Platform
RCT Ecosystem 2026.03 Snapshot
Constitutional AI Operating System — 10-layer architecture, a 41-algorithm framework, 4,849 passed tests, and a 99.98% uptime SLA.
Platform Summary
Short Answer: What This Platform Does
RCT Ecosystem acts as an operating system for enterprise AI by handling verification, memory, routing, governance, and deployment discipline so AI systems can be more auditable, safer, and easier to operate at scale.
Why Buyers Evaluate This Page
- Explains the architecture layer by layer.
- Shows explicit performance and validation numbers.
- Connects protocols, memory, routing, and compliance in one system.
10-Layer Constitutional AI Architecture
From hardware abstraction to enterprise hardening — complete AI operating system stack
Enterprise Hardening
2026.03 SnapshotJWT RS256, RBAC, CircuitBreaker - Security-first architecture with comprehensive access control and fault tolerance.
Universal Adapter
Integration ReadySeamless integration with external systems, APIs, and third-party services through standardized protocols.
Regional Language Adapter
8 MarketsSupport for 8 markets with localized LLM models and compliance frameworks (PDPA, APPI, PIPA, PIPL).
FloatingAI
Conversational AIL3 API microservice for conversational AI with real-time context awareness and knowledge base integration.
JITNA Protocol
RFC-001Just-In-Time Natural Action language for precise intent specification and validation.
SignedAI
0.3% benchmarkMulti-LLM consensus engine with digital signatures for verifiable AI outputs.
RCTDB
8D Memory8-dimensional universal memory schema with Delta Engine compression and quantum-resistant encryption.
Algorithm Kernel
41 Algos41-algorithm framework across 9 tiers from basic operations to self-evolving systems.
Kernel Services
Runtime CoreCore infrastructure services including memory management, context switching, and event processing.
OS Primitives
FoundationFoundation layer providing process isolation, resource allocation, and hardware abstraction.
Architecture Stats
Legend
Architecture
10-Layer System Architecture
From cognitive kernel to enterprise hardening — every layer formally specified with 6 Kernel RFCs.
Enterprise Hardening
Security (JWT RS256, RBAC), Validation, Performance, Resilience, LLM Intelligence
Control Plane
JITNA Wire Schema, ED25519 Signed Execution, Deterministic Replay Engine
Regional Language Adapter
8 language-region pairs (JP, KR, CN, TW, TH, VN, ID, US) with compliance
Universal Adapters
Slack Gateway, Notion Auto-Sync, Home Assistant, Rotki, Blender, Terraform, n8n + more
JITNA Protocol
RFC-001 v2.0 — AI-to-AI communication with PROPOSE→COUNTER→ACCEPT/REJECT
SignedAI
Multi-LLM attestation: GPT-4 + Claude 3.5 + Gemini Pro consensus
RCTDB v2.0
8-dimensional universal memory: Registry, Vault, and Governance zones
41 Production Algorithms
Tier 1-3: Foundation (15) | Tier 4-6: Intelligence (14) | Tier 7-9: Consciousness (12)
OS Primitives
Process Model, Scheduler, IPC, Syscall Interface, Fault Isolation — 6 RFCs
7 Genome System
Architect, ARTENT, JITNA, Codex, SignedAI, Vault-1010, RCT-7 + SHA256 proof
SignedAI
Multi-LLM attestation achieving 0.3% hallucination rate (vs industry 12-15%). GPT-4 + Claude 3.5 + Gemini Pro consensus verification with ED25519 cryptographic signatures.
- 0.3% hallucination rate (95% better than industry)
- ED25519 cryptographic output signing (RFC 8032)
- Multi-model consensus: GPT-4, Claude 3.5, Gemini Pro
- Deterministic replay with SHA-256 checkpoints
{
"output": "Analysis complete",
"signature": {
"tier": "S-8",
"confidence": 0.961,
"consensus": [4, 6, 8],
"hash": "0x7f3a...b2c1"
},
"verified": true,
"timestamp": "2026-03-04T12:00:00Z"
}Vector
Semantic search
Graph
Relationships
SQL
Structured data
Unified Query Interface
RCTDB v2.0
8-dimensional universal memory schema with infinite scalability. Three zones: Registry (Identity & Discovery), Vault (Infinite Storage), and Governance (Rules & Evolution).
- 8-dimensional universal schema
- 74% lossless context compression
- 3-zone architecture (Registry, Vault, Governance)
- pgvector HNSW + Apache AGE graph + async batch ops
Specialist Studio
Create domain-specific AI modules with specialized knowledge and compliance requirements.
Legal
Contract analysis, compliance checking, case research
Medical
Diagnostic support, research synthesis, patient data
Finance
Risk assessment, market analysis, regulatory compliance
Infrastructure
Production-Ready Deployment
v2.5.0 Phase 5-11: Docker, Kubernetes, API Gateway, and monitoring stack.
Docker Compose
31+ services unified deployment with health checks (736 lines)
Kubernetes
57 resources: HPA, PDB, NetworkPolicy, ArgoCD GitOps, Backup CronJobs
API Gateway
Bun + Hono TypeScript: JWT RS256 auth, RBAC, rate limiting, 10 routes
Monitoring
Prometheus scrape configs + Grafana dashboards (health, RPS, latency, errors)
Test Infrastructure
Locust + k6 load testing, OWASP security, Chaos (9 scenarios), E2E (7 flows)
Documentation
OpenAPI 3.1.0 (14 endpoints), C4 Architecture, Deployment Guide, Runbooks
2026.03 Snapshot — Enterprise Integration Suite
Slack Gateway & Notion Auto-Sync
Real-time AI collaboration through 2-Chat Architecture and automated knowledge synchronization.
Slack Gateway
2-Chat Architecture — Research channels powered by Analysearch Intent, Execution channels powered by Kernel 9 Tiers with JITNA Protocol.
- Dynamic message routing
- Block Kit UI (Consensus, Progress, Approval)
- Slash commands: /rct new, list, status
- Real-time progress tracking
Notion Auto-Sync
Automated documentation synchronization — 9 Notion databases, bilingual TH/EN, version tracking, and deployment status dashboards.
- 9-database wiki architecture
- Bilingual TH/EN auto-translation
- Version tracking with CHANGELOG sync
- Deploy status dashboard v3.0
Regional Language Adapter
Multi-language routing with compliance frameworks. LanguageDetector (Unicode script analysis), RegionalModelRouter (4-level resolution + LRU cache), and 6 pilot tenants.
| Language | Region | Default Model | Compliance |
|---|---|---|---|
| English | US | Claude Opus 4.6 | — |
| ไทย | TH | DeepSeek V3.2 | PDPA |
| ญี่ปุ่น | JP | Claude 3.5 Sonnet | APPI |
| เกาหลี | KR | GPT-4 Turbo | PIPA |
| Chinese (Simplified) | CN | Qwen 2.5 72B | PIPL |
| Chinese (Traditional) | TW | Qwen 2.5 72B | — |
| เวียดนาม | VN | Qwen 2.5 7B | — |
| อินโดนีเซีย | ID | Qwen 2.5 7B | — |
Performance
Verified Benchmarks
| Metric | 2026.03 Snapshot | Industry Avg | Improvement |
|---|---|---|---|
| Hallucination Rate | 0.3% benchmark | 12-15% | Benchmark evidence |
| Context Compression | 74% lossless | 30-40% | 185% better |
| Response Latency | 0.07-1.5s | 2-5s | 70% faster |
| Availability Target | 99.98% SLA | 99.5% | Operational target |
| Test Coverage | 4849 verified | 70-80% | Current snapshot |
| Cost Efficiency | 3.74x reduction | 1x baseline | 274% savings |
FAQ
Key Questions Technical Evaluators Ask
What is the RCT Labs platform?
RCT Ecosystem is a constitutional AI operating system that combines a 10-layer architecture, multi-LLM verification, persistent memory, intelligent routing, governance, and compliance-aware deployment into one platform.
Who is the platform designed for?
It is designed for organizations that need lower hallucination risk, stronger auditability, persistent context across workflows, and enterprise AI deployments in regulated or multilingual environments.
How is it different from a typical LLM integration stack?
RCT goes beyond orchestration by combining verification, deterministic routing, memory architecture, protocol layers, and signed outputs so AI behavior can be explained, audited, and deployed safely at enterprise scale.
Related Resources
Continue Through the Related System Pages
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Start building with RCT Ecosystem v2.5.0. Full documentation, 14 OpenAPI endpoints, and enterprise support.