Principal Solutions Engineer

Solo.io extends agentic governance to any environment with Solo Enterprise for agentgateway. September 10, 2026 Enterprise identity, policy, and observability for agentic traffic, now available anywhere. CAMBRIDGE, Mass., September 10, 2026 - Solo.io, the leading provider of cloud native connectivity and AI-ready infrastructure, today announced a standalone mode for Solo Enterprise for agentgateway. Standalone mode ships the enterprise gateway as a single self-contained binary or container that runs in any environment, from a virtual machine or ECS task to bare metal or a developer workstation, extending the governance capabilities Solo.io has implemented for agentic infrastructure to every environment where agents run. Standalone also adds a complete self-service UI for configuration and management, allowing teams to configure model providers, register MCP servers, set policy, and inspect traffic across all supported environments. Enterprise AI does not run only in corporate applications. It runs in the production services a platform team ships, in the agents an MLOps team stands up on a virtual machine, and in the agent harnesses employees install on their laptops to get their own work done. A marketer using a desktop agent to draft campaign copy calls the same model providers and the same MCP servers as a production service. Every one of these calls needs the same things: identity on the request path, policy in front of model providers, governance over which MCP tools an agent can reach, and observability across all of it. Solo Enterprise for agentgateway allows organizations to govern this traffic wherever agents, tools, models, and harnesses run, while centralizing operations through a Kubernetes-native control plane and data plane. Standalone mode brings these same capabilities in a self-contained form factor outside of Kubernetes. Teams download the binary or pull the container image, point it at their model providers and MCP servers, and connect it to the identity providers and observability backends they already operate. The same artifact runs on a well-provisioned host fronting an entire business, on a controller at a remote site with no platform team nearby, or on a developer's laptop. Solo Enterprise for agentgateway gives teams five capabilities from a single deployment: * Identity: full STS-backed token exchange, OAuth authorization flows, eager authorization, and interactive login driven from the management UI. Every call carries a verifiable identity, whether it is headed for a model or a tool, rather than a shared static key. * Management: a full read-write UI to configure model providers, register MCP servers, define policy, and inspect traffic. Teams that operate from a console rather than a repository get the same control without editing configuration files. * Governance: administrators set which model providers a caller can reach, whether that model is hosted internally or served by a frontier provider, and apply guardrails to those calls. MCP servers are handled as first-class backends, with search mode and code mode for tool discovery and invocation, so agents stay effective against large tool catalogs while administrators keep control of what is reachable. * Cost: token budgeting, spend attribution, and cost control applied at the gateway. Every request is attributed to the model that served it and the identity that made it, so spend is visible where it happens rather than reconstructed from provider invoices later. * Observability: traces across model calls and tool calls, exported to the backends an organization already runs. Solo Enterprise for agentgateway builds on the open source agentgateway, an Agentic AI Foundation project written in Rust and purpose-built for agentic protocols with over 50 million image downloads and 500 contributors from a diverse range of organizations including Microsoft, Coinbase, Amazon, Adobe, and Okta. The Solo.io agentic stack provides everything teams need to develop, deploy, and operate AI agents across agentic runtime environments. Powered by core open source projects created and contributed to the community by Solo.io, including: * agentgateway, an Agentic AI Foundation project, is the high-performance data plane for agentic traffic, built from the ground up in Rust to span the full range of agentic protocols and use cases as a unified inference gateway, LLM gateway, MCP gateway, and A2A gateway. * kagent, a CNCF Sandbox project, is the Kubernetes-native runtime that makes agents first-class workloads, with the security, observability, and lifecycle controls enterprises need to run programmatic, declarative, and always-on assistant patterns side-by-side. * agentregistry, contributed to CNCF, is the trusted source for discovering, packaging, and distributing agents and tools across an organization with centralized observability, security, and governance across agent runtimes. * agentdesktop is the open source governance layer for AI agents on the desktop, bringing inventory, managed configuration, non-human identity, and observability to the workstations where most enterprise agent activity actually happens. * agentevals captures evaluation and quality signals using OpenTelemetry rather than in-process instrumentation, providing continuous, framework-agnostic visibility into how agents actually behave in production across the entire agentic loop. 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Solo.io Extends Agentic Governance to Any Environment with Solo Enterprise for agentgateway TMCnet News [September 10, 2026] | / | Solo.io Extends Agentic Governance to Any Environment with Solo Enterprise for agentgateway CAMBRIDGE, Mass., Sept. 10, 2026 (GLOBE NEWSWIRE) - Solo.io, the leading provider of cloud native connectivity and AI-ready infrastructure, today announced a standalone mode for Solo Enterprise for agentgateway. Standalone mode ships the enterprise gateway as a single self-contained binary or container that runs in any environment, from a virtual machine or ECS task to bare metal or a developer workstation, extending the governance capabilities Solo.io has implemented for agentic infrastructure to every environment where agents run. Standalone also adds a complete self-service UI for configuration and management, allowing teams to configure model providers, register MCP servers, set policy, and inspect traffic across all supported environments. Enterprise AI does not run only in corporate applications. It runs in the production services a platform team ships, in the agents an MLOps team stands up on a virtual machine, and in the agent harnesses employees install on their laptops to get their own work done. A marketer using a desktop agent to draft campaign copy calls the same model providers and the same MCP servers as a production service. Every one of these calls needs the same things: identity on the request path, policy in front of model providers, governance over which MCP tools an agent can reach, and observability across all of it. Solo Enterprise for agentgateway allows organizations to govern this traffic wherever agents, tools, models, and harnesses run, while centralizing operations through a Kubernetes-native control plane and data plane. Standalone mode brings these same capabilities in a self-contained form factor outside of Kubernetes. Teams download the binary or pull the container image, point it at their model providers and MCP servers, and connect it to the identity providers and observability backends they already operate. The same artifact runs on a well-provisioned host fronting an entire business, on a controller at a remote site with no platform team nearby, or on a developer's laptop. Solo Enterprise for agentgateway gives teams five capabilities from a single deployment: * Identity: full STS-backed token exchange, OAuth authorization flows, eager authorization, and interactive login driven from the management UI. Every call carries a verifiable identity, whether it is headed for a model or a tool, rather than a shared static key. * Management: a full read-write UI to configure model providers, register MCP servers, define policy, and inspect traffic. Teams that operate from a console rather than a repository get the same control without editing configuration files. * Governance: administrators set which model providers a caller can reach, whether that model is hosted internally or served by a frontier provider, and apply guardrails to those calls. MCP servers are handled as first-class backends, with search mode and code mode for tool discovery and invocation, so agents stay effective against large tool catalogs while administrators keep control of what is reachable. * Cost: token budgeting, spend attribution, and cost control applied at the gateway. Every request is attributed to the model that served it and the identity that made it, so spend is visible where it happens rather than reconstructed from provider invoices later. * Observability: traces across model calls and tool calls, exported to the backends an organization already runs. Solo Enterprise for agentgateway builds on the open source agentgateway, an Agentic AI Foundation project written in Rust and purpose-built for agentic protocols with over 50 million image downloads and 500 contributors from a diverse range of organizations including Microsoft, Coinbase, Amazon, Adobe, and Okta. The Solo.io agentic stack provides everything teams need to develop, deploy, and operate AI agents across agentic runtime environments. Powered by core open source projects created and contributed to the community by Solo.io, including: * agentgateway, an Agentic AI Foundation project, is the high-performance data plane for agentic traffic, built from the ground up in Rust to span the full range of agentic protocols and use cases as a unified inference gateway, LLM gateway, MCP gateway, and A2A gateway. * kagent, a CNCF Sandbox project, is the Kubernetes-native runtime that makes agents first-class workloads, with the security, observability, and lifecycle controls enterprises need to run programmatic, declarative, and always-on assistant patterns side-by-side. * agentregistry, contributed to CNCF, is the trusted source for discovering, packaging, and distributing agents and tools across an organization with centralized observability, security, and governance across agent runtimes. * agentdesktop is the open source governance layer for AI agents on the desktop, bringing inventory, managed configuration, non-human identity, and observability to the workstations where most enterprise agent activity actually happens. * agentevals captures evaluation and quality signals using OpenTelemetry rather than in-process instrumentation, providing continuous, framework-agnostic visibility into how agents actually behave in production across the entire agentic loop. To get started, please visit the Solo Enterprise for agentgateway documentation. Media Contact Solo.io Press Team [email protected] [ Back To TMCnet.com's Homepage] |

Solo.io Extends Agentic Governance to the Desktop with agentdesktop. An open-source visibility, policy, and management layer for AI tools across a desktop fleet. September 03, 2026 09:00 ET | Source: Solo.io CAMBRIDGE, Mass., Sept. 03, 2026 (GLOBE NEWSWIRE) - Solo.io, the leading provider of cloud native connectivity and AI-ready infrastructure, today announced agentdesktop, a new open source project that brings the governance capabilities Solo.io has implemented for agentic infrastructure all the way out to the end user machines where Claude Code, Codex, and other general-purpose agents run. Agentic AI has introduced a completely new dimension to desktop exploits, increasing both the coverage area and blast radius of incidents. Yet most organizations feel that their existing governance controls via MDM and firewall solutions cover the complete threat surface. A recent study showed 90 percent of executives were confident they know what AI is running in their organization. The reality of the situation is quite different: 52 percent of employees admitted to using AI tools their company never approved (Okta) and 86 percent of enterprises do not enforce access policies for AI identities (Cloud Security Alliance). The fundamental tradeoff with agentic AI is that the more autonomy and power we give agents, the less predictable and controllable they become. This is exactly why so many agentic projects are able to demonstrate compelling value in the proof-of-concept and pilot phase, but fail to make it to production due to a lack of visibility, accountability, and control. Solo.io calls this the production gap: the distance between the governance organizations have in their infrastructure today and what they need to deploy agentic AI to production. This production gap now extends to the desktop, with agent harnesses connecting to production data, APIs, and systems. Every organization's governance strategy must now extend to this new frontier. Agentdesktop gives platform and security teams four capabilities from a single deployment: * Discovery: build a real-time inventory of every harness, model, MCP server, and skill across the fleet, attributed to a device and the associated user. Know exactly what's running and where. * Policy: declare configuration centrally and agentdesktop applies it to every harness, previews every change, and continuously reconciles drift. Ensuring consistent and uniform security posture across every installation. * Identity: treat agents as non-human identities with least-privilege access. Devices register, bind to their user through OIDC, and receive short-lived, just-in-time credentials identifying the specific combination of device, user, and agent. Eliminate the blast radius and unpredictable attack vectors of long-lived secrets stored locally. * Observability: opt-in session and tool-use telemetry, attributed to user and device, from only the events administrators select. Real-time awareness of agent activity. Users can start on a single desktop in standalone mode to provide local governance across installed agent harnesses, then move to fleet mode, where MDM installs the endpoint daemon and a central controller integrates with the organization's existing identity provider, PKI, and LLM gateway. Because agentdesktop is open source under the Apache 2.0 license, organizations can see exactly what the endpoint daemon collects, audit its identity and credential boundaries, and extend integrations as AI tools evolve. They keep their existing identity provider, PKI, and gateway rather than adopting a vertically bundled platform. The Solo.io agentic stack provides everything teams need to develop, deploy, and operate AI agents across agentic runtime environments. Powered by core open source projects created and contributed to the community by Solo.io, including: * agentdesktop is the open source governance layer for AI agents on the desktop, bringing inventory, managed configuration, non-human identity, and observability to the workstations where most enterprise agent activity actually happens. * kagent, a CNCF Sandbox project, is the Kubernetes-native runtime that makes agents first-class workloads, with the security, observability, and lifecycle controls enterprises need to run programmatic, declarative, and always-on assistant patterns side-by-side. * agentgateway, an Agentic AI Foundation project, is the high-performance data plane for agentic traffic, built from the ground up in Rust to span the full range of agentic protocols and use cases as a unified inference gateway, LLM gateway, MCP gateway, and A2A gateway. * agentregistry, contributed to CNCF, is the trusted source for discovering, packaging, and distributing agents and tools across an organization with centralized observability, security, and governance across agent runtimes. * agentevals captures evaluation and quality signals using OpenTelemetry rather than in-process instrumentation, providing continuous, framework-agnostic visibility into how agents actually behave in production across the entire agentic loop. * The project announcement blog for a deeper dive into the project's capabilities. * The agentdesktop project site. * Read the documentation. * Get involved by contributing via GitHub. * Join the #agentdesktop discussion in Discord. About Solo.io Solo.io is reimagining infrastructure for cloud and AI, uniting secure, seamless cloud connectivity with AI-ready, agentic infrastructure. Trusted by leading enterprises worldwide, Solo.io helps organizations securely connect applications, services, and AI workloads across any environment. From AI infrastructure to API gateways and service mesh, our solutions simplify and unify application networking, enabling teams to accelerate innovation, scale intelligently, and leverage the full potential of modern AI agents. Learn more at www.solo.io. Media Contact Solo.io Press Team [email protected]