AI Infrastructure
LLM Gateway — Governed AI
One entry point for all your AI requests: multi-providers, quotas, audit logs, and filters. Goal: scale AI adoption without API key sprawl, with clear controls and predictable costs.
Useful links: deployment options · Argy Code · Argy Chat · Pricing
LLM Gateway value
Security, control, and adoption speed: AI becomes a governed service.
Security & compliance
Filtering (PII/secrets), audit logs, and RGPD controls configurable from the admin portal.
Cost & quotas
Quotas, alerts, and limits: avoid runaway usage and manage consumption per team/product.
Multi-provider routing
Pick the right model for latency, quality, or budget — without changing client code.
RAG on your documents
RAG (Retrieval-Augmented Generation) augments prompts with passages retrieved from your documents to deliver grounded, context-aware responses. indexes your content (PDF, Markdown, HTML), chunks passages, generates embeddings, and returns top‑K context to ground your prompts.
How you use it
- Connect your AI providers (OpenAI, Anthropic, Azure OpenAI, etc.).
- Set quotas, filters, and routing rules (budget/quality).
- Your tools call a single API, compatible with OpenAI-style clients.
European SaaS
GDPR compliant & hosted in EU
No Lock-in
Built on open standards
API-First
Everything is automatable
Ready to turn AI into an enterprise operating system?
Share your context (toolchain, constraints, org). We’ll propose a pragmatic rollout that makes AI governed, scalable, and sovereign.