AOS · Agentic Operating System
One platform to run and govern every AI agent, behind your firewall, on your existing infrastructure.
Inside each layer
Three layers. Every agent you build reuses all of them.
03 · Your control room
One place to see, measure and improve every agent, including the ones you didn't build with us.
Dashboards
Live activity across every agent
Agent registry
Every agent, its owner and status
Traces
Every step, with time, tokens and cost
Prompts & content
Change what an agent says, live
Scores & LLM judge
Quality measured on every session
Alerts & audit log
Who did what, and when
02 · Your agent factory
Every agent starts with a job description, tools, a model and rules.
Base agent
Job, tools, model and rules
Orchestration
Plans and runs multi-step work
Tools over MCP
A per-agent allow-list
LLM router
Swap the model, keep the agent
Memory & knowledge
Context that compounds
Retrieval
Answers grounded in your documents
Guardrails & policies
Hooks around every call
PII masking
Personal data never reaches a model
Connectors
CRM, ERP, email and more
01 · Your building
Installed as infrastructure-as-code in your Azure, Google Cloud or AWS tenancy, or on premises. Nothing leaves your perimeter.
Containers
Agents and services
Databases
Stored in your tenancy
Vector search
Your knowledge, indexed
Model endpoints
Models in your region
Secrets vault
Keys stay with you
Private network
No public endpoints
Identity
Managed identities, no keys in code
Logging & monitoring
Into your own SOC
Getting started
The path we follow with every customer, from AOS in your cloud to the first agent in production.
The plan, week by week
Week 1 starts with the workflow
Workflow selectionWeeks 1 to 3
FoundationWeeks 1 to 2
ConfigurationWeeks 3 to 6
RolloutWeeks 6 to 9
Weeks 1 to 3
One high-cost process, defined KPIs and a process owner, chosen alongside the foundation.
Weeks 1 to 2
AOS is deployed in your cloud and connected to your identity, network and secrets.
Weeks 3 to 6
The agent runs side by side with the team until accuracy is validated.
Weeks 6 to 9
Production deployment, handover to the business and continuous monitoring.
Integrations
We build the agents. AOS runs them in your cloud, on your models, connected to your systems.
Qlik
Snowflake
Ongoing WMS
Slack
Fortnox
Fluent Commerce
GitHub
Kubernetes
DocuSign
Elastx
Dynamics 365
Google Gemini
Mistral
Shopify
Jira
Intercom
Quinyx
On-premises
Microsoft Azure
OpenAI
ServiceNow
Freshdesk
Gmail
Cohere
Outlook
Salesforce
AWS
HubSpot
IBM Maximo
Twilio
Rillion
Visma
Anthropic Claude
Google Cloud
Berget AI
Klarna
DeepSeek
Confluence
Ingrid
AWS Bedrock
SAP
Microsoft Teams
nShift
Meta Llama
PostgreSQL
Google Drive
SharePoint
Zendesk
Power BI
Dixa
Databricks
NVIDIA NIMFAQ
The questions your security, risk and IT teams will ask, and where AOS answers each one.
In your own Azure, Google Cloud or AWS tenancy, or on premises. It is stored and logged there, behind your firewall.
No. Personal data is masked before the model sees it, and again before anything is stored.
No. Swap the model without rebuilding the agent. Its job, tools and rules stay the same.
Only the tools on its allow-list, connected over MCP. Policies run as hooks around every model and tool call.
Every step is traced in AOS Control with time, tokens and cost, including agents you didn't build with us.
As infrastructure-as-code into your subscription or project: databases, containers, secrets and monitoring.
We walk you through AOS with your systems, your data and one of your processes.
