Operator Ready v2.0.4

Unified AI
Operator Framework

Governed inference, multi-step reasoning, and Context Heat-Scoring for enterprise-scale AI implementation. Built for developers who demand control.

jebat_operator_boot.sh
[SYSTEM] Initializing JEBAT Core...
[KERNEL] Loading cognitive modules...
[MEMORY] Mapping layers M0-M4 [OK]
[AGENT] Registering Specialist: Architect...
[AGENT] Registering Specialist: Security...
[AGENT] Registering Specialist: DevOps...
[SYSTEM] All subsystems operational.

$ jebat --status
> Runtime: Synchronized
> Memory Heat: Optimal (84%)
> Active Channels: 12

Ready for instruction.
AGENT HUB
MEMORY ENGINE
ULTRA-THINK LOOP
SECURITY CONSOLE
PORTAL BRIDGE
MCP PROTOCOL
AGENT HUB
MEMORY ENGINE
ULTRA-THINK LOOP
SECURITY CONSOLE
PORTAL BRIDGE
MCP PROTOCOL
Continuum Persistence

5-Layer Memory Model

Context preservation that scales from milliseconds to years using Context Heat-Scoring.

M0 Sensory
Hot / Buffering
M1 Episodic
Warm / Recent
M2 Semantic
Neutral / Facts
M3 Conceptual
Cool / Patterns
M4 Procedural
Cold / Long-term
Governed Operations

Enterprise Reviewability

Designed for regulated environments where Governed Inference must be visible, auditable, and restricted.

01 / Hardening

Data Boundaries

Strict VPC isolation and self-hosted deployments. Your secrets and operational data never leave your secure perimeter.

02 / Compliance

RBAC Hardening

Granular role-based access control for agent capabilities. Define exactly what your AI can read, write, and execute.

03 / Assurance

Orchestration Handoff

Complete historical record of orchestration handoffs. Every decision and agent interaction is captured for security review.

Ecosystem

Integration Stack

FastAPI
Next.js
Python
PostgreSQL
Ollama
Llama.cpp