Documentation Map
Learn The Details Behind The Technology
The technology pages explain the story. The docs explain how users operate Kaidera: getting started, Cortex memory, PROMI, model capabilities, trust controls, FAQs, and practical how-to guides.
Start with the product story
Use the website to understand the business outcome: what Kaidera does, how the AI worker team works, and where human review fits.
Back to technology overview →Learn the operating model
Use the docs to understand Cortex memory, PROMI orchestration, worker handoffs, model capabilities, and trust controls in plain language.
Open documentation →Connect details to decisions
When a buyer or operator asks for more depth, link them to the relevant guide rather than overloading the landing page.
See how-to guides →Recommended first reads
The shortest path from story to operation
These docs are the natural continuation after the main technology pages. They explain the user-facing logic without forcing buyers into implementation details.
Start here
Getting started with Kaidera
A practical orientation for teams evaluating Kaidera: why it exists, how to get access, what the platform does, and what to review first.
Open guide →
Platform service
Cortex memory and project intelligence
Cortex is the memory and retrieval system behind Kaidera workers. It stores decisions, lessons, handoffs, documents, code intelligence, and project context.
Open guide →
Platform service
PROMI orchestration
PROMI turns goals into scoped work, routed handoffs, verification evidence, review gates, and resumable project progress.
Open guide →
How-to
Cortex command guide
How Cortex commands support project memory, handoffs, verification, graph review, and operating evidence.
Open guide →
Model settings
AI model capabilities
How Kaidera uses available AI models across text, reasoning, vision, voice, embeddings, and routing.
Open guide →
Trust
Trust and security
How Kaidera keeps work reviewable: project boundaries, credentials, approval gates, public/private separation, and evidence trails.
Open guide →
Full docs index
Link each documentation page back to the product story
Start Here
A practical orientation for teams evaluating Kaidera: why it exists, how to get access, what the platform does, and what to review first.
The plain-language origin story: Kaidera was built to deliver an ambitious aviation product that ordinary delivery could not.
How customers currently get access, what the self-service path will become, and what to prepare before the first project.
A map of the main Kaidera product surfaces: project workspace, AI worker team, Cortex memory, admin controls, docs, and review gates.
Backup And Recovery
Kaidera Infrastructure
The public operating guide for Kaidera Infrastructure: an AI-run team that designs, deploys and operates cloud, datacenter and hybrid estates.
How discovery, maturity assessment, function selection and architecture decisions produce a customer-specific cloud, datacenter or hybrid design.
The named AI workers, deterministic agents, ownership model and escalation ladder behind the service.
The five-phase service loop, autonomy model, work routing, change gates and evidence flow from request to verified outcome.
How the turnkey Kaidera Infrastructure team is instantiated, connected to customer environments and moved through controlled deployment.
The full Run-phase service catalog: platform, network, identity, observability, ITIL, resilience, internal tooling and continual improvement.
How cybersecurity, security operations, authorized testing, risk management and compliance evidence are integrated into infrastructure operations.
How cost control, action evidence, audit trails and management reporting become continuous operational capabilities.
A practical customer journey from the first discovery conversation to a connected, evidence-producing infrastructure service.
Marketing OS
The operating guide for Project Marlow: an approval-led AI marketing function that turns a clear business goal into accountable, channel-ready work.
How Marlow, Saul, Gem, narrow specialist workers, and named human approvers divide marketing responsibility without losing a clear release authority.
The boundaries that keep public marketing work attributable, consent-aware, on-brand, and subject to named human release authority.
How a focused cadence keeps research, drafting, verification, approvals, publishing, and learning visible rather than hidden inside one long-running task.
What to prepare for an initial Marketing OS discovery conversation and how to stage a safe first operating scope.
Kaidera OS
The operating guide for Kaidera OS: what it is, how to install it, how to bring a project online, and how the local control plane works.
Install Kaidera OS, start the local console, confirm the runtime is healthy, and understand the first-run setup flow.
Install the commercial macOS package, complete guided setup, start the local runtime, and use repair and recovery tools.
Register a project, set the workspace root, seed the first worker roster, and run work through approval before enabling autonomy.
Understand leads, orchestrators, AI workers, deterministic jobs, dispatch, handoffs, approval, and run-state evidence.
How Kaidera OS uses Cortex for project memory, registry data, decisions, handoffs, evidence, and boot context.
Set up model providers, choose model routes, understand the catalog, and keep API keys out of code.
How Kaidera OS download, license activation, feature unlocks, account state, and edition boundaries are expected to work.
A documentation guide to the generated Kaidera OS operational ontology: the appliance design, the objects that govern work, and the boundaries between Kaidera OS, Cortex, and OpenKai.
A deeper look at the local console, Cortex API, app database, worker harnesses, run-state streaming, packaging, and extension boundary.
Operate Kaidera OS safely: local access, secret handling, project boundaries, remote access, health checks, and common failure modes.
Projects And Workbench
How to turn a business idea into the first Kaidera project request without needing to write a technical specification.
The main operating surface for following project work, reviewing evidence, and understanding what the AI worker team is doing.
How project files, diagrams, notes, generated outputs, and customer-provided material are organised in Kaidera.
Draw And Design-First Workflow
AI Workers
Kaidera uses a team of specialised AI workers rather than a single generic assistant. Each role has its own lane, tools, and completion expectations.
The default Kaidera roles customers will see first: product intake, coordination, implementation, QA, knowledge, and review support.
How customers define specialist AI workers for their own business functions, knowledge, review style, and approved tools.
Cortex And Platform Services
Cortex is the memory and retrieval system behind Kaidera workers. It stores decisions, lessons, handoffs, documents, code intelligence, and project context.
A plain-language guide to how Cortex helps Kaidera remember projects across long-running work.
How Kaidera connects project concepts so users and AI workers can understand relationships, not just isolated notes.
How Cortex makes AI work reviewable by recording ownership, next steps, verification, and residual risk.
PROMI turns goals into scoped work, routed handoffs, verification evidence, review gates, and resumable project progress.
How Kaidera runs worker tasks inside bounded workspaces with scoped tools, evidence packages, pause and resume points, and human review gates.
Live Testing And Demos
Models And Providers
Steering, Guardrails, And Approvals
Skills, Tools, And Integrations
Admin And Settings
How administrators configure AI providers, bring their own keys, discover available models, and control which models customers can use.
What customer admins configure: organisation details, people, roles, teams, security, models, billing, support, and usage controls.
Billing, Plans, And Usage
Support And Troubleshooting
Trust And Enterprise
How Kaidera keeps work reviewable: project boundaries, credentials, approval gates, public/private separation, and evidence trails.
Enterprise options for stronger boundaries: self-hosted branches, managed model programs, data residency, isolated deployments, and air-gapped scenarios.