Private AI Platform

Self-Hosted · Sovereign · Scalable

Your Private AI Platform. Your Rules. Your Code Stays Inside.

Your engineering team is already paying $60–80 per developer per month across GitHub Copilot, Cursor, ChatGPT, and other AI tools — while your source code flows through third-party APIs you don't control.

We deploy a self-hosted large language model tuned for software development, inside your own infrastructure. One platform, unlimited usage, zero data exposure, and a fixed cost that scales with your team — not with your token consumption.

  • OpenAI-compatible API — works with VS Code, Cursor, Slack bots, CI/CD
  • Codebase-indexed RAG — the model knows your architecture
  • Pre-built AI agents for code review, onboarding, testing, incident response
  • Departmental usage allocation — IT visibility and internal chargeback
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The Sovereignty Stack

Data Sovereignty

Source code, prompts, and responses never leave your infrastructure. Zero third-party API calls.

Predictable Cost

Fixed monthly or annual fee. Usage grows with your team, not with token consumption.

Codebase Context

Your repos, architecture docs, and runbooks are indexed. The model knows your system.

The Real Cost of Fragmented AI Tools

Most dev teams underestimate what they're spending — and what they're giving away.

Current spend — 50-developer team
Tool Cost / dev / mo Team total
GitHub Copilot $19 $950
Cursor / Windsurf $20 $1,000
ChatGPT / Claude Pro $20 $1,000
Research tools $10 $500
Current total ~$69/dev $3,450/mo
Private AI Platform ~$40/dev $2,000/mo

Plus: code stays inside. Plus: the model knows your codebase. Plus: one bill, not four.

What current tools don't give you
No IP protection

Your source code is sent to third-party APIs on every completion request. Legal and compliance teams often don't know this is happening.

No codebase awareness

Public models know nothing about your architecture, naming conventions, internal libraries, or business domain. Every context window starts from zero.

No organizational control

Multiple subscriptions, multiple policies, no usage visibility per team or project. Finance sees a dozen separate SaaS line items.

Platform Architecture

Six layers — from your developer's IDE to the GPU — all inside your perimeter.

Layer 1 · Developer Experience
VS Code / Cursor (OpenAI endpoint) Web Chat (Open WebUI) Slack / Teams Bot GitHub / GitLab Webhooks CLI / REST API
OpenAI-compatible REST API · Zero tool switching for your dev team
Layer 2 · API Gateway & Auth
Department API Keys Rate Limiting per Team Audit Logs Usage Dashboard SSO / OAuth2
Authenticated requests routed to the right agent
Layer 3 · Agent Orchestration (LangGraph)
Code Review Agent Onboarding Agent Test Writer Agent Incident Response Agent Documentation Agent Tool Registry Memory Manager
Agent queries model + retrieves relevant code context in parallel
Layer 4a · Model Serving (vLLM)
Qwen 2.5 Coder 72B DeepSeek-V3 GPU: A100 / H100 Quantized inference Streaming responses
Layer 4b · Knowledge Layer (RAG)
Qdrant Vector DB Code Embeddings Repo Indexing Pipeline Architecture Docs Runbooks & ADRs
YOUR INFRASTRUCTURE  —  AWS VPC / Azure Private / On-Premise  ·  No data exits  ·  You own the model  ·  You own the data

Every Layer, Explained

Production-grade components chosen for reliability, openness, and best-in-class coding performance.

Developer Experience

Because we expose an OpenAI-compatible endpoint, your developers keep using the tools they already know. VS Code + Continue, Cursor, or any custom Slack bot — zero learning curve, immediate productivity.

VS Code Cursor Open WebUI Slack
API Gateway & Auth

Each department gets its own API key with configurable rate limits and a usage dashboard. IT gets full visibility. Finance gets a single consolidated bill. Audit logs record every query for compliance.

Traefik / Kong OAuth2 / SSO Usage metrics
Agent Orchestration

Built on LangGraph, each agent has a defined role, a set of tools it can call (git, file system, search, APIs), and persistent memory across sessions. Agents chain reasoning steps, not just completions.

LangGraph Tool use Memory Human-in-loop
Model Serving (vLLM)

vLLM is the production standard for serving large language models at scale. It supports continuous batching, PagedAttention for memory efficiency, and delivers OpenAI-compatible streaming responses. We deploy Qwen 2.5 Coder 72B or DeepSeek-V3 — both outperform GPT-4o on most coding benchmarks.

vLLM Qwen 2.5 Coder 72B DeepSeek-V3 A100 / H100 GPU
Knowledge Layer (RAG)

We index your repositories, architecture decision records, API docs, and runbooks into Qdrant — a self-hostable vector database. Before every agent response, relevant context is retrieved and injected, so the model answers about your system, not a generic codebase.

Qdrant nomic-embed-text Chunking pipeline Semantic search
Your Infrastructure

The entire stack runs in your AWS VPC, Azure private network, or on-premise servers. Network policies prevent outbound calls. No telemetry, no model training on your data, no shared tenancy. An air-gapped option is available for the highest security requirements.

AWS / Azure VPC Docker / K8s Air-gap option

Pre-Built Agent Library

Ready-to-deploy agents for the most impactful developer workflows. Each one is customized to your stack, tools, and conventions during onboarding.

Code Review Agent
Triggered by PR webhook

Reviews pull requests against your team's patterns, flags anti-patterns, checks for security issues, and adds inline comments directly in GitHub or GitLab. Understands your existing codebase — not generic best practices.

Saves 30–60 min per PR
Onboarding Agent
Triggered by Slack / Web Chat

Answers "how does this service work?", "where is X configured?", "why was this decision made?" using your indexed repos, ADRs, and docs. New engineers get accurate answers in seconds instead of waiting for a colleague.

Reduces ramp time 2–4 weeks
Test Writer Agent
Triggered on file or diff

Generates unit tests, integration tests, and edge-case scenarios from existing code. Understands your test framework, mocking patterns, and fixture conventions. Runs per-file or across an entire diff at once.

Saves 2–4 hrs per feature
Incident Response Agent
Triggered by alert / log query

Reads error logs, correlates stack traces with your source code, identifies the most likely root cause, and suggests a targeted fix. Connects to your observability stack (Datadog, Grafana, CloudWatch) to fetch relevant context automatically.

Cuts MTTR significantly
Documentation Agent
Scheduled or on merge

Detects drift between code and documentation. Generates summaries for new services, updates README files after structural changes, and keeps API docs aligned with actual endpoints — eliminating the documentation backlog.

Eliminates doc drift
Architecture Q&A Agent
Triggered by Slack / Web Chat

"Can I add a new service here without breaking X?" The agent queries your dependency graph, evaluates the change against existing patterns, and gives a reasoned recommendation — before a line of code is written.

Faster architectural decisions

Deployment Options

Choose the model that fits your infrastructure maturity, compliance requirements, and IT capacity.

Cloud Private Instance

Hosted by NeuronProcess on dedicated GPU infrastructure — isolated per client, fully managed by us.

  • Dedicated GPU instance — no shared tenancy
  • Private HTTPS endpoint, custom domain
  • Model updates and security patches managed by us
  • 99.5% uptime SLA
  • Monthly subscription — zero CAPEX
  • Up and running in days, not weeks
Best for mid-market teams without internal GPU infrastructure

On-Premise / Private Cloud

We deploy the entire stack inside your AWS VPC, Azure private network, or your own data center servers.

  • You own the GPU, the model weights, the data
  • Air-gapped option — no internet required
  • Your IT team has full administrative control
  • One-time setup fee + annual license
  • Annual model upgrade service available
  • Meets the strictest compliance requirements
Best for enterprise, regulated industries, and high-security environments
Dimension Cloud Private On-Premise
Setup time 2–5 days 2–4 weeks
CAPEX required None GPU hardware or cloud reserved instances
Data location Your dedicated cloud region Your data center / your cloud account
Air-gap possible Yes
Model updates Managed by NeuronProcess Annual upgrade service
IT overhead Minimal Your team manages infra

Pricing

Fixed cost. Unlimited usage. No per-token billing.

Starter

Up to 25 developers

$2,500 / month

Cloud Private · Billed annually


  • Private cloud-hosted instance
  • Qwen 2.5 Coder 32B model
  • Up to 3 pre-built agents
  • Codebase indexing (up to 5 repos)
  • Department API keys & dashboard
  • Email support
Enterprise

100+ developers

Custom

On-Premise / Private Cloud


  • On-premise or your cloud VPC
  • DeepSeek-V3 or Qwen 72B
  • Custom agent development
  • Air-gapped deployment available
  • Fine-tuning on your codebase
  • SLA + dedicated support
  • Annual model upgrade service
  • Compliance & security documentation

All plans include a 30-day pilot starting with one agent so your team can validate ROI before committing. Setup fee applies for on-premise deployments.

Already automating? Now make it autonomous.

A Private AI Platform handles developer workflows. Our broader AI Agentic Solutions extend that intelligence to any business process — from customer service to back-office operations — using the same sovereign, self-hosted approach.