Search Results for "ai"

...ObjectQL defines data, logic, and UI in a standard format that AI tools can generate and modify. ObjectOS provides the runtime layer for APIs, authentication, permissions, workflow automation, and business logic. Object UI turns metadata into responsive React and Tailwind interfaces, while still allowing custom components and pro-code extension. Steedos is built for teams that need enterprise-grade apps with low-code speed, AI assistance, and flexible backend architecture.

1Backend is an AI-native full-stack platform for building distributed applications with microservices and microfrontends. It works as a framework, proxy, and runtime that reduces early infrastructure overhead for developers. The platform includes built-in capabilities for authentication, user accounts, service routing, microfrontend routing, email, and API access.

beta9 is a platform that enables running serverless GPU workloads with fast cold starts on bare-metal servers globally. It allows developers to deploy and scale GPU-accelerated applications without managing underlying infrastructure, offering flexibility and efficiency for AI and high-performance computing tasks. beta9 supports various frameworks and provides tools for monitoring and managing deployments effectively.

Octelium is an open source, self-hosted unified secure-access platform built for modern infrastructure and hybrid environments. It positions itself as more than a typical VPN; it supports zero-trust network access (ZTNA), “BeyondCorp”-style access, API/AI gateway functionality, and even serves as a PaaS-like deployment surface. One of its key strengths is identity-based, application-layer (L7) aware control, meaning access decisions are made per request, with context and policy rather than simple network-level allow/block rules. It supports both client-based (e.g., WireGuard/QUIC tunnels) and client-less access models, which makes it flexible for both human users and automated workloads. ...

...Rainbond is built for complex enterprise delivery scenarios such as private deployment, offline delivery, internal-network environments, Xinchuang adaptation, ARM migration, and AI application privatization. It includes marketplace and template capabilities so teams can reuse applications and replicate deployments across customer environments. Its goal is to let development and delivery teams work at the application level while platform teams handle the underlying Kubernetes complexity.

...Banks and fintechs, AI-driven companies, service providers and data centers, governances, regulated and privacy-conscious organizations, integrators and independent IT consultants