Intelligence at Production
Altitude
Alpine Icicle integrates AI into SaaS platforms and deploys it on your own hardware — engineered for data sovereignty, real throughput, and measurable results.
--port 8080 -ngl 999
inference throughput
SaaS AI Enablement
We integrate AI agents into your existing SaaS. Users get natural language access to production data through tool-calling architecture with full observability and measurable performance — not just an API wired up, but a system validated by real benchmarks.
- Tool-calling agent architecture
- TimescaleDB & MongoDB backends
- Provider-agnostic via Vercel AI SDK
- Langfuse observability
On-Premises AI
We deploy a complete local AI stack on your hardware — inference, RAG, orchestration, and agent workflows running at frontier-class performance with zero cloud dependency. Your data never leaves the building.
- llama.cpp inference at 53 tok/s
- Open WebUI + n8n orchestration
- ChromaDB vector store & RAG
- Slack, chat, and coding agents
Deployed in the Real World
Both use cases come from production work — not demos.
AI Assistant in a Smart City Integration Platform
Users of a traffic monitoring SaaS needed natural language access to data across multiple modules — building a dedicated view for every combination of inputs wasn't viable.
Seven tool-calling agents with Zod-validated schemas, backed by TimescaleDB (hypertable time series, 10–20× compressed) and MongoDB. Vercel AI SDK provides model-agnostic abstraction. Langfuse tracks every token and tool call.
Generic LLM-generated MongoDB queries achieved 100% success (18/18) at 4,539 tokens and 5.8s average response — 12× fewer tokens and 3× faster than specialized tool-per-query approach (44%, 54,849 tokens, 15.4s).
Model: GPT-5.4-mini · 6 test queries · correctness validated against reference data
Your Data. Your Hardware. Your Stack.
Four reasons teams choose local AI deployment over cloud APIs.
Data Privacy & Compliance
Sensitive data never leaves the building. Meet GDPR, HIPAA, and data residency requirements by design — no DPAs, no third-party processor risk.
Operational Independence
No internet dependency, no vendor outages, no surprise API deprecations. The stack runs whether the cloud is up or not.
Full Control & Auditability
Choose any model, swap versions instantly, fine-tune on proprietary data. Full visibility into what runs, what data it sees, and what gets logged.
Predictable Cost at Scale
One-time hardware investment, zero per-token billing. No usage spikes, no metering surprises — cost decouples from adoption.
Ready to Deploy AI in Production?
Let's talk about your use case — SaaS integration, local hardware, or both.