Pillar 01
Deterministic Writes
Idempotent inserts and canonical hashes prevent drift, duplication, and conflicting retrieval behavior.
Persistent Memory for AI
Memory that stays with you.
SynaptiQ gives AI products durable facts, lifecycle-aware retrieval, and session continuity. Every interaction compounds. No repeated context. No brittle prompt stitching.
10MCP tools
6Platforms supported
StructuredFact-based memory
OpenMCP protocol
Value Clarity
What it does, in one scan.
SynaptiQ is structured memory, not a keyword index. Durable facts are ranked by intent, state, confidence, and relationships.
Pillar 02
Lifecycle Logic
Facts age, supersede, expire, and recover with explicit memory state control.
Pillar 03
Intent Retrieval
Context is resolved per task with relevance orchestration, not fixed prompt stuffing.
Pillar 04
Session Continuity
Every conversation resumes with context that is concise, ranked, and production-safe.
Start risk-free. Leave anytime.
Not sure yet? Just try it. If you ever want to stop, you can delete your account and all stored data in one click from My Data. No lock-in, no hidden retention.
Developer Integrations
Integrate SynaptiQ memory into your favorite developer tools.
All paths use the same MCP endpoint and memory model, so context stays consistent across tools.
VS Code
Editor-Centric Flow
- Enable MCP support in your AI extension/workflow.
- Add SynaptiQ MCP endpoint and authenticate your workspace.
- Use memory-aware prompts during implementation, debugging, and refactoring.
GitHub Copilot
Context Across Repos
- Connect SynaptiQ as your memory backend for AI-assisted sessions.
- Store durable project decisions, conventions, and architecture constraints.
- Retrieve consistent facts while switching branches, files, or repositories.
Codex
Agent Collaboration
- Register SynaptiQ MCP in your AI tool environment.
- Persist goals, constraints, and technical decisions between sessions.
- Keep agent outputs aligned with team standards and current project state.
Why It's Different
Not all memory is created equal.
Most systems store data. SynaptiQ understands it — with structure, lifecycle, and reasoning that generic approaches cannot match.
Similarity Search
Simple Storage
LLM Extraction
SynaptiQ
Retrieval precision
Relationship awareness
Fact versioning
Explainable scoring
Lifecycle control
Audit trail
Multi-tenant isolation
Encryption at rest coming soon
Full support Partial Not supported
The Real Difference
Same conversation. Different memory.
01
“I switched to dark theme, I'm working on the payments API, and the deadline moved to March.”
Both systems receive the same message and store the full text.
02
Other systems
On recall
Returns everything that looks “close” to the query. No ranking by relevance, no awareness of what changed, no filtering. Old and current facts arrive together — your AI can't tell the difference.
High token costStale contextNo history
02
SynaptiQ
On recall
Returns only what's relevant to the current task. Facts are ranked by confidence and recency. The old deadline is automatically deprioritized. Relationships between facts are preserved.
Fewer tokensFresh contextFull audit trail
03
What your AI actually gets
Userprefersdark theme
Userworks onpayments API
Deadlinemoved toMarchupdated
Structured, versioned, and ranked — not a wall of text.
How It Works in Practice
Persistent facts become reliable decisions across teams and projects.
Continuity Flow
Each request is matched with relevant history and current context, then shaped into a clear, consistent answer.
Example: Project Status Recall
- “What's the status of the payments service?”
- Auth migration merged Tuesday. CI green on staging.
- Rate-limiter PR still in review — blocking deploy.
- Last deploy was six days ago; rollback tag saved.
- Outcome: Your AI surfaces a grounded timeline of your project instead of asking you to repeat it.
Conversion
Turn your assistant into a continuous memory system.
Add SynaptiQ to preserve durable facts, reduce context overhead, and keep every session aligned with user history.