PlatStone

About PlatStone

Platform meets Stone

We give development teams a private AI foundation — local models on your own hardware, trained on your codebase, as enduring and trustworthy as stone. Your data stays yours. Your engineers move faster.


01

Our Story

PlatStone was born from a simple tension: AI has made developers dramatically faster, but the best tools want your source code shipped off to someone else's servers. For most serious teams — especially in regulated industries — that's a non-starter.

So we built a different answer. We combine platform engineering with the discipline of building rock-solid foundations — Platform + Stone — to give every developer a private AI that runs locally, knows your codebase, and never leaks a line of it.

02

Our Mission

Put a private, codebase-aware AI in the hands of every developer — fast, local, and fully under your control. We measure success in one currency: how much faster your team ships.


What Sets Us Apart

Private by Default

Everything runs on your hardware — on-prem or fully air-gapped. No third-party APIs, no telemetry, no code leaving your network. Privacy isn't a setting; it's the architecture.

Developer-Experience Obsessed

If it's not faster than what your engineers already use, it won't get adopted. We tune relentlessly for low latency and answers that actually fit your codebase.

Always Improving

Open models leap forward every few months. We keep your platform current — new models, fresh indexes, better retrieval — so it never goes stale.

No Vendor Lock-in

Open models, open standards, open formats. Everything we build is yours, documented and runnable by your team — with no proprietary dependency on us.


Technical Expertise

Deep experience across the local AI stack — from inference serving and open models to retrieval, IDE tooling, and on-prem infrastructure.

vLLM Ollama llama.cpp TGI LM Studio Llama 3 Qwen DeepSeek Mistral Continue.dev Cursor Tabby JetBrains AI Qdrant pgvector Chroma Weaviate LlamaIndex LangChain Embeddings Fine-tuning Docker On-prem Kubernetes GPU Servers Air-gapped Deploys Prometheus Grafana