Cloud agent sandbox with persistent filesystem and on-demand compute
Hybrid search, graph indexing, and vector-symbolic memory for AI agents
Stage
MVP
Startup
Founded
Not given
2026
Based in
US
US
Pricing model
Paid
Open source
Pricing
Compute: $0.015 per GiB-hour (approximately $0.000004167 per GiB-second, billed by the second). Storage: $0.02 per GiB-month for retained incremental RootFS data and memory checkpoints. Network ingress and egress currently free. Object-store GET and PUT requests free. New users receive $5 free credi
Open source under Apache-2.0 license. WARM Cloud is in development with usage-based pricing for sync, backup and verification; details to be published at launch.
Key features
Automatic filesystem growth as storage fills
Pause compute without losing work or paying compute charges
Resume to same environment on demand
Access files while paused without waking compute
Public HTTP services with auto-resume capability
Command-line interface (s0 CLI) for agent-native workflows
Incremental checkpoints to avoid full filesystem copies
Scoped API keys and team-based access controls
On-demand file reads without downloading entire filesystem
Hybrid search combining BM25 lexical and vector scoring
Vertex graph vector index with 2.29-2.75x throughput vs hnswlib
Vector-symbolic fact memory with holographic reduced representations
AES-256-GCM encryption at rest with Argon2id key derivation
Signed audit log with Ed25519 and W3C DID identity
Secure purge that overwrites deleted data with zeros
Crash-safe append-only log with checksumming
Native Rust API with Python HTTP client and Node.js bindings
MCP server integration for editors and AI agents
WARM Cloud sync, backup and verification without server access to keys or documents
What makes it different
Persistent filesystem across pause/resume without duplicating data
Pay only for compute time used; paused sandboxes have zero compute charges
Automatic filesystem growth so agents can install and persist unlimited tools
Same API for both human users and AI agents
Runs entirely locally in your process with no network calls or telemetry
Encryption at rest built into the open-source engine itself, not an enterprise add-on
Significantly faster vector search than hnswlib with graph-indexed vertex retrieval
Signed provenance and verified audit trail using C2PA, COSE and SCITT standards
Embedded library model eliminates dependency on external services or vendor lock-in
warm-rust