Capability provisioning hall / 16 blueprints
Start with the outcome you need. Every blueprint carries its architecture, services, planning footprint, deployment decisions, and required dependencies.
Deploy the owned AI substrate once, then add capabilities as modules.
A repeatable private platform foundation with container lifecycle, pod networking, ingress, persistence, boot protection, deployment automation, and a consistent operating model.
One private workspace for models, knowledge, tools, search, voice and collaborative AI.
A single authenticated AI workspace that can talk to multiple models and attach organizational knowledge, tools and controlled external services.
Unlocks “Private AI + Model Freedom”: Users get one interface while builders can change providers underneath it without changing the experience.
One governed API in front of cloud and local AI providers.
A consistent OpenAI-style API with centralized authorization, model abstraction, routing, cost controls and provider resilience.
Unlocks “Private AI + Model Freedom”: Users get one interface while builders can change providers underneath it without changing the experience.
Turn private documents and structured data into grounded, searchable AI context.
A private retrieval layer combining structured relational data, vector similarity search, full-text search and chat UI knowledge workflows.
Unlocks “Institutional Memory”: The AI can retrieve documents, recall prior work and trace relationships and provenance.
Let agents recall relevant history across sessions instead of starting over.
A semantic session-history layer that can be searched through MCP or HTTP and injected into active work.
Unlocks “Institutional Memory”: The AI can retrieve documents, recall prior work and trace relationships and provenance.
Connect people, sessions, messages, tools, commits and artifacts into a queryable history of work.
A graph representation of project activity that agents can query to answer who/what/when/how questions and generate narratives.
Unlocks “Institutional Memory”: The AI can retrieve documents, recall prior work and trace relationships and provenance.
Give AI modular tools and data connectors without rebuilding the model layer.
A standardized capability layer where MCP-capable clients can discover tools, resources and prompts and invoke permitted actions.
Unlocks “Controlled Agency”: Agents can act across systems while risky writes and commands remain human-gated.
Resume and operate coding agents remotely while humans retain approval over consequential actions.
A remote coding experience exposed through chat/Telegram with explicit approve-or-deny checkpoints for writes and shell operations.
Unlocks “Controlled Agency”: Agents can act across systems while risky writes and commands remain human-gated.
Search, crawl, extract, structure and retain web intelligence as reusable organizational knowledge.
A private research pipeline that discovers sources, crawls approved targets, structures findings and stores them for semantic/graph retrieval.
Unlocks “Research-to-Knowledge”: Discovery becomes a retained, structured research corpus instead of disappearing after one chat.
Add local/private and premium cloud speech plus richer multimodal interaction to the same AI workspace.
A hybrid experience layer that can choose local or cloud speech and plug image/voice capabilities into the same AI interface.
Unlocks “Multi-Channel Intelligence”: The intelligence layer is reusable across interfaces rather than tied to one chat surface.
Expose private AI services through centralized identity and outbound-only tunnel ingress.
A centralized edge with SSO, access policy, reverse-proxy controls and a tunnel architecture that does not require a publicly routable origin service port.
Unlocks “Zero-Trust AI Service”: Remote AI access without exposing origin service ports, with centralized authentication and behavioral remediation.
Detect abusive behavior at the edge, visualize it, scan the software supply chain and optionally enforce runtime policy in the kernel.
Layered security using behavioral detection, application remediation, deception, vulnerability scanning and optional eBPF runtime observability/enforcement.
Unlocks “Zero-Trust AI Service”: Remote AI access without exposing origin service ports, with centralized authentication and behavioral remediation.
Bring metrics, logs, traces and platform health into one operating picture.
A unified observability stack for infrastructure and applications with alerting, correlation and long-retention metrics.
Unlocks “AI SRE Foundation”: Agents can reason over the same telemetry and history humans use for diagnosis.
Turn live operational data into images, summaries and delivery-ready reports.
A render-and-deliver layer that converts selected dashboard panels and platform data into consumable reports and alerts.
Unlocks “Managed AI Business”: A provider can sell governed AI access to teams and customers and track usage and cost centrally.
Operate governed AI capabilities for multiple users, teams or customers from one controlled platform.
A multi-user AI service layer with centralized identity, model access, usage controls, shared knowledge and multiple delivery surfaces.
Unlocks “Managed AI Business”: A provider can sell governed AI access to teams and customers and track usage and cost centrally.
Use the same AI platform as a backend for live geospatial, charting and mobile experiences.
Reusable platform APIs can power real-time visual applications and universal mobile clients without rebuilding identity, AI, knowledge or observability.
Unlocks “Multi-Channel Intelligence”: The intelligence layer is reusable across interfaces rather than tied to one chat surface.
