Memory Orchestration for Production AI
The intelligent layer between your LLM and your data
Transform fragmented memory backends into a coherent, observable, compliant cognitive architecture. Using specialized Small Language Models, MOP orchestrates your existing databases—automatically routing queries, resolving conflicts, and ensuring compliance.
The Memory Crisis in Production AI
RAG systems fail not because of bad models, but because of fragmented, inconsistent, and unobservable memory infrastructure.
Fragmented Infrastructure
- • Vector DBs, graph stores, caches
- • 5+ different SDKs and APIs
- • No unified query interface
- • Manual routing logic
Inconsistency & Conflicts
- • User changes address → old data persists
- • Contradictory facts across DBs
- • No automatic conflict resolution
- • Stale data degrades accuracy
Compliance Nightmare
- • GDPR deletion across 4+ databases
- • No audit trails or provenance
- • Data residency violations
- • Manual compliance processes
One API. Multiple Backends. Intelligent Orchestration.
MOP doesn't replace your databases—it orchestrates them intelligently using specialized Small Language Models.
from mop import MemoryClient
client = MemoryClient(
api_key="mop_xxx",
namespace="user_12345"
)
# Store - MOP routes automatically
client.store(
content="User prefers dark mode",
memory_type="preference"
)
# Retrieve - MOP orchestrates across backends
context = client.retrieve(
query="What are user preferences?",
strategy="hybrid", # Vector + Graph + Cache
max_tokens=2000
)Core Capabilities
Production-ready memory orchestration powered by specialized Small Language Models
Intelligent Query Routing
Automatic strategy selection (vector/graph/hybrid) powered by specialized SLMs. Routes queries to optimal backends in <2ms.
Automated Consolidation
Detect and resolve conflicts, deduplicate memories, and extract entities—all running asynchronously in the background.
Full Observability
OpenTelemetry-powered distributed tracing. See exactly what your AI remembers, why it was retrieved, and how it was ranked.
Built-in Compliance
GDPR-compliant deletion across all backends, purpose limitation enforcement, and complete audit trails for regulatory compliance.
Multi-Backend Orchestration
Works with Pinecone, Neo4j, Redis, PostgreSQL, and more. Preserve your existing infrastructure investments.
SLM-Powered Intelligence
Specialized small language models (1-7B params) deliver 95% cost reduction vs. frontier models while maintaining accuracy.
Why Memory Orchestration Platform?
Built for production AI teams who need reliability, observability, and compliance
95% Cost Reduction
SLM-powered memory operations cost $0.0001 vs $0.05 with GPT-4. Process millions of memories economically.
Zero Vendor Lock-In
Bring your own backends. MOP orchestrates, you own the data. Switch providers without rewriting code.
Production-Ready Observability
Debug RAG failures in minutes with full tracing. Know exactly why a memory was retrieved or excluded.
Automatic Conflict Resolution
User changed address? MOP detects conflicts and resolves using temporal priority, source authority, or custom rules.
GDPR Automation
One API call deletes user data across all backends with verification. Built-in consent management and purpose limitation.
Context Engineering
Lost-in-the-Middle optimization, attention-aware positioning, and token budget management for optimal LLM performance.
Production Success Stories
Real-world applications of memory orchestration
1Customer Support AI
A SaaS company's support chatbot was giving inconsistent answers because user preferences were scattered across 3 databases. After implementing MOP, the consolidation engine automatically resolved conflicts and maintained a single source of truth. Result: 40% reduction in "I already told you that" complaints and 25% faster resolution times.
2Enterprise Knowledge Management
A financial services firm needed to answer complex multi-hop questions like "How did Q1 budget cuts affect Q3 hiring?" Their vector-only RAG system failed. MOP's hybrid routing automatically combined graph traversal (for causal chains) with vector search (for facts), improving complex query accuracy by 3x.
3Healthcare Compliance
A healthcare AI platform faced a 6-month HIPAA audit process due to fragmented patient data across vector DBs, SQL, and caches. MOP's compliance engine provided complete audit trails and one-click RTBF deletion across all backends. They passed HIPAA audit in 2 weeks.
4Prompt Injection Defense
A document Q&A system was vulnerable to indirect prompt injection attacks in uploaded PDFs. MOP's security scanner (fine-tuned RoBERTa) detected and quarantined malicious chunks before they reached the LLM. Zero security incidents in 6 months of production.
Start Orchestrating Memory in Minutes
Transform your fragmented memory infrastructure into an intelligent, observable, compliant system.
Free tier: 10,000 operations/month • No credit card required • Production-ready