For CTO / CIO

Technical Documentation

Platform capabilities, system architecture, security, and integration details for Origin 137. Use this document to validate integration in your enterprise ecosystem and assess sovereignty and robustness.

Last updated: January 2026 — Origin 137

1. Overview

Origin 137 is a sovereign AI infrastructure and platform for orchestrating AI agents and automated workflows. It is designed for mid-size to large organizations, with a dual interface to align business needs with technical execution.

  • Business mode: chat interface for automation requests
  • Technical mode: full Studio (Agents, Workflows, Infrastructure)
  • Collaborative builder: assign tasks to agents; optional request queue for governance

2. Access Modes & Governance

Dual interface

  • Business mode: Simplified chat interface to express needs in natural language; submit automation requests (e.g. “Analyze invoices > €5k”); visual and audio feedback.
  • Technical / Studio mode: Full access to the creation studio (Agents, Workflows, Infrastructure); technical dashboard with monitoring and costs.

Request queue (governance)

  • Business requests appear in a dedicated “Business Requests” tab in the Studio.
  • CTO/Admin actions: Validate (convert to workflow/agent), Reject, or Process.
  • Full traceability from initial request to deployment.

3. Dashboard (Studio)

  • Real-time stats: Active agents, API requests (24h), estimated monthly cost (with optimization).
  • Activity: Interactive request volume chart; list of deployed agents with status (active / paused / draft).
  • Quick actions: Create Agent, Create Workflow, Marketplace, Documentation.

4. Agents

  • Shared presets: Save configurations (model, temperature, system prompt) from the Playground; reuse immediately when creating Agents or Workflow nodes.
  • Model choice: OpenAI (GPT-4o), Anthropic (Claude 3.5), Mistral (Large 2), Google (Gemini), Meta (Llama), sovereign models, and others (see Integrations & Models).
  • UX: Monochrome/glass premium UI; agent cards with status and metrics.

5. Workflows

Visual editor (CTO / Admin)

  • Test Run: Simulated execution inside the editor.
  • Logs console: Real-time logs, execution traces, metrics; resizable (max/min) for debugging.
  • Predictive costs: Modal at end of test with estimated run cost (input/output tokens per model).

Nodes & logic

  • Multiple triggers: Webhook, Email, Schedule.
  • AI nodes: Agents, RAG, LLM.
  • Conditional logic, loops, branching.
  • External integrations: Slack, DB, API.

Tabs: “My Workflows” and “Business Requests”. Filters: status (Active, Inactive, Draft) and search.

6. Marketplace (Coming Soon)

Template marketplace: business templates (HR, Finance, IT, Legal); cards for use cases (e.g. GDPR Audit, Balance Sheet Analyst); category filters and search. “Coming Soon” badge in UI.

7. Playground

Interactive chat to test prompts and models. Save Preset stores a configuration; presets are available across the Studio (Agents & Workflows). Model list synchronized with the platform (by provider).

8. Observability & Evaluate

Monitoring: Latency, cost, errors; detailed execution logs.

Evaluate (Coming Soon): A/B tests, model benchmarks, dataset validation.

9. Finetune (Coming Soon)

Interface to run fine-tuning jobs on proprietary data. “Coming Soon” badge.

10. Design System & UX

Deep void theme (#050505), glass effects (backdrop-blur). Geist Sans & Mono; white titles, gray text, uppercase labels. Apple-like audio feedback on key interactions; Framer Motion for transitions and modals. Collapsible sidebar; “Coming Soon” badges; Origin 137 logo.

11. Integrations & Models

Broad support for leading and sovereign models. Summary by provider:

  • OpenAI: GPT-5 (Preview), GPT-4.5 Turbo, GPT-4o, o3 Mini, o1
  • Anthropic: Claude 3.7 Opus, 3.5 Sonnet, 3.5 Haiku
  • Google: Gemini 3.0 Ultra, 2.0 Flash, 1.5 Pro
  • DeepSeek: R1, V3
  • Meta: Llama 4 400B, 3.3 70B, 3.2 90B (Vision)
  • Mistral: Large 3, Large 2, Codestral 25.01
  • Qwen: 2.5 Max, 2.5 72B, QwQ 32B
  • xAI: Grok 3, Grok 2
  • Others: Perplexity Sonar Huge, Nvidia Nemotron 4, Microsoft Phi-4

Data: File upload for RAG and context. Connectors for ERP, CRM, databases, collaboration tools.

12. Infrastructure & Security

Deployment: On-premise, private cloud, or Origin 137 Cloud.

Security: End-to-end encryption, GDPR alignment, role-based access (RBAC).

Technical Architecture (CTO / CIO)

System architecture, tech stack, and security protocols to validate integration and sovereignty.

13. System Architecture

Origin 137 uses a modular, event-driven architecture: Client (UI) is decoupled from orchestration (Core) and inference (AI Gateways).

  • Frontend (Studio & Business): Next.js 14+ (App Router), reactive state; ReactFlow for workflow graphs; code splitting, lazy loading, asset optimization.
  • Orchestration layer: Microservices for horizontal scale; async queue (e.g. Redis/BullMQ) for request peaks; DAG workflow engine (parallel execution, conditionals, error recovery).
  • AI Gateway: Unified API for any LLM; smart routing (cost/performance/availability); rate limiting and semantic caching to reduce latency and cost.

14. Security & Sovereignty

Security is built in (“Security by Design”).

Deployment

  • Sovereign SaaS: SecNumCloud-certified hosting (on request).
  • Private cloud / VPC: Isolated on your infrastructure (AWS, Azure, GCP).
  • On-premise (air-gapped): Full install on your servers; supports local open-source models (Ollama/vLLM).

Data governance

  • Privacy: No customer data used to train foundation models (configurable zero-retention).
  • Encryption: At rest AES-256 (prompts, vector stores, logs); in transit TLS 1.3 (inter-service and client-server).
  • RBAC: Admin, Developer, Business, Auditor; environment segregation (Dev/Staging/Prod).

15. AI Stack & Agentic Capabilities

Model-agnostic: proprietary (GPT-4o, Claude, Gemini via APIs), open-weight/sovereign (Mistral Large 2, Llama 3.3, DeepSeek V3, Qwen 2.5), reasoning (o1, R1), code (Codestral).

RAG: Vector stores (Pinecone, Milvus, Weaviate, PGVector); document ingestion (PDF, DOCX, CSV) with semantic chunking; hybrid search (dense + sparse/BM25).

Memory: Short-term (sliding context); long-term (persistent facts and decisions across sessions).

16. Integrability & Extensibility

API-first: workflows expose a secure REST API. Native integrations: Slack, Teams, Google Workspace, Jira, Notion, HubSpot, Salesforce. DB connectors: PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery. Custom webhooks (inbound/outbound). Optional code interpreter: Python/Node in isolated sandboxes (e.g. gVisor/Firecracker) for data processing and charts.

17. Observability & FinOps

Full traceability: log each step (input, output, latency, tokens). Predictive cost analysis before run; detailed report after. Retry with exponential backoff; real-time alerts.

18. Minimal Technical Specs (On-Premise)

For local deployment (excluding heavy LLM inference): Docker & Kubernetes (Helm charts provided). Min 4 vCPU, 16 GB RAM. SSD NVMe recommended for vector stores. Note: local LLM inference requires GPUs (e.g. NVIDIA A100/H100).

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