well as business operations. Libra Financials has been a trusted partner for more than 500 companies in North Africa, the Gulf, and Lebanon for more than 30 years.

Refact.ai is an advanced AI-powered assistant that integrates directly into your IDE, offering intelligent code completion, real-time code suggestions, and automatic refactoring to streamline the coding process. By using the AI model trained on your codebase, Refact.ai adapts to your team's style, providing highly relevant recommendations to enhance productivity. Developers can also fine-tune the assistant to better suit their unique requirements, making it a powerful tool for personalized coding assistance. With support for all major IDEs and secure on-premise deployment, Refact.ai empowers developers to increase code quality, reduce time spent on manual tasks, and achieve faster results.

Postgres now features open-source vector similarity search capabilities. This allows for both exact and approximate nearest neighbor searches utilizing L2 distance, inner product, and cosine distance metrics. Additionally, this functionality enhances the database's ability to manage and analyze complex data efficiently.

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.

Faiss is a powerful library designed for the efficient search and clustering of dense vector data. It provides algorithms capable of searching through vector sets of varying sizes, even those that may exceed RAM capacity. Additionally, it includes tools for evaluation and fine-tuning parameters to optimize performance. Written in C++, Faiss offers comprehensive wrappers for Python, making it accessible for a broader range of users. Notably, many of its most effective algorithms are optimized for GPU execution, enhancing computational speed. This library is a product of Facebook AI Research, reflecting their commitment to advancing artificial intelligence technologies. Its versatility makes Faiss a valuable resource for researchers and developers alike.

Cody is an advanced AI coding assistant developed by Sourcegraph to enhance the efficiency and quality of software development. It integrates seamlessly with popular Integrated Development Environments (IDEs) such as VS Code, Visual Studio, Eclipse, and various JetBrains IDEs, providing features like AI-driven chat, code autocompletion, and inline editing without altering existing workflows. Designed to support enterprises, Cody emphasizes consistency and quality across entire codebases by utilizing comprehensive context and shared prompts. It also extends its contextual understanding beyond code by integrating with tools like Notion, Linear, and Prometheus, thereby gathering a holistic view of the development environment. By leveraging the latest Large Language Models (LLMs), including Claude Sonnet 4 and GPT-4o, Cody offers tailored assistance that can be optimized for specific use cases, balancing speed and performance. Developers have reported significant productivity gains, with some noting time savings of approximately 5-6 hours per week and a doubling of coding speed when using Cody.

We are excited to introduce Jurassic-2, the newest iteration of AI21 Studio's foundation models, which represents a major advancement in artificial intelligence, boasting exceptional quality and innovative features. In addition to this, we are unveiling our tailored APIs that offer seamless reading and writing functionalities, surpassing those of our rivals. At AI21 Studio, our mission is to empower developers and businesses to harness the potential of reading and writing AI, facilitating the creation of impactful real-world applications. Today signifies a pivotal moment with the launch of Jurassic-2 and our Task-Specific APIs, enabling you to effectively implement generative AI in production settings. Known informally as J2, Jurassic-2 showcases remarkable enhancements in quality, including advanced zero-shot instruction-following, minimized latency, and support for multiple languages. Furthermore, our specialized APIs are designed to provide developers with top-tier tools that excel in executing specific reading and writing tasks effortlessly, ensuring you have everything needed to succeed in your projects. Together, these advancements set a new standard in the AI landscape, paving the way for innovative solutions.

Baserow is the open-source platform that empowers you to build scalable databases and applications without code. It supports real-time collaboration, workflow automation, and streamlined data management. • User-friendly interface: With Baserow, you don't need to be a tech wizard to create powerful databases. Its intuitive drag-and-drop interface makes it a breeze for anyone on your team to design, customize, and manage data without any hassle. • Collaboration: Multiple users can work on the same database in real-time, ensuring everyone's always on the same page. Share your progress with teammates, assign tasks, and watch your projects flourish. • Fully customizable: Your team is unique, and your database should be too. Tailor every aspect of your database to fit your specific needs. From custom fields to personalized views, Baserow gives you the freedom to build a database that's as individual as your team. • Open source advantage: Being open source means Baserow is continuously improving with contributions from its community. You get a reliable, secure platform that grows with you, plus the flexibility to modify it as you see fit. This includes having no vendor lock-in, which is critical for business continuity.

FLAN-T5, introduced in the paper titled "Scaling Instruction-Finetuned Language Models," represents an improved iteration of T5 that has undergone fine-tuning across a diverse range of tasks, thereby enhancing its capabilities. This advancement allows it to better understand and respond to various instructional prompts.

This repository showcases an implementation of model parallel autoregressive transformers utilizing GPUs, leveraging the capabilities of the DeepSpeed library. It serves as a record of EleutherAI's framework designed for training extensive language models on GPU architecture. Currently, it builds upon NVIDIA's Megatron Language Model, enhanced with advanced techniques from DeepSpeed alongside innovative optimizations. Our goal is to create a centralized hub for aggregating methodologies related to the training of large-scale autoregressive language models, thereby fostering accelerated research and development in the field of large-scale training. We believe that by providing these resources, we can significantly contribute to the progress of language model research.

GPT-J represents an advanced language model developed by EleutherAI, known for its impressive capabilities. When it comes to performance, GPT-J showcases a proficiency that rivals OpenAI's well-known GPT-3 in various zero-shot tasks. Remarkably, it has even outperformed GPT-3 in specific areas, such as code generation. The most recent version of this model, called GPT-J-6B, is constructed using a comprehensive linguistic dataset known as The Pile, which is publicly accessible and consists of an extensive 825 gibibytes of language data divided into 22 unique subsets. Although GPT-J possesses similarities to ChatGPT, it's crucial to highlight that it is primarily intended for text prediction rather than functioning as a chatbot. In a notable advancement in March 2023, Databricks unveiled Dolly, a model that is capable of following instructions and operates under an Apache license, further enriching the landscape of language models. This evolution in AI technology continues to push the boundaries of what is possible in natural language processing.

Pythia integrates the examination of interpretability and scaling principles to gain insights into the progression and transformation of knowledge throughout the training of autoregressive transformer models. This approach enables a deeper understanding of the mechanisms behind model learning and adaptation.

AutoGPT is a pioneering open-source tool that demonstrates the potential of the GPT-4 language model. This innovative application utilizes GPT-4 to link together various "thoughts" generated by the model, enabling it to independently pursue any objectives you define. As one of the initial implementations of GPT-4 functioning entirely on its own, Auto-GPT expands the frontiers of artificial intelligence capabilities. It offers features such as 🌐 the ability to access the internet for conducting searches and collecting information, 💾 management of both long-term and short-term memory, 🧠 utilization of GPT-4 instances for generating text, 🔗 connections to widely used websites and platforms, 🗃️ capabilities for file storage and summarization, and 🔌 the option to extend functionality through plugins. This makes it a versatile tool for various applications.

This Python script exemplifies an AI-driven task management system that leverages both OpenAI and Chroma to manage tasks effectively. The core concept of this system is that it generates tasks informed by prior outcomes and a set goal. Utilizing OpenAI's natural language processing (NLP), the script formulates new tasks aligned with its objectives while employing Chroma to archive and access task outcomes for added context. This implementation serves as a simplified version of the original Task-Driven Autonomous Agent. The script operates within an endless loop executing a series of defined steps, which include: 1. Retrieving the initial task from the list of tasks. 2. Dispatching the task to the execution agent, which utilizes OpenAI's API to accomplish the task within the contextual framework. 3. Enhancing the result obtained and saving it in Chroma for future reference. 4. Generating additional tasks and rearranging the task list according to the overarching objective and the results from the completed task, ensuring continuous adaptation and improvement in task management. This approach allows for a dynamic and responsive task management system that evolves with each completed task.

Our no-code platform allows you to rapidly develop a tailored AI chatbot that is trained specifically on your data within moments. Enhance the efficiency of customer support, facilitate the onboarding process for new employees, and much more! This AI chatbot is capable of addressing common inquiries and managing straightforward support tasks, enabling your team to dedicate more time to delivering personalized assistance to clients. Furthermore, it can provide 24/7 support for customer queries, ensuring that assistance is readily available, even during off-hours. Integrating this AI chatbot into your website is incredibly simple—just copy and paste our code, and you'll be ready to offer immediate support to your visitors, enhancing their overall experience and satisfaction. With this seamless integration, you can transform the way you interact with customers and improve your service quality.

Stable LM represents a significant advancement in the field of language models by leveraging our previous experience with open-source initiatives, particularly in collaboration with EleutherAI, a nonprofit research organization. This journey includes the development of notable models such as GPT-J, GPT-NeoX, and the Pythia suite, all of which were trained on The Pile open-source dataset, while many contemporary open-source models like Cerebras-GPT and Dolly-2 have drawn inspiration from this foundational work. Unlike its predecessors, Stable LM is trained on an innovative dataset that is three times the size of The Pile, encompassing a staggering 1.5 trillion tokens. We plan to share more information about this dataset in the near future. The extensive nature of this dataset enables Stable LM to excel remarkably in both conversational and coding scenarios, despite its relatively modest size of 3 to 7 billion parameters when compared to larger models like GPT-3, which boasts 175 billion parameters. Designed for versatility, Stable LM 3B is a streamlined model that can efficiently function on portable devices such as laptops and handheld gadgets, making us enthusiastic about its practical applications and mobility. Overall, the development of Stable LM marks a pivotal step towards creating more efficient and accessible language models for a wider audience.

Dolly is an economical large language model that surprisingly demonstrates a notable level of instruction-following abilities similar to those seen in ChatGPT. While the Alpaca team's research revealed that cutting-edge models could be encouraged to excel in high-quality instruction adherence, our findings indicate that even older open-source models with earlier architectures can display remarkable behaviors when fine-tuned on a modest set of instructional training data. By utilizing an existing open-source model with 6 billion parameters from EleutherAI, Dolly has been slightly adjusted to enhance its ability to follow instructions, showcasing skills like brainstorming and generating text that were absent in its original form. This approach not only highlights the potential of older models but also opens new avenues for leveraging existing technologies in innovative ways.

The multilingual T5 (mT5) is a highly versatile pretrained text-to-text transformer model, developed using a methodology akin to that of T5. This repository serves as a resource for replicating the findings outlined in the mT5 research paper. mT5 has been trained on the extensive mC4 corpus, which encompasses 101 different languages, including but not limited to Afrikaans, Albanian, Amharic, Arabic, Armenian, Azerbaijani, Basque, Belarusian, Bengali, Bulgarian, Burmese, Catalan, Cebuano, Chichewa, Chinese, Corsican, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hmong, Hungarian, Icelandic, Igbo, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Latin, Latvian, Lithuanian, Luxembourgish, Macedonian, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Mongolian, Nepali, Norwegian, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Samoan, Scottish Gaelic, Serbian, Shona, Sindhi, and many others. This impressive range of languages makes mT5 a valuable tool for multilingual applications across various fields.

Training cutting-edge language models presents significant challenges; it demands vast computational resources, intricate distributed computing strategies, and substantial machine learning knowledge. Consequently, only a limited number of organizations embark on the journey of developing large language models (LLMs) from the ground up. Furthermore, many of those with the necessary capabilities and knowledge have begun to restrict access to their findings, indicating a notable shift from practices observed just a few months ago. At Cerebras, we are committed to promoting open access to state-of-the-art models. Therefore, we are excited to share with the open-source community the launch of Cerebras-GPT, which consists of a series of seven GPT models with parameter counts ranging from 111 million to 13 billion. Utilizing the Chinchilla formula for training, these models deliver exceptional accuracy while optimizing for computational efficiency. Notably, Cerebras-GPT boasts quicker training durations, reduced costs, and lower energy consumption compared to any publicly accessible model currently available. By releasing these models, we hope to inspire further innovation and collaboration in the field of machine learning.