What This Is
LangChain is enterprise AI plumbing — chains, agents, tools, memory.
SLOS wraps it. Six drop-in hook classes (~560 lines) transform any LangChain deployment into a sovereign, floor-guaranteed, court-admissible AI system.
No rip-and-replace. One sprint to certification.
The Layer Stack
SOSTLE Castle → outer defence, all LLM calls
↓
TRIME Vault → GID token strip on ingest
↓
LangChain → chains / agents / tools (unchanged)
↓
TREDNALS → γ₁ floor check on every response
↓
Model-Radar → organism3 drift signal async
↓
PEMCLAU → 2-hop GraphRAG (not flat cosine)
↓
Sovereign answer · auditable · floor-guaranteed
vs LangChain Native
No sovereign IDs
No quality floor
No injection gate
No degradation monitor
No provenance graph
SLOS: all five solved
Sorry
OPEN Hook classes not yet packaged as pip module
OPEN SLOS certification dashboard not yet built
OPEN FalkorDB backend not yet integrated
CLOSED All 6 hook architectures designed + documented
6 Drop-In Hook Classes
Total: ~560 lines · One pip install · Zero LangChain modification
~50
SovereignDocumentLoader
Extends BaseDocumentLoader. Strips GID tokens before chain sees document. Contamination structurally impossible.
~80
TredNALSCallbackHandler
Extends BaseCallbackHandler. on_llm_end() checks γ₁ floor. WPA < 84.808% → raises SovereignFloorViolation → retry or escalate.
~100
SOSTLEToolWrapper
Extends BaseTool. Every tool call passes through castle gate. Prompt injection via tool output caught before chain sees it.
~120
LOCOLangChainLLM
Extends BaseLLM. TC^k latent loop wrapper. Model thinks privately, returns converged answer only. No raw CoT leakage.
~150
PEMCLAURetriever
Extends BaseRetriever. 2-hop PEMCLAU GraphRAG via Qdrant. Returns causally connected nodes (theorem_dependency, phase_coherence, temporal_proximity, crew_provenance).
~60
ModelRadarCallbackHandler
Extends BaseCallbackHandler (async). Runs organism3 signal check every 10th LLM call. CHAOTIC/FAST_MONOTONE/SLOW_MONOTONE signals. Alert on drift.
Integration
pip install eose-sovereign-langchain
Drop-in: swap your loader, add two callbacks, wrap your LLM, swap your retriever. One sprint. Done.
7-Gate SLOS Certification
Pass all 7 → EOSE Sovereign Certified.
G1
GID token stripping active
SovereignDocumentLoader
G2
Zero exfiltration in 24h
TRIME Vault
G3
All responses WPA ≥ 84.808%
TredNALSCallbackHandler
G4
Zero tool injection in 24h
SOSTLEToolWrapper
G5
TC^k latent loop active
LOCOLangChainLLM
G6
No degradation signal in 24h
ModelRadarCallbackHandler
G7
Provenance chain intact
PEMCLAURetriever
Commercial Tiers
New deployment → EOSE SRE RAG Platform (full V12 stack)
Existing LangChain → pip install eose-sovereign-langchain → one sprint → certified
Volume play Every enterprise running LangChain is a prospect. No rip-and-replace.
DCJ-141 — Sovereign LangChain Ops Standard
Claim: A 7-gate certification framework for LangChain-based enterprise AI that adds sovereignty, quality floor, and provenance via ~560 lines of drop-in hook classes.
BigLaw: Existing LangChain RAG stack certified sovereign in one sprint. Privilege protection by architecture. No rip-and-replace.
Moat vs LangChain Native
TRIME — No GID token concept in LangChain. HARD.
TREDNALS — No γ₁ rejection floor anywhere. HARD.
PEMCLAU — Flat vector search only. 4-edge-type graph = ours. HARD.
SOSTLE — No castle-layer tool gate. MEDIUM.
LOCO — CoT not latent. TC^k is ours. MEDIUM.
Model-Radar — No 13-engine corpus anywhere. HARD.
Related TRBs / ARBs
TRB-SOVEREIGN-LANGCHAIN-OPS-001
TRB-SOVEREIGN-AI-ENTRY-001
ARB1-SOVEREIGN-AI-ENTRY-001
ARB1-TRIME-001 · ARB1-TREDNALS-001
LABR-SRE-RAG-001 (Day 87)
ELI5 — What Did We Build?
You know how LangChain is like plumbing — it connects your AI to your documents, your tools, your memory?
Right now that plumbing has no filter. Anything that flows through it can leak.
We built the filter system.
TRIME strips sensitive IDs before they hit the AI.
TREDNALS rejects any answer below a mathematically proven floor.
SOSTLE guards every door the AI can open.
LOCO makes the AI think privately before answering.
Model-Radar watches the AI 24/7 for silent drift.
PEMCLAU gives it a real memory with relationships.
The plumbing still works. We just made it sovereign.
No one else has done this for LangChain. That's the moat.
The Entry Floor
BigLaw. Clinical AI. Government inference.
All need to answer three questions before AI can touch privileged work:
1. Can it contaminate my data? TRIME: No.
2. Is it degrading silently? TREDNALS + Radar: No.
3. Can it be injected? SOSTLE + LOCO: No.
No other vendor answers all three simultaneously. We do.