LLM gateway serving millions of users
One API in front of multiple LLM providers, both commercial and self-hosted. Automatic cross-provider failover, per-feature rate limits, per-user cost metering.
Who we are, which organisations we have worked for, and what we have built.
Ingenious Networks GmbH combines long-standing UC experience with engineers who run AI platforms and voice agents at scale.
| Competence | What we bring |
|---|---|
| AI engineering | Agents, RAG, MCP, LangGraph, Pydantic AI, OpenAI Agents SDK, evaluation (LLM-as-a-judge) |
| LLM platform & ops | LLM gateways, self-hosting (vLLM), observability (Langfuse, OpenTelemetry), cost control |
| Voice AI | Real-time voice agents (LiveKit, WebRTC), STT/TTS streaming, speech-to-speech |
| Unified Communications | Cisco UCM, Webex, Webex DI, Expressway, CUBE, contact centre, Microsoft Teams |
| Software & cloud | Python, TypeScript, FastAPI, Node.js, React, PostgreSQL, Kafka, Kubernetes, GCP, AWS, Azure |
| Certifications | Vimal Bergmiller: Cisco CCIE Collaboration #38515, CCNP Voice, CCNA, Microsoft MCITP |
| Languages | German, English, Spanish |
Ingenious Networks has delivered projects for companies including:
Connecting two complex systems – where others had failed, Mr Bergmiller of Ingenious Networks, as a CCIE, did it in under three days. As a follow-up order, we engaged him for three years of support. Highly recommended.
One API in front of multiple LLM providers, both commercial and self-hosted. Automatic cross-provider failover, per-feature rate limits, per-user cost metering.
Streaming speech → LLM → speech pipeline with turn detection, interruptions and tool calling, including a speech-to-speech mode.
Self-hosted models behind a central gateway for 7 teams across 5 companies, with SSO, tracing and per-team cost attribution.
Automated evaluation with a fixed release gate for a copywriting workflow, followed by a model swap with no loss in quality.
Multi-step AI agents with RAG over market data, and an OAuth 2.0-secured MCP server that lets B2B customers query the platform from their own AI assistants.
Planning, configuration and handover to operations of a Cisco environment with session management, SRST, call recording and provisioning.
AI projects come from our team's experience.
We look at the use case, data and infrastructure and say honestly whether AI is worth it.
Fixed scope, fixed timeline, clear success criteria. The result is a working system – and a measurement.
Monitoring, evaluation on every model change, cost control and support – or a clean handover to the client's team.
Your AI. Your data. In the EU.
20 minutes, without obligation: the situation is described, and we say what AI can realistically do, and what it cannot.