RelaySwitch vs. plaingateway Comparison Chart

Hivenet Compute gives you on-demand RTX 5090 and RTX Pro 6000 GPUs, plus vCPU instances, billed per second while they run. Hivenet owns and operates the infrastructure, with data centres in France, the UAE and the US, so EU teams can keep workloads and data in Europe. Use it for training and fine-tuning, inference, notebooks, rendering and batch jobs. Launch from ready-made templates in a few minutes, or automate everything through the public Compute API. If you'd rather not run the serving layer yourself, the Inference API gives you an OpenAI-compatible endpoint. Teams get organisations with role-based access, prepaid credits, and S3-compatible object storage alongside hivenet compute.

FinOpsly is an AI Cost Governance platform. It brings AI, cloud, data platform and SaaS spend into one attribution, policy and control layer, so enterprises can price a workload before building it, attribute every dollar to an owner, hold spend inside budget under policy, and prove what landed in run-rate. Your AI invoice is not what your AI costs. One request draws on model tokens, retrieval, warehouse queries, GPU capacity and storage, and only the first shows up on the AI bill. FinOpsly resolves all of it, plus the seats in procurement and the compute in an untagged cloud account, to the same dimensions: owner, team, application, line of business, customer and tenant. An AI initiative's full cost becomes one figure, charged back through one hierarchy in one cycle. Workforce AI is the tools employees use: seats and per-user token draw across GitHub Copilot, Cursor, ChatGPT Enterprise and Microsoft 365 Copilot. Application AI is the AI your product ships: tokens, compute and data joined into cost-to-serve across OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex AI, SageMaker and Databricks. PLAN. Price a workload from its architecture before any resource exists, across model APIs, GPU capacity, data platform consumption and storage, with assumptions visible. Compare it across candidate models on your measured usage. EXPLAIN. Attribute spend to owner, team, application, line of business and business unit across 9+ hierarchy levels. Unified tagging reconciles providers that tag inconsistently, and AI-driven bulk labeling closes large key estates. Unattributed spend is reported in dollars. ACT. Budgets per project, team and API key, with daily burn-rate monitoring. Anomaly detection with root cause, routed to the owner. Waste detection using FinOpsly's own algorithms and ML models. Commitment planning across AWS, Azure and Google Cloud. Policy-driven parking of idle compute. PROVE. Chargeback across AI, cloud, data and SaaS in one cycle. Realized savings tracked into run-rate against a no-action baseline. Cost per call, cost per active user, and cost-to-serve per customer and tenant. proof: 100% attribution of AI spend; chargeback from 12.4 days to under one day across 9+ levels; 26% realized savings in AWS and 17%+ in Azure at a payments client. Built for CIOs, CTOs and platform leaders accountable for technology spend, FinOps and finance teams running chargeback, and engineering teams who need cost signal before they decide

Since 2012, AuctionMethod has provided white-label auction software and custom auction software development for the auction industry. Based in Massachusetts, serving the U.S., Canada, Australia, and New Zealand. AuctionMethod serves auctioneers, estate liquidators, farm and heavy equipment, industrial, salvage and recycling, non-profit, corporations, retail liquidators, auto/car dealers, real estate, arts and collectibles, and single-use auction businesses. AuctionMethod is the winner of the SourceForge Spring 2026 Top Performer Award in Auction Software, and is rated 4.9/5 on Capterra and SourceForge. AuctionMethod's model includes no commissions, no per-lot fees, no platform skim, and no contract, so clients keep the revenue from every sale instead of splitting it with the platform. Clients also keep 100% ownership of their bidder lists, seller lists, item data, images, and transaction history on a fully white-label auction website rather than a shared marketplace listing. The platform covers catalog and lot management, consignor setup, bidder registration, invoicing, payment processing, tax handling, and reporting in one system. Auction event types include timed online auctions, simulcast auctions, blind timed auctions, catalog-only, fixed-price, and perpetual events. AuctionMethod includes a mobile app for iOS and Android and integrates with Fiserv, Stripe, Authorize.net, and more. Hosted on AWS with separate client databases, AuctionMethod specializes in real-time speed for live, rapid-fire simulcast auctions, where latency is critical and must stay under one second so online bidders do not miss the auctioneer's hammer, and the platform is fully hosted with daily backups, auto-scaling for high traffic, and security updates included, with 100% uptime tracked on a public status page. For operations whose workflows fall outside the standard product, AuctionMethod also builds custom auction software development solutions, a dedicated codebase built around a client's specific processes, quoted at a fixed rate. AuctionMethod's pricing starts at $100/mo with a $250 one-time setup charge, and is published publicly. AuctionMethod offers a 30-day free trial, no credit card required.

RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.

Macaw AMS is for selling Insurance. Brokers, MGAs, MGUs, Program Managers and Lloyds Coverholders can use Macaw AMS to automate their operating model. Macaw AMS is built with a customer-centric model. It supports CRM, Sales, Underwriting, Rating, Policy Servicing, Claims Intimation and Billing. Self-service portals are available for Customers, Producers and Carriers. The reporting, analytics and visualization capabilities are best-in-class. Macaw AMS comes with in-built Document Management and Task Management facilities. It has several ready adaptors to provide integrated & in-flow facilities for eSignature, Payment, OFAC check, Mass Emailing and Computer Telephony, using 3rd Party Services. Macaw AMS is hosted in cloud and tested for cyber security. Technology-wise, the screens are responsive and can be used from web / mobile / tablet. The database is relational and the core components are written in Java. At the peak, Macaw AMS can process 500-1000 Policies within one day.

Gemini platform is an enterprise AI development and machine learning platform from Google Cloud that enables organizations to build, customize, deploy, and manage AI agents and intelligent applications. Formerly known as Vertex AI, the platform provides access to more than 200 foundation models from Google, third-party providers, and open-source communities. Its Agent Studio and Agent Development Kit allow developers to create autonomous agents, design multistep workflows, and integrate artificial intelligence with enterprise data and external tools. The platform also supports custom model training, fine-tuning, machine learning pipelines, model evaluation, and scalable inference infrastructure. Enterprise capabilities include agent identity management, centralized governance, security policies, persistent memory, and monitoring tools for evaluating agent performance. Gemini platform integrates with BigQuery, Google Antigravity, Google Cloud infrastructure, and developer frameworks to support generative AI applications, predictive analytics, and automated business workflows.

Careerminds is a global workforce solutions provider specializing in outplacement, career and talent development, and job architecture. We combine modern technology with high-touch, one-to-one coaching to help organizations support employees through workforce change and growth. Our scalable delivery model enables consistent, personalized experiences, offering a flexible, cost-effective alternative to traditional firms. - Outplacement and redeployment: We’re the modern partner for HR leaders who demand results. Faster transitions, measurable impact, and cost efficiency, all powered by data and a smarter coaching model. - Talent solutions: Executive coaching, career development and leadership development programs that grow talent, improve retention and build future-ready workforces through modern career enablement technology. - Job architecture and career frameworks: Redesign your workforce by giving employees a clear pathway to develop in roles that benefit both them and you.

Passwork is a password manager built for security-conscious organizations, available as both a self-hosted (on-premise) solution and a secure cloud service. Developed and headquartered in Europe (Barcelona, Spain), Passwork meets GDPR, NIS2, ENS and other European regulatory requirements by design. The self-hosted version stores all passwords and credentials exclusively on your own server. Double-layer AES-256 encryption (server-side and client-side) with zero-knowledge architecture ensures your data stays within your infrastructure. For organizations seeking instant deployment without infrastructure overhead, Passwork Cloud provides a fully managed SaaS option. Hosted in secure data centers in Germany, the cloud platform operates on the same zero-knowledge model. Passwork is ISO/IEC 27001 certified. Both deployment options are trusted by enterprises for secure password sharing, privileged access management, and centralized credential governance.

AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack. At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design. Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns. Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets. AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes. Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules. Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering.

Admin By Request EPM gives organizations control over who and what can elevate on their endpoints, without standing up servers, databases, or a dedicated admin team to run it. The model is least privilege: a user or an application receives the specific access its task requires and nothing more. This closes off a common attack route, since permanent local admin rights are what an attacker inherits when malware executes or a credential is stolen. Removing admin rights does not push users back into support queues. When someone needs a longer stretch of elevated work, they run an Admin Session that expires on its own. When they need only one program elevated, Run As Admin handles that alone and leaves the rest of the system unprivileged. Requests can be approved through the portal, the mobile app, or the API. Files receive an OPSWAT MetaDefender reputation check before elevation, and software that has already been vetted can clear automatically through pre-approval or the AI and Machine Learning approval engine. A single agent supports Windows, macOS, and Linux and behaves the same whether the endpoint is online or offline. Auditing and inventory are included as standard.