Agumbe LLM Gateway (and Console)
Guardrails and Provenance for enterprise AI control
Agumbe LLM Gateway (and Console) launched on March 24, 2026 with 3 votes, #3,303 of 23,380 launches that month and more than 50% of that year's launches.
What it does
Most LLM guardrails don’t make it to production. Agumbe LLM Gateway lets you define guardrails at the app level and enforces them in your real request path. Detect, redact, or block → Prompt injection (direct + indirect) → PII and secrets detection → Denied topics → Output safety and groundedness → and more.. All while ensuring → Budget enforcement → Cheap models for dev, premium reserved for prod and more Test everything through a console that uses the same headless gateway as production.
Control model traffic with AI Gateway and control agent context with XContext.
Two focused products give platform and engineering teams control over the full AI request path: AI Gateway governs model traffic, while XContext reduces, protects, and retrieves the context sent by agents. Route across providers, apply guardrails, manage keys and budgets, and trace production LLM traffic. Capture agent output, redact secrets, store durable context references, and retrieve only what a taskfrom console.agumbe.ai
Does a similar job
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Forge – Guardrails take an 8B model from 53% to 99% on agentic tasksMay 2026 · github.com · ▲687Hi HN, I'm Antoine Zambelli, AI Director at Texas Instruments. I built Forge, an open-source reliability layer for self-hosted LLM tool-calling. What it does: - Adds domain-and-tool-agnostic guardrails (retry nudges, step enforcement, error recovery, VRAM-aware context management) to local models running on consumer hardware - Takes an 8B model from ~53% to ~99% on multi-step agentic workflows without changing the model - just the system around it - Ships with an eval harness and interactive dashboard so you can reproduce every number I wanted to run a handful of always-on agentic systems…
TrueFoundry AI GatewayDec 2025 · truefoundry.com · ▲315Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…
ElevenAgents Guardrails 2.0Apr 2026 · elevenlabs.io · ▲132Configurable safety control for enterprise agent deployment.

An open-source AI Gateway with integrated guardrails2024 · github.com · ▲21Hi HN, I've been developing Portkey Gateway, an open-source AI gateway that's now processing billions of tokens daily across 200+ LLMs. Today, we're launching a significant update: integrated Guardrails at the gateway level. Key technical features: 1. Guardrails as middleware: We've implemented a hooks architecture that allows guardrails to act as middleware in the request/response flow. This enables real-time LLM output evaluation and transformation. 2. Flexible orchestration: The gateway can now route requests based on guardrail verdicts. This allows for complex logic like fallbacks…

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