Continuity.
Within reach.
Add persistent memory to any LLM in 3 lines of code.
Embedded.
ICE runs entirely within your application process. No external servers, database daemons, or network round-trips required.
Optimized.
Core memory operations are handled by an optimized, compiled binary kernel, bypassing Python runtime overhead for microsecond speeds.
Type-Safe.
Surgical control over cognitive defaults, budgets, and query limits via a clean SDK validated with strict Pydantic models.
Persistent Memory.
Reliable Recall.
Standard LLMs forget everything once the context window fills up. ICE provides a high-performance Virtual Memory Management (VMM) layer that runs directly inside your application for functionally infinite context.
ICE Response: "Based on our previous discussion in May, your preferred region is us-east-1."
Zero-Conf.
Embedded DuckDB.
Boots instantly with an embedded DuckDB file (`~/.ice/ice_memory.db`). No Docker, no PostgreSQL, no daemons required. Just wrap your OpenAI client and get started.
- 100% Embedded (runs completely locally)
- Optimized Binary Core (bypasses Python overhead)
- Type-Safe Enterprise API (Pydantic validated)
import iceimport asyncioimport os # 1. Set your signed license keyos.environ["ICE_LICENSE_JWT"] = "your_signed_jwt_here" async def main(): # 2. Ingest documents into memory await ice.ingest("s3://data-lake/architecture.pdf") # 3. Query with automatic memory retrieval response = await ice.query( prompt="Analyze this.", model="gpt-4o" ) print(response) asyncio.run(main())Definitive memory capabilities.
Pure, embedded memory engine for Large Language Models. Mount virtual memory directly into your application.
Embedded & Private
ICE runs entirely within your application process. No external servers, database daemons, or network round-trips required.
High Performance Core
Core memory operations are handled by an optimized, compiled binary kernel, bypassing Python runtime overhead for microsecond speeds.
Type-Safe SDK
Surgical control over defaults, budgets, and query limits via a clean SDK validated with strict Pydantic models.
Enterprise Escape Hatches
Inject your own logic before or after a query using middleware hooks for PII scrubbing, toxicity filtering, or custom audit logs.
Memory Guardian
The scheduler automatically monitors VRAM pressure and down-quantizes precision to prevent out-of-memory system crashes.
Seamless Integration.
Deploy ICE exactly how your stack demands. Compiled for maximum performance.
ICE for Python
Compiled SDK for AI engineering and LangChain.
Flexible Licensing for Every Scale
Choose the deployment model that fits your scaling needs. From individual developers to full enterprise integrations.
🧊 Community License
INDEXLESS CONTEXT ENGINE (ICE) - COMMUNITY LICENSE. Free for individual, non-commercial, and personal research purposes.
- Permitted Use: Individual, non-commercial, and personal research only
- NO Redistribution: Binaries or source code cannot be shared or sub-licensed
- NO Replication: Reverse-engineering or algorithm extraction is strictly banned
- NO Commercial Use: Integration into commercial products requires MSA license
🛡️ Enterprise Edition
High-performance regulatory, compliance, and training toolkit optimized for Data Science, Data Engineering, and production workloads.
- Atomic Provenance (ICE Audit): Cryptographically signed GPU token-traces for auditability
- Zero-Leak Training (ICE Guard): GPU memory-level sentinel blocking unauthorized data threads
- Optimized Compiler: Compile PyTorch/TensorFlow graph structures into hardware-optimized binary states
- Dedicated SLAs & 24/7/365 production architecture support
Built for Production.
If you are shipping persistent enterprise copilots or multi-tenant AI products, stop rebuilding brittle Postgres/Redis memory workarounds. Drop ICE into your stack today.