Synapse Layer is an encrypted memory infrastructure designed to provide trust and governance for AI agents operating in real-world scenarios. It addresses the challenge of context loss in AI workflows, enabling agents to store, recall, and transfer context securely across sessions, models, and tools. The platform is built to reduce repeated context injection, which can result in wasted computational resources and increased costs for engineering teams.
Key features include AES-256-GCM encryption for all stored memories, ensuring data is protected at rest with per-operation random initialization vectors and 128-bit authentication tags. The system supports secure agent handover, allowing one agent to store information and another to recall it, with memory persisting across agent handoffs and providing a full audit trail. Synapse Layer introduces the Trust Quotient™ scoring system, which offers a per-memory confidence signal based on factors such as recency, consistency, and integrity. The platform maintains an immutable audit trail using a three-layer lifecycle model that separates live data, tombstone metadata, and administrative analytics, aligning with LGPD and GDPR requirements for audit trail preservation and data governance.
Semantic recall is supported through pgvector-powered similarity search, enabling agents to retrieve memories by meaning rather than keywords. The system allows filtering by agent, type, or time range, and each retrieval includes a Trust Quotient™ score. 0 with PKCE for authorization, HMAC-SHA256 handover signatures, PBKDF2-SHA256 for AES key derivation, tenant isolation to ensure private memory spaces, and automatic redaction of personally identifiable information from logs. Consent-gated storage and hard-delete options are provided to comply with privacy regulations.
Synapse Layer is delivered as a Python SDK, installable via pip, and integrates with environments such as Claude Desktop, MCP, Cursor IDE, LangChain, and ChatGPT via proxy. The roadmap includes features like a human approval layer, intent ledger for cryptographic proof of agent actions, and a guardian runtime for autonomous policy enforcement. The platform is intended for use by teams building AI agents, multi-agent systems, and autonomous workflows that require persistent, auditable, and trustworthy memory infrastructure. A free tier is available, with additional pricing details referenced on the site.
synapse-layer is a Frameworks & SDKs product. It focuses on providing persistent, secure memory storage for AI agents to share and retrieve information. synapse-layer is an open-source project aimed at AI developers and agent framework builders. The project is open source (Apache-2.0). synapse-layer is available on the web, the command line, and API, and it can be self-hosted.
SynapseLayer builds and maintains synapse-layer, and the product first shipped in 2026. The project is developed in the open on GitHub with 11 stars and 131 commits in the last 90 days. Across PulseGate's embedding index, synapse-layer has few near neighbours, marking it as relatively distinct. Among its 4 catalogued features are persistent memory, encrypted storage, and cross-agent support. It exposes integrations via a public API.
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