We deploy OpenClaw or an equivalent: routing between local and cloud models, a skills library, rate limits, and PII masking before sending data to the cloud. Switch models without rewriting integrations.
cashcrown // ai.infra
AI gateway / router
multi-model, fallback, cost control.
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Problem
You need “AI gateway / router”, but building it in-house gets stuck on integrations, maintenance and lack of time — and the result tends to be fragile and hard to scale.
// 02
What we build
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Process
- Sizing and cost
Choosing models and hardware to fit real load and budget.
- On-prem deployment
LLM serving + embeddings, fronted by a router/gateway.
- RAG over knowledge
Document indexing, semantic search, answers with citations.
- Hardening
Observability, backups, network isolation, cost control.
// 04
Stack
self-hosted LLMOllamavLLMBGE-M3QdrantNSSM / systemd
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Related
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FAQ
How much does this service cost and when does it pay off?#
We work in ranges that depend on scope — we start with a fixed, low-cost pilot so you see the value before a larger investment. When the service takes back a dozen to several dozen hours of work a month, it usually pays off in 2–4 months. Calculate your concrete return in the ROI calculator; we don't quote fixed prices upfront because they depend on the actual scope.
Does it integrate with our systems and is it GDPR-compliant?#
Yes. We connect to your systems (CRM, email, databases, n8n) through controlled, allow-listed tools, and irreversible actions require confirmation (a human-gate). We mask PII before anything leaves for the cloud and handle sensitive paths locally — GDPR and AI Act compliance designed in from the start.
How do we start?#
With an audit and a pilot on one narrow scope with a measurable result. We show a working service before we ask for your trust — then expand the scope step by step. More on the approach: how to choose the first process.