Part of the Kiwi Edge AI Stack | Founder OS: NZ-Start-Up | Agent policy: .github/agent-fleet/
Sovereign hybrid edge AI for NZ farms and founders - local-first + multi-model, Te Mana Raraunga aligned - collaborating with Venture Taranaki, startups.com investors and Kotahitanga Investment Fund (HITL + cultural advisory for formal approaches).
See AI Infrastructure Leadership for our positioning as New Zealand's leader in sovereign edge AI Infrastructure.
Agents inform, draft, prepare, monitor, and remind. Humans advise, sign, file, send, and pay.
Anti-hallucination policy: .github/agent-fleet/anti-hallucination.md | Congruence: CAT_CONGRUENCE.md
Aether is the sovereign agentic companion (including computer-use paths) with hard HITL ceilings for NZ builders.
- Unconstrained agent hype - "Autonomous employees" create legal, tax, and cultural risk in NZ.
- Tool sprawl - Founders and engineers need one companion that can draft and operate tools under policy.
- Offshore default - Agentic stacks often assume US cloud identity and data paths.
- Weak explainability - Operators need skill routing and human gates, not black-box actuation.
| Built capability | What it does |
|---|---|
| Agent orchestrator | ReAct-style loop + skill routing |
| Computer-use path | Desktop operation where explicitly enabled |
| Skill packs | Super Grok governance skills (aether-core, CAT standards, skills CI) + NZ Start-Up fleet under skills/nz-startup/ |
| Licence | Proprietary (Coastal Alpine Tech) - internal companion across CAT products |
Skills guide: docs/SKILLS.md
Policy slogan: Agents inform, draft, prepare, monitor, and remind. Humans advise, sign, file, send, and pay.
| Lever | Benefit |
|---|---|
| Regional R&D HQ | Product design and IP stay in New Plymouth / Taranaki - not only Auckland/offshore SaaS |
| Primary-sector productivity | On-farm and rural tools aim to cut waste, protect consents, and support export competitiveness |
| Skilled employment pathways | Edge install, field support, agritech ops, software, compliance, and cultural advisory roles as pilots scale |
| Data sovereignty | Te Mana Raraunga-aligned local custody keeps high-value operational data onshore |
| HITL jobs quality | Agents inform / draft / prepare / monitor / remind; humans advise / sign / file / send / pay - augment people, do not fake full autonomy |
Stage honesty (pre-seed): Impact today is founder R&D, near-term contractors, and EDA/partner leverage. Permanent multi-region payroll follows paid pilots and revenue - we do not invent headcount claims.
Sovereign Agentic Development System
Aether is a culturally grounded, extensible agentic development orchestrator. It helps you plan, debug, scaffold, and execute development work using tools and reusable skills while keeping you in control through strong human oversight.
Coastal Alpine Tech Limited pre-seed startup, New Plymouth, Taranaki, Aotearoa New Zealand.
Canonical edge target: Raspberry Pi 5 (16GB) with Hailo-10H NPU (40 TOPS). Local LLM via Ollama (qwen2.5-coder / Gemma 4 class models).
Diagrams: Architecture images and Mermaid maps describe the target product architecture for this pre-seed stack. They are engineering design maps not claims of large-scale commercial fleet deployment.
Aether is the sovereign agentic development orchestrator for the stack: ReAct loop over local tools and markdown skills, with HITL gates and optional Ollama (qwen2.5-coder / Gemma-class models) on developer or edge hardware.
%%{init: {
"theme": "dark",
"themeVariables": {
"fontSize": "15px",
"fontFamily": "Inter, ui-sans-serif, system-ui, sans-serif",
"primaryColor": "#0ea5e9",
"primaryTextColor": "#f8fafc",
"primaryBorderColor": "#38bdf8",
"lineColor": "#67e8f9",
"secondaryColor": "#1e293b",
"tertiaryColor": "#0f172a",
"clusterBkg": "#0b1220cc",
"clusterBorder": "#38bdf880",
"titleColor": "#e2e8f0"
},
"flowchart": {
"nodeSpacing": 36,
"rankSpacing": 44,
"padding": 18,
"htmlLabels": true,
"curve": "basis",
"useMaxWidth": true
}
}}%%
flowchart TB
classDef act fill:#422006,stroke:#fbbf24,stroke-width:2px,color:#fffbeb
classDef core fill:#134e4a,stroke:#2dd4bf,stroke-width:2px,color:#f0fdfa
classDef ai fill:#3b0764,stroke:#e879f9,stroke-width:2px,color:#fdf4ff
classDef store fill:#1e1b4b,stroke:#a5b4fc,stroke-width:2px,color:#eef2ff
classDef host fill:#0c4a6e,stroke:#38bdf8,stroke-width:2px,color:#f0f9ff
classDef desk fill:#052e16,stroke:#4ade80,stroke-width:2px,color:#f0fdf4
classDef stack fill:#312e81,stroke:#a5b4fc,stroke-width:2px,color:#eef2ff
G["Goal / CI signal"] --> ORCH["AetherOrchestrator<br/>ReAct loop"]
ORCH --> LLM["Ollama client<br/>JSON action contract"]
ORCH --> SK["Skill loader<br/>skills/*/SKILL.md"]
ORCH --> TL["File tools<br/>read | search | write | memory"]
ORCH --> CU["Computer use hybrid<br/>screenshot | click | type | shell"]
ORCH --> GR["Guardrails + threat model<br/>HITL gates"]
LLM --> DEC["Validated decision"]
DEC --> GR
GR --> | approved | TL
GR --> | approved | CU
GR --> | halt / approve | HITL["Human approval"]
TL --> MEM["JSONL memory / audit"]
CU --> MEM
SK --> ORCH
subgraph HOSTS["Hybrid hosts one code path"]
WIN["Windows 10/11<br/>install.ps1 | pyautogui"]
LIN["Linux / RPi OS<br/>install.sh | X11/Wayland"]
MAC["macOS optional"]
end
subgraph STACK["Kiwi Edge hybridisation"]
CORE["Coastal-Alpine-Core skills"]
WEA["Weaver multi-tenant mesh"]
CAS["coastal-alpine-stack monorepo"]
end
ORCH -.-> HOSTS
SK -.-> CORE & WEA & CAS
CU -.-> WIN & LIN
class G,HITL act
class ORCH,SK,TL,CU core
class LLM,DEC ai
class GR,MEM store
class WIN,LIN,MAC host
class CORE,WEA,CAS stack
| Layer | Components | Role |
|---|---|---|
| Loop | ReAct + tools + computer use | One action per step (files or desktop) |
| Skills | Markdown packs + Kiwi Edge skills | Domain procedures + stack architecture |
| Safety | Guardrails + skill HITL | Writes / desktop actuation gated by default |
| LLM | Ollama local (text + vision) | Offline-capable on Windows, Linux, RPi |
| Hosts | install.ps1 |
install.sh |
| Hybrid stack | Core | Weaver |
Full detail: docs/ARCHITECTURE.md | docs/GETTING_STARTED.md
Linux / macOS
curl -fsSL https://raw.githubusercontent.com/fivepanelhat/Aether/main/install.sh | bash
aether doctorWindows (PowerShell)
irm https://raw.githubusercontent.com/fivepanelhat/Aether/main/install.ps1 | iex
aether doctorNote: If script execution is blocked:
Set-ExecutionPolicy -Scope CurrentUser RemoteSigned
Linux / macOS
git clone https://github.com/fivepanelhat/Aether.git
cd Aether
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[computer]" # or: pip install -e . for CLI only
aether init
aether --help
aether skills
aether run "Audit the API routes for security issues"Windows (PowerShell)
git clone https://github.com/fivepanelhat/Aether.git
cd Aether
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -e ".[computer]" # or: pip install -e . for CLI only
aether init
aether --help
aether skills
aether run "Audit the API routes for security issues"Prerequisites (both platforms): Python 3.10+, Git, Ollama for local models. On Linux desktop control also needs a display server (X11/Wayland) and often python3-tk / scrot depending on distro.
- Getting Started Guide: A complete guide on how to use Aether's ReAct loop and tools.
- CLI Reference: A detailed reference of all available CLI commands.
Trigger the error remediation workflow on a specific error or CI failure.
aether remediate "CI failed on main branch with test error in user.test.ts"Aether now hybridises sovereign edge AI with computer use: a local (Ollama) vision model looks at screenshots and drives the real mouse, keyboard, and shell to accomplish goals entirely on-device. No screenshots or keystrokes leave the machine. Works on Windows and Linux (and macOS) from one code path.
Linux / macOS
curl -fsSL https://raw.githubusercontent.com/fivepanelhat/Aether/main/install.sh | bashWindows (PowerShell)
irm https://raw.githubusercontent.com/fivepanelhat/Aether/main/install.ps1 | iex
aether doctorOr from a clone, install the desktop extras alongside the base package:
pip install -e ".[computer]" # adds pyautogui + Pillow
aether doctor # verify Ollama + display + backendThe installers create an isolated virtualenv, expose the aether command on your
PATH, install the bundled skills, and check for the local Ollama
runtime. Pull a vision model once:
ollama pull qwen2.5-vl:7b # vision model for the agentic loop
ollama pull qwen2.5-coder:7b # text model for `aether run`# Vision loop: Aether observes the screen and acts to reach the goal.
aether computer run "Open the calculator and compute 12 * 9"
aether computer run "Rename the selected file to report_final.txt" --max-steps 15
# Authorize actuation without per-step prompts (batch / trusted contexts):
aether computer run "Tidy my downloads folder" --auto-approve
# Rehearse without touching the mouse/keyboard:
aether computer run "..." --dry-runBy default every actuating step (click, type, key, scroll, shell) pauses for
human approval on a TTY, routed through the same guardrails/HITL layer that
gates Aether's file writes. screenshot and screen_info are read-only and
never gated.
Environment switches: AETHER_COMPUTER_DRY_RUN=1 rehearses without actuating;
the vision model/host are overridable with --model / --base-url.
Skills are markdown packs under skills/*/SKILL.md, auto-loaded at runtime. Full catalogue: docs/SKILLS_CATALOG.md.
python -m aether.cli skills
# or, after install:
aether skills| Skill | Role |
|---|---|
kiwi-edge-architecture |
System map: field -> MQTT -> Core -> Weaver -> portals -> Ollama/Hailo on RPi 5 16GB + Hailo-10H |
security-notifications-triage |
Dependabot / GHSA / CodeQL / audit response (HITL for high-impact) |
te-mana-raraunga-sovereignty |
Te Mana Raraunga 2018 data-sovereignty constraints |
| Skill | Role |
|---|---|
error-remediation-orchestrator |
Analyze failures and propose/apply fixes (HITL) |
git-workflow |
Branch, commit, push, PR (HITL) |
ci-failure-parser |
Structure CI / Actions logs |
notification-responder |
Status updates and approval requests |
Trigger manually or via GitHub webhook remediation:
aether run "Apply kiwi-edge-architecture and Te Mana Raraunga checks to this Core PR"
aether remediate "CI failed on main with test error in user.test.ts"Note: Git operations, code writes, and high-impact security changes require human approval by default.
Some features (especially error remediation and git operations) require additional configuration:
To use the git-workflow skill effectively, you should have:
- A GitHub Personal Access Token (classic) with the following scopes:
repo(Full control of private repositories)workflow(Update GitHub Action workflows)
How to create a token:
- Go to GitHub -> Settings -> Developer settings -> Personal access tokens -> Tokens (classic)
- Generate new token
- Select the scopes listed above
- Store the token securely (e.g. in a
.envfile or password manager)
Note: Aether currently expects you to handle git authentication via your local environment (SSH keys or credential manager). Token support can be added later.
Aether can start investigation when your CI fails. Default is propose-only (read tools + plan; high-risk writes halt for HITL). Opt in to unattended writes with AETHER_WEBHOOK_AUTO_REMEDIATE=1.
- Start the webhook server
python run_webhook.py
# or
aether webhook
# or on a custom port
aether webhook --host 0.0.0.0 --port 9000- Set your webhook secret (required verification fails closed without it)
export GITHUB_WEBHOOK_SECRET=your-secure-secret
# Optional local-dev only bypass (never in production):
# export AETHER_WEBHOOK_INSECURE=1
# Optional: authorize high-risk tool actions from webhooks (default off):
# export AETHER_WEBHOOK_AUTO_REMEDIATE=1- Expose the server using ngrok or deploy to a server
ngrok http 8000- Register the webhook in GitHub
- Go to your repo -> Settings -> Webhooks -> Add webhook
- Payload URL:
https://your-url/webhook/github - Content type:
application/json - Secret: your
GITHUB_WEBHOOK_SECRETvalue - Events: Select Workflow runs and Check runs
When a CI failure is received, Aether will attempt to trigger remediation up to 4 times using exponential backoff (2s -> 4s -> 8s -> 16s).
If all retry attempts fail, the error is logged but no further automatic action is taken. You can still trigger remediation manually:
aether run "Investigate CI failure in <repo> on branch <branch>"Retry parameters are configurable via environment variables:
| Variable | Default | Description |
|---|---|---|
WEBHOOK_MAX_RETRIES |
4 |
Maximum number of retry attempts |
WEBHOOK_MIN_WAIT |
2 |
Minimum wait between retries (s) |
WEBHOOK_MAX_WAIT |
30 |
Maximum wait between retries (s) |
- Email parsing (for inbox-based remediation)
- Slack / Discord notifications
- GitHub App (for deeper integration without PAT)
Aether/
|-- aether/
| |-- webhooks/ # GitHub webhook handler (FastAPI)
| |-- tools/ # Core tools (file_writer, codebase_search, etc.)
| -- orchestrator.py # ReAct loop + skill routing
|-- skills/ # Reusable skills (add your own here)
|-- docs/ # Documentation
|-- examples/ # Usage examples
|-- run_webhook.py # Start the webhook server
|-- pyproject.toml # Packaging configuration
-- README.md
- Builder capabilities are still early (only the Project Scaffolder exists so far).
- Auto-remediation requires human approval at multiple steps for safety.
- Some advanced features (full auto-remediation, email triggers, etc.) are still in development.
We are actively working on improving generative (builder) capabilities.
Proprietary — © 2026 Coastal Alpine Tech Limited. All rights reserved. No open-source grant is implied by access to this repository; use is governed solely by LICENSE.
Built with focus on data sovereignty and edge intelligence. Coastal Alpine Tech Limited New Plymouth, Taranaki, New Zealand.

