We deploy MLX Serve
into your environment.
From scoping to production in two weeks. On-premises, air-gapped, cloud, or hybrid. Your team operates it independently from day one.
Choose how we work together
Sprint deployment
Two-week engagement. We scope, configure, and deploy working AI workflows. Money-back guarantee if we don't deliver.
Managed platform (PaaS)
We handle infrastructure, updates, and monitoring against an agreed support SLA. Start managed, move on-prem later.
Training & workshops
Structured training for developers, operators, and security teams tailored to your deployment.
Advisory & custom development
Bespoke agents, integrations, and workflow automation built to your exact specifications.
Ongoing support and service level agreements are priced separately from implementation. We will scope one with you during the engagement.
What MLX Serve ships
The open-source engine, in full. Nothing here is locked.
Unified model runtime
Text, image, video, music, speech, and 3D from one server and one model cache. A model loads on demand and unloads when it is done.
Four API surfaces, one port
OpenAI chat completions and Responses, Anthropic Messages, and the Ollama API. Existing clients point at it unchanged. There is no SDK to adopt.
Declarative agents and skills
Skills are markdown with YAML frontmatter. Agents, MCP servers, and prompts are plain files. Nothing hides in a database, so you review and ship them through git.
Sandboxed execution
Agent shell commands run inside an isolated Linux VM that boots in under a second. The host machine stays untouched.
Tool ecosystem
Full MCP client with a curated server catalog and ten built-in tools. Each tool sits behind an approval prompt: allow once, allow for the session, or deny.
Local model management
Resumable downloads with RAM estimates before you commit, loading by name, and model sharing between machines on your LAN. It finds models you already have so nothing downloads twice.
The controls your security team will ask for
Paid components that sit on top of the engine. Support for the engine is included.
Modern authentication
Single sign-on with the identity provider you already run. Access follows the accounts and groups you manage today, so there is no second directory to maintain.
Role-based access control
Roles decide who reaches which agents, models, and tools. Scope a team to what it needs, and show a reviewer exactly who can do what.
Enterprise logging
Structured, exportable records of access and activity, built to land in the log platform your security team already watches instead of a console they have to remember to open.
Rate limiting
Per-user and per-team ceilings on request volume, so one workload cannot exhaust shared capacity for everyone else.
Support for all of it
Support covers the add-ons and the engine underneath. We scope it with you during the engagement.
Or build them yourself
The engine is MIT, so you can build your own versions of these. Most teams would rather buy ours.
Where the line sits
Free: the engine. MIT licensed, complete, nothing locked.
Paid: the add-ons above, and support.
The add-ons are extra parts we built. They are not engine features we took out.
What we build for your environment
Engagement work, scoped to you. This is where the orchestration, data, and integration effort goes.
Multi-agent workflows
Orchestration across agents, with retries, branching, and human approval gates. We build and run this layer on top of the engine.
Knowledge pipelines
Postgres, MySQL, SQLite, file shares, and web APIs, indexed against your own data and reindexed on a schedule.
Customer-facing endpoints
Published agents behind your own auth, rate limits, and logging. Safe to hand to people outside engineering.
Integration with your systems
Wiring the platform into the identity, ticketing, and data systems you already run, so it fits the way your teams work.
Deploy anywhere your data lives
Your coding agents, pointed inward
The server speaks the OpenAI, Anthropic, and Ollama wires, so the tools your engineers already use connect straight to it. No proxy, no rewrite, no prompts leaving the building.
- Claude Code, Cursor, Zed, Continue, and aider on local models
- One-click launchers, already set to the real context window
- Model sharing across machines on your LAN, zero setup
- Optional API key on every request from off the machine
On-premises
Entire stack inside your perimeter, running fully disconnected. That is the isolation CJIS, HIPAA, and ITAR work depends on.
Cloud
Fastest path to production. Managed GPU capacity, cloud providers, or your own hardware, whichever your data policy allows.
Hybrid
Sensitive workloads on hardware you own, everything else in the cloud. The same agent and skill files work in both.
Native desktop apps
A code-signed desktop app bundles the server behind a full UI. No terminal required, nothing to configure.
Hardened by design
Access control
The engine can require an API key on every request from off the machine. Single sign-on and role-based access are enterprise add-ons.
Sandboxed execution
Agent shell commands run in an isolated Linux VM. Nothing they touch reaches the host filesystem.
No Python, no supply chain
A single code-signed binary. No interpreter, no package manager, no transitive dependency tree to audit.
Visible and reviewable
Live request monitoring, full server logs, and configuration you review in git. Retained audit records are an enterprise add-on.
2-Week Money-Back Guarantee
We agree on success criteria before we start. If we don't deliver a working AI workflow that meets them within two weeks, you get your money back. We carry the risk, not you.
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