Pinecone Rerank v0 Integrations

Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.

Around 25 million engineers work across dozens of distinct functions. Engineers are using New Relic as every company is becoming a software company to gather real-time insight and trending data on the performance of their software. This allows them to be more resilient and provide exceptional customer experiences. New Relic is the only platform that offers an all-in one solution. New Relic offers customers a secure cloud for all metrics and events, powerful full-stack analytics tools, and simple, transparent pricing based on usage. New Relic also has curated the largest open source ecosystem in the industry, making it simple for engineers to get started using observability.

AWS is the leading provider of cloud computing, delivering over 200 fully featured services to organizations worldwide. Its offerings cover everything from infrastructure—such as compute, storage, and networking—to advanced technologies like artificial intelligence, machine learning, and agentic AI. Businesses use AWS to modernize legacy systems, run high-performance workloads, and build scalable, secure applications. Core services like Amazon EC2, Amazon S3, and Amazon DynamoDB provide foundational capabilities, while advanced solutions like SageMaker and AWS Transform enable AI-driven transformation. The platform is supported by a global infrastructure that includes 38 regions, 120 availability zones, and 400+ edge locations, ensuring low latency and high reliability. AWS integrates with leading enterprise tools, developer SDKs, and partner ecosystems, giving teams the flexibility to adopt cloud at their own pace. Its training and certification programs help individuals and companies grow cloud expertise with industry-recognized credentials. With its unmatched breadth, depth, and proven track record, AWS empowers organizations to innovate and compete in the digital-first economy.

Amazon Bedrock is a comprehensive service that streamlines the development and expansion of generative AI applications by offering access to a diverse range of high-performance foundation models (FMs) from top AI organizations, including AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon. Utilizing a unified API, developers have the opportunity to explore these models, personalize them through methods such as fine-tuning and Retrieval Augmented Generation (RAG), and build agents that can engage with various enterprise systems and data sources. As a serverless solution, Amazon Bedrock removes the complexities associated with infrastructure management, enabling the effortless incorporation of generative AI functionalities into applications while prioritizing security, privacy, and ethical AI practices. This service empowers developers to innovate rapidly, ultimately enhancing the capabilities of their applications and fostering a more dynamic tech ecosystem.

GitHub Copilot represents the next evolution of intelligent software development, combining AI-driven coding, collaboration, and automation in a single ecosystem. It seamlessly integrates with GitHub and leading IDEs, transforming natural language prompts into working code, tests, and documentation. The new Agent Mode allows developers to delegate tasks—Copilot autonomously writes, executes, and validates code using GitHub Actions, delivering ready-to-review pull requests. Developers can interact through Copilot Chat, switch between models like GPT-5, Claude Sonnet 4, and Gemini 2.0 Flash, and refine results with contextual feedback. Next Edit Suggestions and automated code review ensure project-wide consistency, helping teams catch bugs before they reach production. With Copilot Spaces, teams can organize shared context—code, notes, and knowledge—to produce tailored, high-quality results. Available in Free, Pro, and Pro+ plans, Copilot scales from individuals to enterprises with flexible model access and premium capabilities. Ultimately, GitHub Copilot transforms development from manual iteration to AI-augmented collaboration, enabling engineers to focus on innovation instead of boilerplate.

Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. Founded in 2005, Box simplifies work for leading global organizations, including AstraZeneca, JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. Visit box.com to learn more

Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.

Microsoft Azure serves as a versatile cloud computing platform that facilitates swift and secure development, testing, and management of applications. With Azure, you can innovate purposefully, transforming your concepts into actionable solutions through access to over 100 services that enable you to build, deploy, and manage applications in various environments—be it in the cloud, on-premises, or at the edge—utilizing your preferred tools and frameworks. The continuous advancements from Microsoft empower your current development needs while also aligning with your future product aspirations. Committed to open-source principles and accommodating all programming languages and frameworks, Azure allows you the freedom to build in your desired manner and deploy wherever it suits you best. Whether you're operating on-premises, in the cloud, or at the edge, Azure is ready to adapt to your current setup. Additionally, it offers services tailored for hybrid cloud environments, enabling seamless integration and management. Security is a foundational aspect, reinforced by a team of experts and proactive compliance measures that are trusted by enterprises, governments, and startups alike. Ultimately, Azure represents a reliable cloud solution, backed by impressive performance metrics that validate its trustworthiness. This platform not only meets your needs today but also equips you for the evolving challenges of tomorrow.

Datadog is the cloud-age monitoring, security, and analytics platform for developers, IT operation teams, security engineers, and business users. Our SaaS platform integrates monitoring of infrastructure, application performance monitoring, and log management to provide unified and real-time monitoring of all our customers' technology stacks. Datadog is used by companies of all sizes and in many industries to enable digital transformation, cloud migration, collaboration among development, operations and security teams, accelerate time-to-market for applications, reduce the time it takes to solve problems, secure applications and infrastructure and understand user behavior to track key business metrics.

Snowflake offers a unified AI Data Cloud platform that transforms how businesses store, analyze, and leverage data by eliminating silos and simplifying architectures. It features interoperable storage that enables seamless access to diverse datasets at massive scale, along with an elastic compute engine that delivers leading performance for a wide range of workloads. Snowflake Cortex AI integrates secure access to cutting-edge large language models and AI services, empowering enterprises to accelerate AI-driven insights. The platform’s cloud services automate and streamline resource management, reducing complexity and cost. Snowflake also offers Snowgrid, which securely connects data and applications across multiple regions and cloud providers for a consistent experience. Their Horizon Catalog provides built-in governance to manage security, privacy, compliance, and access control. Snowflake Marketplace connects users to critical business data and apps to foster collaboration within the AI Data Cloud network. Serving over 11,000 customers worldwide, Snowflake supports industries from healthcare and finance to retail and telecom.

OpenAI aims to guarantee that artificial general intelligence (AGI)—defined as highly autonomous systems excelling beyond human capabilities in most economically significant tasks—serves the interests of all humanity. While we intend to develop safe and advantageous AGI directly, we consider our mission successful if our efforts support others in achieving this goal. You can utilize our API for a variety of language-related tasks, including semantic search, summarization, sentiment analysis, content creation, translation, and beyond, all with just a few examples or by clearly stating your task in English. A straightforward integration provides you with access to our continuously advancing AI technology, allowing you to explore the API’s capabilities through these illustrative completions and discover numerous potential applications.

Enable enterprises and developers to harness advanced neural search, generative AI, and multimodal services by leveraging cutting-edge LMOps, MLOps, and cloud-native technologies. The presence of multimodal data is ubiquitous, ranging from straightforward tweets and Instagram photos to short TikTok videos, audio clips, Zoom recordings, PDFs containing diagrams, and 3D models in gaming. While this data is inherently valuable, its potential is often obscured by various modalities and incompatible formats. To facilitate the development of sophisticated AI applications, it is essential to first address the challenges of search and creation. Neural Search employs artificial intelligence to pinpoint the information you seek, enabling a description of a sunrise to correspond with an image or linking a photograph of a rose to a melody. On the other hand, Generative AI, also known as Creative AI, utilizes AI to produce content that meets user needs, capable of generating images based on descriptions or composing poetry inspired by visuals. The interplay of these technologies is transforming the landscape of information retrieval and creative expression.

Vercel combines the best in developer experience with a laser-focused focus on end-user performance. Our platform allows frontend teams to do their best work. Next.js is a React framework Vercel created with Google and Facebook. It's loved by developers. Next.js powers some of the most popular websites, including Twilio and Washington Post. It is used for news, e-commerce and travel. Vercel is the best place for any frontend app to be deployed. Start by connecting to our global edge network with zero configuration. Scale dynamically to millions upon millions of pages without breaking a sweat. Live editing for your UI components. Connect your pages to any data source or headless CMS and make them work in every dev environment. All of our cloud primitives, from caching to Serverless functions, work perfectly on localhost.

Cohere is a robust enterprise AI platform that empowers developers and organizations to create advanced applications leveraging language technologies. With a focus on large language models (LLMs), Cohere offers innovative solutions for tasks such as text generation, summarization, and semantic search capabilities. The platform features the Command family designed for superior performance in language tasks, alongside Aya Expanse, which supports multilingual functionalities across 23 different languages. Emphasizing security and adaptability, Cohere facilitates deployment options that span major cloud providers, private cloud infrastructures, or on-premises configurations to cater to a wide array of enterprise requirements. The company partners with influential industry players like Oracle and Salesforce, striving to weave generative AI into business applications, thus enhancing automation processes and customer interactions. Furthermore, Cohere For AI, its dedicated research lab, is committed to pushing the boundaries of machine learning via open-source initiatives and fostering a collaborative global research ecosystem. This commitment to innovation not only strengthens their technology but also contributes to the broader AI landscape.

Revolutionary Cloud-Native ETL Tool: Quickly Load and Transform Data for Your Cloud Data Warehouse. We have transformed the conventional ETL approach by developing a solution that integrates data directly within the cloud environment. Our innovative platform takes advantage of the virtually limitless storage offered by the cloud, ensuring that your projects can scale almost infinitely. By operating within the cloud, we simplify the challenges associated with transferring massive data quantities. Experience the ability to process a billion rows of data in just fifteen minutes, with a seamless transition from launch to operational status in a mere five minutes. In today’s competitive landscape, businesses must leverage their data effectively to uncover valuable insights. Matillion facilitates your data transformation journey by extracting, migrating, and transforming your data in the cloud, empowering you to derive fresh insights and enhance your decision-making processes. This enables organizations to stay ahead in a rapidly evolving market.

LangChain provides a comprehensive framework that empowers developers to build and scale intelligent applications using large language models (LLMs). By integrating data and APIs, LangChain enables context-aware applications that can perform reasoning tasks. The suite includes LangGraph, a tool for orchestrating complex workflows, and LangSmith, a platform for monitoring and optimizing LLM-driven agents. LangChain supports the full lifecycle of LLM applications, offering tools to handle everything from initial design and deployment to post-launch performance management. Its flexibility makes it an ideal solution for businesses looking to enhance their applications with AI-powered reasoning and automation.

Nexla's automated approach to data engineering has made it possible for data users for the first time to access ready-to-use data without the need for any connectors or code. Nexla is unique in that it combines no-code and low-code with a developer SDK, bringing together users of all skill levels on one platform. Nexla's data-as a-product core combines integration preparation, monitoring, delivery, and monitoring of data into one system, regardless of data velocity or format. Nexla powers mission-critical data for JPMorgan and Doordash, LinkedIn LiveRamp, J&J, as well as other leading companies across industries.

Anyscale is a configurable AI platform that unifies tools and infrastructure to accelerate the development, deployment, and scaling of AI and Python applications using Ray. At its core is RayTurbo, an enhanced version of the open-source Ray framework, optimized for faster, more reliable, and cost-effective AI workloads, including large language model inference. The platform integrates smoothly with popular developer environments like VSCode and Jupyter notebooks, allowing seamless code editing, job monitoring, and dependency management. Users can choose from flexible deployment models, including hosted cloud services, on-premises machine pools, or existing Kubernetes clusters, maintaining full control over their infrastructure. Anyscale supports production-grade batch workloads and HTTP services with features such as job queues, automatic retries, Grafana observability dashboards, and high availability. It also emphasizes robust security with user access controls, private data environments, audit logs, and compliance certifications like SOC 2 Type II. Leading companies report faster time-to-market and significant cost savings with Anyscale’s optimized scaling and management capabilities. The platform offers expert support from the original Ray creators, making it a trusted choice for organizations building complex AI systems.

Apify serves as a powerful platform for web scraping and automation, allowing users to transform any website into an accessible API. Developers can independently create workflows for data extraction or web automation, while non-developers have the option to purchase ready-made solutions. With our user-friendly scraping tools, you can begin harvesting vast quantities of structured data immediately or collaborate with us to address your specific needs. Our services deliver quick and precise results that you can depend on. Enhance your operations by automating repetitive tasks and expediting workflows through our versatile automation software. This automation empowers you to outperform your competitors with greater efficiency and less exertion. You can export the scraped data in formats that machines can easily read, such as JSON or CSV. Apify also allows for seamless integration with your existing workflows in platforms like Zapier or Make, as well as any other web application utilizing APIs and webhooks. Our intelligent management of both data center and residential proxies, paired with top-tier browser fingerprinting technology, ensures that Apify bots are virtually indistinguishable from human users. With Apify, you can unlock the full potential of web data for your business or projects.

Amazon SageMaker is a comprehensive machine learning platform that integrates powerful tools for model building, training, and deployment in one cohesive environment. It combines data processing, AI model development, and collaboration features, allowing teams to streamline the development of custom AI applications. With SageMaker, users can easily access data stored across Amazon S3 data lakes and Amazon Redshift data warehouses, facilitating faster insights and AI model development. It also supports generative AI use cases, enabling users to develop and scale applications with cutting-edge AI technologies. The platform’s governance and security features ensure that data and models are handled with precision and compliance throughout the entire ML lifecycle. Furthermore, SageMaker provides a unified development studio for real-time collaboration, speeding up data discovery and model deployment.

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.

TwelveLabs is revolutionizing video intelligence with its powerful AI platform designed to understand and analyze video content at a deep level. Unlike traditional video search tools, TwelveLabs’ AI can comprehend the entire context of a video, including the spatial and temporal relationships between scenes, making it possible to discover deep insights and automate workflows. It provides fast, context-aware search results across multiple data points, including speech, text, visuals, and audio. Whether for media, advertising, or enterprise use, TwelveLabs enables businesses to gain a comprehensive understanding of their video content and make more informed decisions. The platform is highly scalable and customizable, capable of processing petabytes of video data and being deployed on the cloud, private cloud, or on-premise. With no missed moments or unreachable data, TwelveLabs ensures enterprises can fully leverage their video assets. Additionally, TwelveLabs’ flexible pricing structure allows businesses to start small and scale efficiently as needed.

Flowise is a versatile open-source platform that simplifies the creation of tailored Large Language Model (LLM) applications using an intuitive drag-and-drop interface designed for low-code development. This platform accommodates connections with multiple LLMs, such as LangChain and LlamaIndex, and boasts more than 100 integrations to support the building of AI agents and orchestration workflows. Additionally, Flowise offers a variety of APIs, SDKs, and embedded widgets that enable smooth integration into pre-existing systems, ensuring compatibility across different platforms, including deployment in isolated environments using local LLMs and vector databases. As a result, developers can efficiently create and manage sophisticated AI solutions with minimal technical barriers.

StreamNative transforms the landscape of streaming infrastructure by combining Kafka, MQ, and various other protocols into one cohesive platform, which offers unmatched flexibility and efficiency tailored for contemporary data processing requirements. This integrated solution caters to the varied demands of streaming and messaging within microservices architectures. By delivering a holistic and intelligent approach to both messaging and streaming, StreamNative equips organizations with the tools to effectively manage the challenges and scalability of today’s complex data environment. Furthermore, Apache Pulsar’s distinctive architecture separates the message serving component from the message storage segment, creating a robust cloud-native data-streaming platform. This architecture is designed to be both scalable and elastic, allowing for quick adjustments to fluctuating event traffic and evolving business needs, and it can scale up to accommodate millions of topics, ensuring that computation and storage remain decoupled for optimal performance. Ultimately, this innovative design positions StreamNative as a leader in addressing the multifaceted requirements of modern data streaming.

Instill harnesses advanced AI to cultivate a robust organizational culture, enhance team dynamics, and accelerate outstanding performance. Step into the future of productivity and growth by effectively assessing, developing, and progressing your organizational culture. Discover profound insights into the nuances of your company culture that were previously difficult to grasp. Employ predictive analytics to assemble high-performing teams that promote synergy and drive innovation. Leverage AI-driven strategies to remove uncertainty in your pursuit of an ideal cultural environment. Our expertise lies in forming high-impact teams capable of achieving remarkable results. Receive invaluable guidance on constructing world-class teams from experts in research, organizational psychology, and related fields. Infuse a greater level of scientific rigor and technological innovation into your human resource tools than ever before. Unleash the potential of scientifically validated instruments that evaluate your culture in a multidimensional framework. Instill integrates both active and passive approaches, facilitating high-level discussions regarding team culture and performance while fostering continuous improvement. This holistic methodology ensures that every layer of your organization is aligned with its cultural goals.

Langtrace is an open-source observability solution designed to gather and evaluate traces and metrics, aiming to enhance your LLM applications. It prioritizes security with its cloud platform being SOC 2 Type II certified, ensuring your data remains highly protected. The tool is compatible with a variety of popular LLMs, frameworks, and vector databases. Additionally, Langtrace offers the option for self-hosting and adheres to the OpenTelemetry standard, allowing traces to be utilized by any observability tool of your preference and thus avoiding vendor lock-in. Gain comprehensive visibility and insights into your complete ML pipeline, whether working with a RAG or a fine-tuned model, as it effectively captures traces and logs across frameworks, vector databases, and LLM requests. Create annotated golden datasets through traced LLM interactions, which can then be leveraged for ongoing testing and improvement of your AI applications. Langtrace comes equipped with heuristic, statistical, and model-based evaluations to facilitate this enhancement process, thereby ensuring that your systems evolve alongside the latest advancements in technology. With its robust features, Langtrace empowers developers to maintain high performance and reliability in their machine learning projects.

Fleak serves as a user-friendly, low-code serverless API builder tailored for data teams, eliminating the need for any underlying infrastructure while enabling the quick embedding of API endpoints into your modern AI and data technology ecosystem. Begin by setting up the necessary elements of your data workflow, which can include transforming data, creating text embeddings, and linking with vector databases, all achievable in just a few straightforward steps. The platform's intuitive features remove unnecessary complications, allowing you to efficiently create workflows without cumbersome configurations. You can easily add and adjust nodes to construct your workflow, accommodating various data formats such as JSON, SQL, CSV, and plain text. Furthermore, you have the flexibility to customize each step of your workflow to facilitate diverse data transformations. After designing your workflow, you can test and preview the results on the spot, ensuring everything is accurate before proceeding. Once the workflow is complete, Fleak enables seamless integration with large language models, databases, and a range of other critical tools, significantly enhancing your data management capabilities. This streamlined process not only saves time but also empowers teams to leverage their data more effectively.

TruLens is a versatile open-source Python library aimed at the systematic evaluation and monitoring of Large Language Model (LLM) applications. It features detailed instrumentation, feedback mechanisms, and an intuitive interface that allows developers to compare and refine various versions of their applications, thereby promoting swift enhancements in LLM-driven projects. The library includes programmatic tools that evaluate the quality of inputs, outputs, and intermediate results, enabling efficient and scalable assessments. With its precise, stack-agnostic instrumentation and thorough evaluations, TruLens assists in pinpointing failure modes while fostering systematic improvements in applications. Developers benefit from an accessible interface that aids in comparing different application versions, supporting informed decision-making and optimization strategies. TruLens caters to a wide range of applications, including but not limited to question-answering, summarization, retrieval-augmented generation, and agent-based systems, making it a valuable asset for diverse development needs. As developers leverage TruLens, they can expect to achieve more reliable and effective LLM applications.

Traceloop is an all-encompassing observability platform tailored for the monitoring, debugging, and quality assessment of outputs generated by Large Language Models (LLMs). It features real-time notifications for any unexpected variations in output quality and provides execution tracing for each request, allowing for gradual implementation of changes to models and prompts. Developers can effectively troubleshoot and re-execute production issues directly within their Integrated Development Environment (IDE), streamlining the debugging process. The platform is designed to integrate smoothly with the OpenLLMetry SDK and supports a variety of programming languages, including Python, JavaScript/TypeScript, Go, and Ruby. To evaluate LLM outputs comprehensively, Traceloop offers an extensive array of metrics that encompass semantic, syntactic, safety, and structural dimensions. These metrics include QA relevance, faithfulness, overall text quality, grammatical accuracy, redundancy detection, focus evaluation, text length, word count, and the identification of sensitive information such as Personally Identifiable Information (PII), secrets, and toxic content. Additionally, it provides capabilities for validation through regex, SQL, and JSON schema, as well as code validation, ensuring a robust framework for the assessment of model performance. With such a diverse toolkit, Traceloop enhances the reliability and effectiveness of LLM outputs significantly.

Terraform is a powerful open-source tool for managing infrastructure as code, offering a consistent command-line interface to interact with numerous cloud services. By translating cloud APIs into declarative configuration files, Terraform enables users to define their infrastructure requirements clearly. Infrastructure can be written using these configuration files, leveraging the HashiCorp Configuration Language (HCL), which provides a straightforward way to describe resources through blocks, arguments, and expressions. Before making any changes to your infrastructure, executing the command terraform plan allows you to verify that the proposed execution plan aligns with your expectations. To implement the desired configuration, you can use terraform apply, which facilitates the application of changes across a wide range of cloud providers. Furthermore, Terraform empowers users to manage the entire lifecycle of their infrastructure — from creating new resources to overseeing existing ones and eventually removing those that are no longer necessary, ensuring efficient management of cloud environments. This holistic approach to infrastructure management helps streamline operations and reduces the risk of errors during deployment.

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.

Gather all your unstructured data to meet your LLM requirements effectively. Datavolo transforms single-use, point-to-point coding into rapid, adaptable, reusable pipelines, allowing you to concentrate on what truly matters—producing exceptional results. As a dataflow infrastructure, Datavolo provides you with a significant competitive advantage. Enjoy swift, unrestricted access to all your data, including the unstructured files essential for LLMs, thereby enhancing your generative AI capabilities. Experience pipelines that expand alongside you, set up in minutes instead of days, without the need for custom coding. You can easily configure sources and destinations at any time, while trust in your data is ensured, as lineage is incorporated into each pipeline. Move beyond single-use pipelines and costly configurations. Leverage your unstructured data to drive AI innovation with Datavolo, which is supported by Apache NiFi and specifically designed for handling unstructured data. With a lifetime of experience, our founders are dedicated to helping organizations maximize their data's potential. This commitment not only empowers businesses but also fosters a culture of data-driven decision-making.

AI engineering can be transparent rather than opaque. With a suite of tools for tracing, assessment, prompt management, and more, HoneyHive emerges as a comprehensive platform for AI observability and evaluation, aimed at helping teams create dependable generative AI applications. This platform equips users with resources for model evaluation, testing, and monitoring, promoting effective collaboration among engineers, product managers, and domain specialists. By measuring quality across extensive test suites, teams can pinpoint enhancements and regressions throughout the development process. Furthermore, it allows for the tracking of usage, feedback, and quality on a large scale, which aids in swiftly identifying problems and fostering ongoing improvements. HoneyHive is designed to seamlessly integrate with various model providers and frameworks, offering the necessary flexibility and scalability to accommodate a wide range of organizational requirements. This makes it an ideal solution for teams focused on maintaining the quality and performance of their AI agents, delivering a holistic platform for evaluation, monitoring, and prompt management, ultimately enhancing the overall effectiveness of AI initiatives. As organizations increasingly rely on AI, tools like HoneyHive become essential for ensuring robust performance and reliability.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

Achieve limitless data retention for Apache Kafka® with Confluent, empowering you to be infrastructure-enabled rather than constrained by outdated systems. Traditional technologies often force a choice between real-time processing and scalability, but event streaming allows you to harness both advantages simultaneously, paving the way for innovation and success. Have you ever considered how your rideshare application effortlessly analyzes vast datasets from various sources to provide real-time estimated arrival times? Or how your credit card provider monitors millions of transactions worldwide, promptly alerting users to potential fraud? The key to these capabilities lies in event streaming. Transition to microservices and facilitate your hybrid approach with a reliable connection to the cloud. Eliminate silos to ensure compliance and enjoy continuous, real-time event delivery. The possibilities truly are limitless, and the potential for growth is unprecedented.

Infrastructure as Code has evolved to allow for the creation, deployment, and management of cloud infrastructure using well-known programming languages and tools. With a unified workflow across multiple cloud platforms, you can utilize the same language and tools no matter where your resources are hosted. Collaboration between developers and operators is streamlined, fostering a harmonious engineering environment. Continuous delivery becomes simple, as you can deploy from the command line or integrate with your preferred CI/CD systems, while also having the ability to review all changes prior to implementation. Navigating through complexity is made easier with enhanced visibility across all environments, allowing for more effective management. You can maintain security and audit trails by tracking who made changes, when alterations occurred, and the reasons behind them, all while enforcing deployment policies through your chosen identity provider. Secrets management is simplified with built-in encrypted configurations to keep sensitive information secure. Define your infrastructure in various familiar programming languages such as JavaScript, TypeScript, Python, Go, or any .NET language like C#, F#, and VB. Utilize your preferred development tools, IDEs, and testing frameworks to enhance productivity. Furthermore, you can codify and share best practices and policies, fostering a culture of reuse and efficiency within your team. This approach not only increases operational effectiveness but also empowers teams to innovate continuously.

Introducing revolutionary data streaming features that enable unparalleled customer experiences. The Kafka API and its ecosystem are fully compatible with Redpanda, which boasts predictable low latencies and ensures zero data loss. Redpanda is designed to outperform Kafka by up to ten times, offering enterprise-level support and timely hotfixes. It also includes automated backups to S3 or GCS, providing a complete escape from the routine operations associated with Kafka. Additionally, it supports both AWS and GCP environments, making it a versatile choice for various cloud platforms. Built from the ground up for ease of installation, Redpanda allows for rapid deployment of streaming services. Once you witness its incredible capabilities, you can confidently utilize its advanced features in a production setting. We take care of provisioning, monitoring, and upgrades without requiring access to your cloud credentials, ensuring that sensitive data remains within your environment. Your streaming infrastructure will be provisioned, operated, and maintained seamlessly, with customizable instance types available to suit your specific needs. As your requirements evolve, expanding your cluster is straightforward and efficient, allowing for sustainable growth.

The AI search engine provides accurate responses sourced from your text, documents, and videos. Experience seamless out-of-the-box AI-driven search and generative responses from your diverse materials while ensuring data privacy is maintained. Nuclia automatically organizes your unstructured data from various internal and external sources, delivering enhanced search outcomes and generative replies. It adeptly manages tasks such as transcribing video and audio, extracting content from images, and parsing documents. Users can search through your data using not just keywords but also natural language in nearly all languages to obtain precise answers. Effortlessly create AI search results and responses from any data source with ease. Implement our low-code web component to seamlessly incorporate Nuclia’s AI-enhanced search into any application, or take advantage of our open SDK to build your customized front-end solution. You can integrate Nuclia into your application in under a minute. Choose your preferred method for uploading data to Nuclia from any source, supporting any language and format, to maximize accessibility and efficiency. With Nuclia, you unlock the power of intelligent search tailored to your specific data needs.

Leverage cutting-edge NLP advancements by utilizing Haystack's pipeline architecture on your own datasets. You can create robust solutions for semantic search, question answering, summarization, and document ranking, catering to a diverse array of NLP needs. Assess various components and refine models for optimal performance. Interact with your data in natural language, receiving detailed answers from your documents through advanced QA models integrated within Haystack pipelines. Conduct semantic searches that prioritize meaning over mere keyword matching, enabling a more intuitive retrieval of information. Explore and evaluate the latest pre-trained transformer models, including OpenAI's GPT-3, BERT, RoBERTa, and DPR, among others. Develop semantic search and question-answering systems that are capable of scaling to accommodate millions of documents effortlessly. The framework provides essential components for the entire product development lifecycle, such as file conversion tools, indexing capabilities, model training resources, annotation tools, domain adaptation features, and a REST API for seamless integration. This comprehensive approach ensures that you can meet various user demands and enhance the overall efficiency of your NLP applications.

Approximately 80% of corporate data is stored in challenging formats such as HTML, PDF, CSV, PNG, and PPTX, among others. Unstructured simplifies the extraction and transformation of intricate data to be compatible with all leading vector databases and LLM frameworks. This platform enables data scientists to preprocess data efficiently at scale, allowing them to allocate more time to modeling and analysis rather than data collection and cleaning. With our enterprise-grade connectors, we can gather data from various sources and convert it into AI-friendly JSON files, making it easier for organizations to integrate AI into their operations. Rely on Unstructured to provide meticulously curated data that is clean of any artifacts and, crucially, ready for use with LLMs. In doing so, we empower businesses to harness the full potential of their data for innovative applications.

Estuary Flow, a new DataOps platform, empowers engineering teams with the ability to build data-intensive real-time applications at scale and with minimal friction. This platform allows teams to unify their databases, pub/sub and SaaS systems around their data without having to invest in new infrastructure or development.

Context Data is a data infrastructure for enterprises that accelerates the development of data pipelines to support Generative AI applications. The platform automates internal data processing and transform flows by using an easy to use connectivity framework. Developers and enterprises can connect to all their internal data sources and embed models and vector databases targets without the need for expensive infrastructure or engineers. The platform allows developers to schedule recurring flows of data for updated and refreshed data.

Voyage AI provides cutting-edge embedding and reranking models that enhance intelligent retrieval for businesses, advancing retrieval-augmented generation and dependable LLM applications. Our solutions are accessible on all major cloud services and data platforms, with options for SaaS and customer tenant deployment within virtual private clouds. Designed to improve how organizations access and leverage information, our offerings make retrieval quicker, more precise, and scalable. With a team comprised of academic authorities from institutions such as Stanford, MIT, and UC Berkeley, as well as industry veterans from Google, Meta, Uber, and other top firms, we create transformative AI solutions tailored to meet enterprise requirements. We are dedicated to breaking new ground in AI innovation and providing significant technologies that benefit businesses. For custom or on-premise implementations and model licensing, feel free to reach out to us. Getting started is a breeze with our consumption-based pricing model, allowing clients to pay as they go. Our commitment to client satisfaction ensures that businesses can adapt our solutions to their unique needs effectively.

Oversee and protect the entire data lifecycle from the Edge to AI across any cloud platform or data center. Functions seamlessly within all leading public cloud services as well as private clouds, providing a uniform public cloud experience universally. Unifies data management and analytical processes throughout the data lifecycle, enabling access to data from any location. Ensures the implementation of security measures, regulatory compliance, migration strategies, and metadata management in every environment. With a focus on open source, adaptable integrations, and compatibility with various data storage and computing systems, it enhances the accessibility of self-service analytics. This enables users to engage in integrated, multifunctional analytics on well-managed and protected business data, while ensuring a consistent experience across on-premises, hybrid, and multi-cloud settings. Benefit from standardized data security, governance, lineage tracking, and control, all while delivering the robust and user-friendly cloud analytics solutions that business users need, effectively reducing the reliance on unauthorized IT solutions. Additionally, these capabilities foster a collaborative environment where data-driven decision-making is streamlined and more efficient.

Llama (Large Language Model Meta AI) stands as a cutting-edge foundational large language model aimed at helping researchers push the boundaries of their work within this area of artificial intelligence. By providing smaller yet highly effective models like Llama, the research community can benefit even if they lack extensive infrastructure, thus promoting greater accessibility in this dynamic and rapidly evolving domain. Creating smaller foundational models such as Llama is advantageous in the landscape of large language models, as it demands significantly reduced computational power and resources, facilitating the testing of innovative methods, confirming existing research, and investigating new applications. These foundational models leverage extensive unlabeled datasets, making them exceptionally suitable for fine-tuning across a range of tasks. We are offering Llama in multiple sizes (7B, 13B, 33B, and 65B parameters), accompanied by a detailed Llama model card that outlines our development process while adhering to our commitment to Responsible AI principles. By making these resources available, we aim to empower a broader segment of the research community to engage with and contribute to advancements in AI.