An enterprise OS built around Full Automation and Continuous Improvement.

Improved Iteration Current State Optimization Scoring

AI-embedded Continuous Improvement Cycle

Each iteration improves on the previous iteration, each creating a new layer of optimization

Current OS models are built around apps.

Clara OS is a cloud OS built around process improvement, scoring, cost balancing, role optimization and iterating to reach full automation.

AI Workstations

Iterate to the next improvement step with one or multiple AI assistants

Use existing industry or role workstations or configure your own.

App Models

Build apps faster with ready made templates which are AI ready

Reduce costs and time to implementation drastically. Select from a library of App Models which can be used to create apps

Workspaces

Combine apps together to build an all-in-one solution using AI

Use as a standalone tool or use inside the OS platform. Use existing workspaces by role, industry, function or build a custom one using AI builder.

Apps

Build new types of apps which train users and AIs

Apps which can be execute inside or outside the OS. Start with an App model or build from scratch with an AI based on a process.

Chatbots

Create custom interfaces which can email, chat, text, meet or talk

Use AI to build custom communication apps based on roles and app models. Communicate with one or multiple LLMs inside a new custom chat app. Go beyond the standard one size fits all chat app to gain leaps in productivity.

AI Models

Leverage AI models inside your improvement cycles

Employ app models to improve automations, processes and apps.

Data Hub

Data for everyone. Make it easier for all team members to know their data

Data knowledge is no longer a barrier for improvement.

Score Models

Score automations, processes and AIs easily

Everything is scored. Apply various score models to gage the value added by an AI, automation, process, app.

Process Hub

Refine and enhance processes with process templates

Define new process templates using AI. Use process templates to create full apps, workspaces, automations.

Enterprise Ontology

Search solutions by enterprise ontology, functions and industry

Use existing role and industry templates to combine and build custom roles

Automations

Create, modify and use ready-make automations into the improvement cycle

Use UI automation builder or create an automation based on a process. Include automations inside App models. Combine full code, mixed code or full UI based automations.

UI Canvas

Use floating UI canvases inside any browser as your OS interface

Build custom floating UIs inside any browser to invoke any OS component such as apps, AI workstations, automations, etc

AI Agents

Easily train AI models with data in various forms and sources

Use AIs to help stage, transform and prepare data for AI models.

App Engines

Boost the app SDLC and maintenance with low code platforms

Low Code platforms which are vendor neutral. Build a new low code platform using AIs and TAMs.

Two new layers above current OS Models

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01

Automation Layer

02

Process Layer

03

UI Layer

04

Cloud/Data Layer

05

Device / Hardware Layer

App Model Trees define full solutions and products

TAMs are the basic building block of ClaraOS. Within one TAM (Transportable App Model TM) there are sub-nodes in an App Model Tree. Each node defines various components of the process, app, AI model, logic, etc. App Models can be executed inside Cloud CPUs to run apps, workspaces, and business solutions.

Root Node Nodes TAM Sub-Nodes TAM Schema

Apps that can talk, chat and train users

Apps developed within the TAM Layer are built using TAMs (Transportable App Models TM). The TAM layer provides a new set of abilities for apps:

  • Voice communication
  • Chat Access
  • Multi-bot support
  • AI training
  • User training
  • Data schema changes
  • End user training
  • Data schema training
  • App self-testing
  • App self-scoring
  • Embedded process definitions
  • App Telemetry

Execute TAMs and create next improvement iteration

Manage the entire solution SDLC cycle and maintenance by maintaining everything inside a TAM. Run full solutions inside or out of the Cloud CPUs.

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Usage : 86%

Easily manage multiple environments by running different instances of the TAM. Use AI to iterate optimizations of the TAM Model. Run complex systems inside the Cloud CPUs without worrying about capacity, cloud, or database.

Data is everything

A methodology where everyone knows data. Every role, every automation, every bot needs data. Without data, any AI or app cannot function. The TAM data schema securely removes the mystery of the data. Multiple layers above a traditional DB schema. TAM apps which run on the Cloud CPUs use the TAM schema. Use AI Studio to build and enhance components.

Mass Iteration Recursive Methodology

A new methodology which takes all project participants into the mix: AIs, Staff Teams, Contractors, Highly specialized consultants, and Teams using AIs. Create anything in small teams or teams with thousands of contributors and AIs.