Compare Pinecone vs. Superlinked

RunPod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, RunPod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, RunPod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.

LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents. Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development. Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

Google AI Studio is a user-friendly, web-based workspace that offers a streamlined environment for exploring and applying cutting-edge AI technology. It acts as a powerful launchpad for diving into the latest developments in AI, making complex processes more accessible to developers of all levels. The platform provides seamless access to Google's advanced Gemini AI models, creating an ideal space for collaboration and experimentation in building next-gen applications. With tools designed for efficient prompt crafting and model interaction, developers can quickly iterate and incorporate complex AI capabilities into their projects. The flexibility of the platform allows developers to explore a wide range of use cases and AI solutions without being constrained by technical limitations. Google AI Studio goes beyond basic testing by enabling a deeper understanding of model behavior, allowing users to fine-tune and enhance AI performance. This comprehensive platform unlocks the full potential of AI, facilitating innovation and improving efficiency in various fields by lowering the barriers to AI development. By removing complexities, it helps users focus on building impactful solutions faster.

AI agents that interact and answer questions with users and complete tasks using your data and APIs. AI that can answer questions, summarize and extract insights from any long document. Transfer styles and formats, as well as tags and summaries between documents and data sources. Stack AI is used by developer teams to automate customer service, process documents, qualify leads, and search libraries of data. With a single button, you can try multiple LLM architectures and prompts. Collect data, run fine-tuning tasks and build the optimal LLM to fit your product. We host your workflows in APIs, so that your users have access to AI instantly. Compare the fine-tuning services of different LLM providers.

Our decentralized platform streamlines AI data collection and labeling through a worldwide contributor network. By combining crowdsourcing with blockchain technology, we deliver high-quality, traceable datasets. Platform Highlights: Worldwide Collection: Tap into global contributors for comprehensive data gathering Blockchain Security: Every contribution tracked and verified on-chain Quality Focus: Expert validation ensures exceptional data standards Platform Benefits: Rapid scaling of data collection Complete data providence tracking Validated datasets ready for AI use Cost-efficient global operations Flexible contributor network How It Works: Define Your Needs: Create your data collection task Community Activation: Global contributors notified and start gathering data Quality Control: Human verification layer validates all contributions Sample Review: Get dataset sample for approval Full Delivery: Complete dataset delivered once approved

Ant Media provides ready-to-use, highly scalable real-time video streaming solutions for live video streaming needs. Based on customer requirements and preferences, it enables a live video streaming solution to be deployed easily and quickly on-premises or on public cloud networks such as AWS, Azure, GCP and Oracle Cloud. Ant Media’s well-known product, called Ant Media Server, is a video streaming platform and technology enabler, providing highly scalable, Ultra-Low Latency (WebRTC) and Low Latency (CMAF & HLS) video streaming solutions supported with operational management utilities. Ant Media Server in a cluster mode dynamically scales up and down to enable our customers to serve from tens to millions of viewers in an automated and controlled way. Ant Media Server provides compatibility to be played in any Web Browser. In addition, SDKs for iOS, Android, and JS are provided freely to enable customers to expand their reach to a broader audience. Thanks to the adaptive bitrate streaming feature that allows any video to be played at any bandwidth on mobile devices. Ant Media has been serving a growing number of customers in 120+ countries all around the world.

Criminal IP is a cyber threat intelligence search engine that detects vulnerabilities in personal and corporate cyber assets in real time and allows users to take preemptive actions. Coming from the idea that individuals and businesses would be able to boost their cyber security by obtaining information about accessing IP addresses in advance, Criminal IP's extensive data of over 4.2 billion IP addresses and counting to provide threat-relevant information about malicious IP addresses, malicious links, phishing websites, certificates, industrial control systems, IoTs, servers, CCTVs, etc. Using Criminal IP’s four key features (Asset Search, Domain Search, Exploit Search, and Image Search), you can search for IP risk scores and vulnerabilities related to searched IP addresses and domains, vulnerabilities for each service, and assets that are open to cyber attacks in image forms, in respective order.

DWR eDiscovery allows legal professionals to review, process, and produce documents that could be relevant to litigation. Our Software and hosted Subscriptions offers a wide range of document review tools, including AI search, keyword search, keyword highlight, metadata filtering and marking documents. It also has privilege log, redactions and analysis tools to help users better understand their document corpus. These features can all be done by the user themselves, so they can do the standard eDiscovery tasks without consulting. DWR eDiscovery offers subscriptions to both hosted and on-prem eDiscovery. DWR Pro desktop software can be downloaded to your computer or server. DWR Pro costs $1995per concurrent use license/year. Cloud subscriptions are charged per-GB for hosting and there are no hidden fees. The entry-level Single Matter subscription costs $10/GB/Month and has a minimum of $250 per month. Private clouds allow multiple matters and multiple users for no more than $4/GB/month moving quickly to $1/GB/month.

RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times. RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.