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).
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
Coastal Alpine Tech products treat operational and personal data as taonga. Defaults favour local-first operation, purpose-limited collection, and Human-in-the-Loop for high-stakes actions.
| Commitment | Statement |
|---|---|
| No data sales | We do not sell personal information or customer operational data to third parties for advertising, brokerage, or unrelated commercial exploitation. |
| NZ Privacy Act 2020 | Collection, use, storage, and disclosure of personal information is designed to operate in accordance with the Privacy Act 2020 information privacy principles (including IPP awareness and IPP 3A indirect-collection notification where applicable). |
| Te Mana Raraunga | Where Māori data or community data interests arise, systems are designed to operate in accordance with Te Mana Raraunga principles (including Rangatiratanga, Whakapapa, Whanaungatanga, Kotahitanga, Manaakitanga, Kaitiakitanga) as a sovereignty and stewardship lens — not as a marketing slogan. |
| NZ AI safety | AI features follow a NZ AI safety-aligned posture: Algorithm Charter spirit (fairness, transparency, human oversight where relevant), digital.govt.nz / responsible AI guidance awareness, no silent model training on private journals without consent, and HITL for high-stakes outcomes. |
| Security | No silent exfiltration; owner-controlled credentials; least privilege; SecOps / dependency hygiene on the fleet cadence. |
| Governance | Agents inform, draft, prepare; humans advise, sign, file, send, and pay. |
| Pillar | Commitment |
|---|---|
| Privacy | Local-first / offline-capable where practical; Privacy Act 2020; Te Mana Raraunga spirit; third-party AI only when opt-in and labelled |
| Security | No silent exfil of tenant or personal data; owner-controlled keys |
| Governance | HITL for high-stakes; Te Mana Raraunga spirit; multi-region compliance maps in COMPLIANCE_REGIONS.md |
Agents inform, draft, prepare, monitor, and remind. Humans advise, sign, file, send, and pay.
Fleet policy: fivepanelhat / Kiwi Edge AI Stack · COMPLIANCE.md · COMPLIANCE_REGIONS.md · SECURITY.md
Weaver is the multi-tenant edge orchestration and local RAG mesh for high-stakes Kiwi operations helpdesks.
- Data leakage risk - Sending industrial / farm / client docs to public LLM APIs is unacceptable for many NZ operators.
- Tenant cross-contamination - Shared SaaS helpdesks mix client knowledge unless isolation is designed in.
- Rigid routing - Static ticket trees cannot adapt to multi-step operational requests.
- Cloud dependency - Rural enterprises need local RAG and agent graphs that survive offline windows.
| Built capability | What it does |
|---|---|
| Tenant-aware agents | Intake / fulfilment / resolution with isolation |
| Local LangGraph orchestration | Adaptive routing on-edge |
| Partitioned vector knowledge | Per-tenant retrieval without cross-bleed |
| White-label posture | Industry-specific deployments on the Kiwi Edge stack |
Pairs with Aether (companion skills) and Core (edge primitives) under the portfolio map.
| 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.
Coastal Alpine Tech Limited pre-seed startup, New Plymouth, Taranaki, Aotearoa New Zealand. Edge AI | Sovereign Systems | Practical Intelligence
License: Proprietary Coastal Alpine Tech Limited | See LICENSE (same Coastal Alpine proprietary terms as AquaGuard, SoilGuard, Blue-Moon, Sting-Operation, Core, and the rest of the edge stack).
White-label multi-tenant AI helpdesk scaffold with isolated knowledge retrieval and local LangGraph orchestration.
- Who: Built by Coastal Alpine Tech Limited (pre-seed), designed for high-stakes Kiwi industries (civil construction, agritech, etc.).
- What: A decentralized LangGraph orchestration layer that safely directs multi-agent tasks and handles local document vectorization.
- Where: Engineered at HQ in New Plymouth, Taranaki. Deployable strictly at the edge.
- When: Active development as of June 2026.
- Why: To support data sovereignty by keeping tenant operational data local and strictly partitioned.
- Tenant-aware multi-agent orchestration (Intake, Fulfilment, Resolution)
- Strict data isolation via SQLAlchemy and tenant-partitioned vector stores
- Local LangGraph-based state machine for adaptive routing
- Modular knowledge base with RAG support
- White-label ready for industry-specific deployments
- Full offline edge capability
- Python 3.10+
- Ollama with a local LLM Gemma 4 E4B
- PostgreSQL (optional) or in-memory mode
Weaver is Windows + Linux (and macOS) ready. Edge production target remains RPi 5 16GB + Hailo-10H. Hybridised with Coastal-Alpine-Core, Aether (companion skills / HITL), and coastal-alpine-stack.
- Prerequisites: setup.md
- Full install guide: installation.md
Linux / macOS
curl -fsSL https://raw.githubusercontent.com/fivepanelhat/Weaver/main/install.sh | bashWindows (PowerShell)
irm https://raw.githubusercontent.com/fivepanelhat/Weaver/main/install.ps1 | iexNote: If script execution is blocked:
Set-ExecutionPolicy -Scope CurrentUser RemoteSigned
git clone https://github.com/fivepanelhat/Weaver.git
cd Weaver
python bootstrap.py # Linux / macOS / Windows creates venv, installs Core + depsLinux / macOS (Bash)
git clone https://github.com/fivepanelhat/Weaver.git
cd Weaver
python3 -m venv venv
source venv/bin/activate
pip install -U pip
pip install "git+https://github.com/fivepanelhat/Coastal-Alpine-Core.git@v0.5.5"
pip install -r requirements.txt
pip install -r requirements-dev.txt
cp .env.example .envSystem packages (Debian/Ubuntu/RPi OS):
sudo apt-get update
sudo apt-get install -y python3-dev python3-venv python3-pip git build-essentialWindows (PowerShell)
git clone https://github.com/fivepanelhat/Weaver.git
cd Weaver
python -m venv venv
.\venv\Scripts\Activate.ps1
python -m pip install -U pip
pip install "git+https://github.com/fivepanelhat/Coastal-Alpine-Core.git@v0.5.5"
pip install -r requirements.txt
pip install -r requirements-dev.txt
Copy-Item .env.example .envPrerequisites: Python 3.10+ with "Add Python to PATH", Git for Windows.
Ensure Ollama is running locally and pull the target model:
ollama pull gemma4:e4b
python demo.pyTo run smoke tests validating state graph transitions:
pytestDiagrams: 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.
Weaver routes multi-tenant requests entirely on the edge node: RPi 5 16GB + Hailo-10H, local Ollama, and tenant-isolated stores. No tenant data leaves the deployment site.
%%{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 store fill:#1e1b4b,stroke:#a5b4fc,stroke-width:2px,color:#eef2ff
classDef ai fill:#3b0764,stroke:#e879f9,stroke-width:2px,color:#fdf4ff
classDef sdk fill:#0c4a6e,stroke:#38bdf8,stroke-width:2px,color:#f0f9ff
classDef host fill:#052e16,stroke:#4ade80,stroke-width:2px,color:#f0fdf4
classDef companion fill:#312e81,stroke:#c4b5fd,stroke-width:2px,color:#eef2ff
U["User / operator query"] --> ORCH["LangGraph orchestrator"]
ORCH --> IN["Intake agent<br/>auth | tenant scope"]
ORCH --> FU["Fulfilment agent<br/>RAG | tools"]
ORCH --> RE["Resolution agent<br/>response | actions"]
IN & FU & RE --> KB["Tenant-aware knowledge base"]
KB --> STORE["Isolated vector + SQL store"]
STORE --> LLM["Local LLM via Ollama<br/>Gemma 4 e4b"]
LLM --> ORCH
ORCH --> OUT["Actions & responses"]
subgraph HYBRID["Hybrid stack integration"]
CAC["Coastal-Alpine-Core<br/>SecurityGuard | Telemetry | Flywheel"]
AETH["Aether companion<br/>skills | HITL | computer use"]
CAS["coastal-alpine-stack<br/>compose / K3s"]
end
subgraph HOSTS["Dual-platform hosts"]
WIN["Windows 10/11<br/>install.ps1 | bootstrap.py"]
LIN["Linux / RPi OS<br/>install.sh | bootstrap.py"]
RPI["RPi 5 16GB + Hailo-10H<br/>production edge"]
end
ORCH --> CAC
CAC --> LLM
AETH -.-> | dev / remediate | ORCH
CAS -.-> ORCH
ORCH -.-> HOSTS
class U,OUT act
class ORCH,IN,FU,RE core
class KB,STORE store
class LLM ai
class CAC,CAS sdk
class AETH companion
class WIN,LIN,RPI host
| Layer | Components | Role |
|---|---|---|
| Orchestrator | LangGraph state machine | Deterministic multi-agent routing |
| Agents | Intake | Fulfilment |
| Knowledge | Isolated vector + SQL | No cross-tenant leakage |
| Inference | Ollama on-device | Offline-capable responses |
| SDK hybrid | Coastal-Alpine-Core | Guards, telemetry, flywheel on every path |
| Companion | Aether | Dev orchestration, HITL, computer use |
| Hosts | Windows | Linux |
Full detail: ARCHITECTURE.md
Weaver/
|-- agent_knowledge_base/ # Policy, ethics, and platform runbooks (Markdown)
|-- weaver_graph/ # Edge-friendly state graph (does not shadow PyPI langgraph)
| |-- graph.py # StateGraph compiler
| |-- llm.py # Local Ollama client bridge (LocalSovereignLLM)
| |-- orchestrator.py # build_agnostic_helpdesk graph nodes
| |-- embeddings.py # Embedding helpers
| -- ingestion.py # Document ingestion
|-- orchestrator.py # AgentOrchestrator unified entrypoint (agent + graph paths)
|-- agents.py # Intake / Fulfilment / Resolution agents
|-- knowledge_base.py # Tenant-isolated KB clients (in-memory + SQLAlchemy)
|-- database.py # TenantAwareDB connection utilities
|-- models.py # SQLAlchemy relational & vector schemas
|-- demo.py # Local simulation runner (offline-capable)
|-- bootstrap.py # Cross-platform venv + dependency bootstrap
|-- tests/ # pytest suite (orchestrator, LLM URL, demo smoke)
|-- tests_security_stress/ # Adversarial / red-team suite (prompt attacks)
|-- .env.example
|-- requirements.txt
|-- requirements-dev.txt
|-- Dockerfile
|-- ARCHITECTURE.md # System design details
-- README.md # This fileHardware
- Raspberry Pi 5 (16GB) with Hailo-10H NPU (40 TOPS AI Accelerator / AI HAT+ 2)
Software
- Orchestration: LangGraph
- Inference: Ollama + Local LLMs
- Data: SQLAlchemy + pgvector / local vector stores
- Deployment: Docker-ready, systemd compatible
These are the use cases Weaver is designed for. Weaver is at an early release (v0.1.0) and these are illustrative target scenarios, not claims of existing production deployments.
- Civil Construction Helpdesk: Route project-compliance queries across multiple subcontractors on-premise, keeping each client's data strictly isolated.
- Agritech Support Platform: Provide localized advisory services to cooperatives without exposing farm data to third-party clouds.
- White-Label Service Providers: Embed into existing SaaS platforms whose clients require sovereign, on-site data handling.
Implementation Notes:
- Install on a dedicated edge server or Raspberry Pi cluster.
- Configure tenant IDs at database and vector store level for isolation.
- Use systemd services for persistent operation and monitor via local dashboards.
- Start with
demo.pyto validate routing and isolation before production scaling.
Preliminary, illustrative figures measured informally on the reference edge node (RPi 5 16GB + Hailo-10H, Gemma 4 E4B via Ollama). Not audited production benchmarks treat as ballpark expectations and re-measure for your own workload and hardware.
- Routing latency: on the order of ~1 second per routing decision.
- Active power draw: roughly ~6W on a headless Raspberry Pi 5 16GB node.
- Storage footprint: SQL + vector stores well under 200MB for small tenants.
- ARCHITECTURE.md
- agent_knowledge_base/platform_runbook.md
- agent_knowledge_base/ethics_review_playbook.md
- CHANGELOG.md
This project is licensed under the Coastal Alpine Tech Limited License (proprietary / commercial) the same license used across the Kiwi Edge AI Stack (Weaver, AquaGuard, SoilGuard, Blue-Moon, Sting-Operation, Coastal-Alpine-Core, coastal-alpine-stack, Sovereign-Edge-Firmware, fivepanelhat).
- Full terms: LICENSE
- No open-source grant is implied by access to this repository
- Commercial use requires a written agreement with Coastal Alpine Tech Limited
Built with focus on data sovereignty and edge intelligence. Questions or collaboration? Contact Coastal Alpine Tech Limited.
Last updated: July 2026 | First public release: v0.1.0

