Memory that carries work forward
Useful information should carry across conversations. InnerOS organizes documents, context and progress so work can resume with its history.
THE CONNECTING PLATFORM
Things work better when they share context.
InnerOS connects memory, agents, applications and tools. Ralfi IA is its lead agent: helping understand what you need and coordinate the next step.
Tools for real work
Agents query services and prepare actions through integrations. Each connection has a defined scope; reading information and changing a system require different permissions.
People remain in charge
The system can summarize, prepare a quote or gather evidence. Decisions and actions that require review go through a responsible person.
Local capacity and cloud services
Local models offer control over data and resources. Cloud services add options when a task needs different capabilities. Architecture is chosen for the use case.
Voice, Alexa and automation
VoiceOps connects conversations to queries and tasks. Work with Home Assistant, Alexa and Atlas Control explores how to bring that interaction to devices and spaces, validated per integration.
An evolving platform
The platform includes components with documented operation, demonstrators and research work. Each project states its stage; a public demo does not grant access to internal systems.
A CLEAR WORKFLOW
Understand. Prepare.
Review and continue.
A tool adds value when it has a clear purpose and its result can be checked. This is how we approach connections between people, agents and systems.
InnerOS+ Ralfi IA
01
You define the goal
An idea, a need or a question.
02
Ralfi IA gathers context
History, documents and the information that matters.
03
InnerOS coordinates tools
Memory, agents, applications and services.
04
You review the next step
You decide how to continue.
05
The result is recorded
Evidence to check and carry work forward.
Illustrative workflow. Available capabilities are validated per project.
More technical detail and project context
What InnerOS owns
The core concepts: persistent memory, agent registry, task state, evidence, tool permissions, model routing, file/document context, runbooks, operational messages and rollback-aware execution.
How it coordinates
ChatGPT, Codex, Cursor, Open WebUI, local agents and operational services read a shared live state through MCP and Mongo-backed coordination instead of relying on one fragile conversation.
How it decides compute
Task classes such as coding, heavy reasoning, browser review, tests and fallback can be routed to the right node or provider with explicit evidence.
How it stays governed
Sensitive operations use approval gates, status labels, evidence requirements and public/private boundaries. A public page can explain the architecture without exposing private execution.
Why it matters
InnerOS makes AI useful beyond a chat window: it can remember, reason, coordinate, act through tools and prove what happened.
Primary Intel Node
Coordination services, browser/build/test work, fallback execution, MCP access, Open WebUI integration and daily operational services.
AMD Local AI Node
Local-first AI capacity for coding, heavy reasoning and private model experiments, with vLLM/ROCm direction and rollback-aware model registry.
Ralfi IA MCP
Shared bridge for ChatGPT, Codex, Cursor, Open WebUI and agents. It exposes tools, state, runbooks, documents and operational actions under governance.
Cloud + Edge
Cloud Run, Cloudflare, Google Cloud, Alibaba Cloud and external model providers extend reach when public access, scale or advanced models are needed.
Infrastructure and inference
Learn more ↗Meet Ralfi IA
Learn more ↗System architecture
Learn more ↗InnerOps and operations
Learn more ↗Responsible AI
Learn more ↗Technologies and integrations
Learn more ↗THE NEXT STEP STARTS WITH A CONVERSATION
What would you like
to make possible?
Tell us about the idea, problem or project. We will help you find the right area and a sensible first step.