Memory that belongs to your code— not your model
Long-term synthetic memory for developers and teams who don't want to be locked in.
Store architectural decisions in your project. Your connected AI tools remember them—across models, IDEs, and teams. Available for software engineering, writing, research, medical, legal, and general knowledge work via domain profiles.
After installing, ask your AI this question:
Your AI should confirm it can access log_decision() and search_decisions(), then summarize the current handoff context when native tools are mounted.
What to Expect Next
- •Handoff context: Connected AI tools can surface repo-local handoff context automatically through Continuity's synthetic memory system; others fall back to repo-local files
- •No manual re-explaining: Once the client is mounted, you can rely on Continuity to surface the relevant project context instead of pasting notes each time
- •Persistent synthetic memory: Decisions you log today remain available to your AI tomorrow, next week, and next month
Benchmarked, Not Promised
8 independent benchmarks. Every claim on this page is backed by measured results.
vs MemPalace
47 wins, 2 losses across 50 queries • 352× faster
Retrieval Quality
97.7% Precision, 98.4% Hit Rate, 0.98 MRR
RAG Faithfulness
0.96 faithfulness • 0.97 relevance • 0.94 precision
Robustness (RGB)
1.00 noise • 0.90 counter-factual • 1.00 refusal
Freshness Detection
8/8 scenarios • sigmoid decay • tag boosting
Token Scaling
13,854 vs 712,668 tokens at 5K decisions
Search Latency
8ms wake-up • 15ms search • 352× faster than MemPalace
MCP Tools
59 tools across 8 modules • 100% schema-handler consistency
Common Problems Continuity Solves
If you use AI coding assistants, you've probably experienced these frustrations
Why does Cursor keep forgetting my project structure?
Every time you start a new chat, Cursor loses context about your architecture, design patterns, and past decisions. You waste 15-30 minutes re-explaining how your codebase works.
How Continuity fixes this:
Automatically captures architectural decisions through git commits and file saves. Cursor (and other supported AI tools) can query this synthetic memory via MCP or repo-local fallbacks.
Claude loses context between sessions
AI coding assistants have temporary context windows that reset. Your project's history, conventions, and rationale disappear every time.
How Continuity fixes this:
Embedding-based retrieval keeps architectural decisions persistently accessible. 768-dimensional embeddings enable semantic search so relevant context is surfaced automatically.
I'm tired of re-explaining my codebase architecture
Onboarding new AI tools or starting fresh conversations means repeating yourself constantly about project structure, naming conventions, and design choices.
How Continuity fixes this:
A triple-detection system (git commits + file saves + AI conversations) builds a living knowledge graph of your architecture. All connected AI tools access the same synthetic memory.
My AI coding assistant doesn't remember past conversations
Each coding session starts from zero. The AI doesn't learn from previous interactions or remember solutions you've already discussed.
How Continuity fixes this:
Stores every architectural decision with relationships and timestamps. AI tools see the evolution of your codebase—not just the current state.
What is Synthetic Memory?
Context windows are temporary buffers. Synthetic memory is permanent storage for AI.
The Problem: Context Windows Reset
Every new chat starts from zero. You re-explain the same architectural decisions repeatedly.
The Solution: Synthetic Memory
Permanent storage that lives outside the context window—in your project folder.
- •Stored in .continuity/ as plain JSON
- •Works across Claude, Cursor, Copilot, Gemini
- •Local-first, commit to git, share with team
How It Changes Your Workflow
Open any AI chat and it already knows your architecture. No more context-setting.
Why context windows aren't enough
Temporary buffers. You need permanent storage.
Automated Decision Capture
5 detection layers, 19 detection points — capturing decisions automatically.
File System Detection
Monitors 14 architectural file patterns (package.json, tsconfig, Docker, CI/CD) with git-aware diff calculation
Git Hook Integration
Pre-commit hooks detect architectural changes and prompt for decision logging or add to debt tracker. Blocks commit if more than 5 decisions are unlogged.
Memory Middleware
Intercepts AI tool calls to detect 5 decision patterns: research-based, continuity-informed, iterative, config, dependency
Conversation Analysis
AI-powered extraction using Claude analyzes conversation logs to find missed decisions, surfacing only results with confidence scoring above 60%
Enhanced Prompts
Contextual reminders and accountability metrics shown to AI tools via the synthetic memory system
How Synthetic Memory Works
Log once, remember forever.
Automatic context loading
Every chat starts with your project context already loaded. No copy-paste, no manual prompts.
Works with your AI tools
Claude Code, Cursor, GitHub Copilot, Gemini CLI, and other AI coding assistants. Install once, use everywhere.
Zero-click tool setup
Auto-detects installed AI tools and configures synthetic memory automatically on first activation. No manual config files required.
Visual decision graph (Pro)
See how your architectural choices connect across a 1,500 node capacity knowledge graph. Force-directed, radial, and tree layouts with zoom and filtering.
Dream Engine
4-phase memory consolidation — gathers signals, detects duplicates and contradictions, scores staleness, and consolidates. Like sleep for your project's memory.
Decision lifecycle
Decisions can be active, draft, outdated, deprecated, or superseded. Old decisions are auto-outdated, never deleted — your full history is always preserved.
Local storage only
Everything lives in a .continuity folder in your project. No cloud, no external servers.
Plain JSON format
Your decisions are stored as readable JSON. Commit to git, grep them, edit manually—you own the data.
Domain profiles
6 domain profiles adapt Continuity's vocabulary and templates to your field — software engineering, writing, research, medical, legal, or general knowledge work.
Wiki system
Automated wiki health checks detect contradictions, stale claims, and knowledge gaps. Generate summary, comparison, timeline, and deep-dive reports from your decisions.
Anti-sycophancy guardrails
Epistemic Rigor Scoring detects when decisions lack counterarguments. Echo Chamber Detection surfaces groupthink. The only AI memory tool that fights confirmation bias.
CLI feature parity
7 CLI commands — update, archive, lint, report, source, audit, echo-chamber — give full feature access from the terminal without needing a connected AI tool.