North star
AI-native systems
AI is part of the architecture: agents, capabilities, data models, prompts, tools, memory, and evaluations are first-class engineering concerns.
AI-native by design
Platform engineering for the next operating model.
MarkOS builds practical AI-native systems: consulting, automation, agentic development platforms, secure workflow architecture, and applied products that move from idea to operation.
Company and platform
MarkOS is an AI-native engineering company.
MarkOS brings together consulting services, applied AI products, automation, and the platform work needed to make those systems reliable.
Atlas is the internal platform underneath it: reusable capabilities, declared environments, private networking, typed contracts, agent and model gateways, workflow ledgers, evals, and fast deployment paths.
ContractedOpenAPI, generated clients, policy checks
AgenticAgents, tools, model gateways, evals
OperableDeclared state, traces, repeatable deploys
What MarkOS delivers
- AI platform engineering: capability platforms, agent/model gateways, runtime placement, and deployment workflows.
- Consulting and enablement: automation, system improvement, AI adoption, and practical operating changes.
- Applied products: legal workbench, mail and connection services, radio, social agents, document intelligence, and workflow tools.
Platform discipline
Service boundaries
Applications are focused surfaces over shared capabilities, declared contracts, gateway-routed services, and repeatable deployment primitives.
Evidence layer
Traceable work
Agent actions, workflow steps, model calls, release evidence, and source-backed memory are treated as platform facts rather than hidden transcript state.
Current platform focus
From AI apps to an agentic development platform.
Atlas is being built around capability contracts, agent/model gateways, workflow ledgers, environment-aware deployment, private Tailscale transport, source-backed memory, and eval evidence. The goal is not a collection of demos; it is an operating layer where AI systems can be built, reviewed, deployed, and improved with the same discipline expected from serious platform engineering.