Metadata-Version: 2.4
Name: ai-iq
Version: 5.2.0
Summary: Persistent context system for AI coding assistants
Author-email: Kobus Wentzel <kobie@pop.co.za>
License: MIT
Project-URL: Homepage, https://github.com/kobie3717/ai-iq
Project-URL: Repository, https://github.com/kobie3717/ai-iq
Project-URL: Issues, https://github.com/kobie3717/ai-iq/issues
Project-URL: Discord, https://discord.gg/Y2jCXNGgE
Keywords: ai,memory,context,sqlite,rag,semantic-search,knowledge-graph,llm,claude,coding-assistant
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Database
Classifier: Topic :: Text Processing :: Indexing
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Provides-Extra: full
Requires-Dist: numpy>=1.21.0; extra == "full"
Requires-Dist: onnxruntime>=1.14.0; extra == "full"
Requires-Dist: tokenizers>=0.13.0; extra == "full"
Requires-Dist: sqlite-vec>=0.1.0; extra == "full"
Requires-Dist: huggingface-hub>=0.14.0; extra == "full"
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: mypy>=1.0; extra == "dev"
Requires-Dist: pylint>=3.0; extra == "dev"
Dynamic: license-file

# AI-IQ

**The only lightweight SQLite memory system with belief-confidence scoring, causal graph reasoning, autonomous dream consolidation, and self-learning feedback — built for Claude Code and local AI agents.**

[![PyPI version](https://img.shields.io/pypi/v/ai-iq?color=blue)](https://pypi.org/project/ai-iq/)
[![Python 3.8+](https://img.shields.io/badge/python-3.8%2B-blue)](https://www.python.org/downloads/)
[![License MIT](https://img.shields.io/badge/license-MIT-green)](LICENSE)
[![Tests: 478](https://img.shields.io/badge/tests-478-passing)](tests/)
[![GitHub stars](https://img.shields.io/github/stars/kobie3717/ai-iq?style=social)](https://github.com/kobie3717/ai-iq)

---

## Why AI-IQ?

**Single SQLite file, zero cloud, 100% private.**
Your AI's memory lives in one portable database file. No API keys, no cloud services, no vendor lock-in. Works offline, owns your data.

**Beliefs with confidence that update from predictions and evidence.**
Track what your AI thinks it knows with confidence scores (0.01-0.99). When predictions resolve, related beliefs strengthen or weaken automatically. Bayesian-style learning from outcomes.

**Dream mode: autonomous consolidation like REM sleep for AI.**
Just like biological memory, AI-IQ consolidates during "sleep". Finds duplicates, resolves conflicts, normalizes metadata, strengthens frequently-used patterns. Memory gets smarter over time without manual curation.

**Self-learning: tracks what works, auto-tunes search weights.**
Every search logs which results you actually use. Meta-learning adjusts hybrid search fusion weights (keyword vs semantic) based on effectiveness. Search quality improves the more you use it.

---

## Comparison Table

| Feature | AI-IQ | Mem0 | Zep/Graphiti | Letta | Claude Auto Dream |
|---------|-------|------|--------------|-------|-------------------|
| **Portable single file** | ✅ SQLite | ❌ Cloud DB | ❌ Cloud DB | ✅ Filesystem | ✅ SQLite |
| **Causal beliefs with confidence** | ✅ Full system | ❌ None | ❌ None | ❌ None | ❌ None |
| **Prediction engine + resolution** | ✅ Bayesian updates | ❌ None | ❌ None | ❌ None | ❌ None |
| **Dream consolidation** | ✅ Autonomous REM-like | ❌ None | ❌ None | ❌ None | ⚠️ Shallow merge |
| **Identity layer (behavioral traits)** | ✅ Auto-discovers | ❌ None | ❌ None | ❌ None | ❌ None |
| **Narrative memory (causal chains)** | ✅ LEADS_TO/PREVENTS edges | ❌ None | ⚠️ Temporal only | ❌ None | ❌ None |
| **Meta-learning search tuning** | ✅ Feedback loop | ❌ Static | ❌ Static | ❌ Static | ❌ None |
| **Coding-specific hooks** | ✅ PostToolUse/Stop | ❌ Generic | ❌ Generic | ❌ Generic | ✅ But locked to Claude |
| **No cloud dependency** | ✅ 100% local | ❌ Cloud SaaS | ❌ Cloud SaaS | ✅ Local | ✅ Local |
| **No vendor lock-in** | ✅ Standard SQL | ❌ Proprietary API | ❌ Proprietary | ✅ Open format | ⚠️ Claude ecosystem only |
| **Knowledge graph** | ✅ Entities + relationships + facts | ✅ Strong | ✅ Very strong | ❌ None | ❌ None |
| **Hybrid search (keyword + semantic)** | ✅ RRF fusion | ✅ Yes | ✅ Yes | ⚠️ Tiered only | ❌ Keyword only |
| **Vector embeddings** | ✅ Optional (384-dim) | ✅ Required | ✅ Required | ✅ Required | ❌ None |
| **Zero dependencies** | ✅ Core works bare | ❌ Heavy stack | ❌ Heavy stack | ❌ Heavy stack | ✅ SQLite only |

**Key differentiators:**
AI-IQ is the only system that combines portable single-file storage with advanced cognitive features like belief-confidence tracking, causal reasoning, dream consolidation, and self-learning. Mem0/Zep are powerful but cloud-dependent. Letta is local but lacks causal graph. Claude Auto Dream is shallow consolidation without confidence scoring or causal edges.

---

## Quick Start

```bash
# Install from PyPI
pip install ai-iq

# Or install with semantic search (adds numpy, onnxruntime, sqlite-vec)
pip install ai-iq[full]

# Add your first memory
memory-tool add learning "Docker containers need network_mode: host for Redis access" --project FlashVault

# Search for it
memory-tool search "docker networking"
# Output:
#   [1] learning | Docker containers need network_mode: host for Redis access | FlashVault

# Create a belief with confidence
memory-tool believe "PayFast will work for South African payments" --confidence 0.8 --project FlashVault

# Make a prediction based on the belief
memory-tool predict "PayFast approval within 2 weeks" --based-on 1 --deadline 2026-04-15 --expect "Merchant account approved"

# Resolve prediction when it completes
memory-tool resolve 1 --refuted "PayFast rejected our application"
# → Belief confidence automatically drops from 0.8 to 0.6

# Run dream mode to consolidate
memory-tool dream
# Output: Consolidated 3 duplicates, resolved 1 conflict, normalized 5 dates

# Discover behavioral traits
memory-tool identity --discover
# Output: Detected traits: prefers_docker (0.85), automation_first (0.78), sqlite_lover (0.92)

# Build narrative for a project
memory-tool narrative WhatsAuction
# Output: Chronological cause-effect story with 12 connected events
```

---

## Features

### Core Memory Operations
- **Add/Update/Delete** - Standard CRUD with content deduplication
- **Hybrid Search** - RRF fusion of keyword (FTS5) + semantic (vector) + graph traversal
- **Categories** - `project`, `decision`, `preference`, `error`, `learning`, `pending`, `architecture`, `workflow`, `contact`
- **Tags & Metadata** - Auto-tagging from content keywords, manual tags, priorities (0-10)
- **Topic Keys** - Upsert-style identifiers for stable updates without duplicates
- **Expiry & Decay** - Auto-stale after 30d (pending) or 90d (general), priority decay after 60d

### Belief System (Unique to AI-IQ)
- **Confidence Scoring** - Beliefs track confidence from 0.01 to 0.99
- **Prediction Engine** - Make testable predictions with deadlines and expected outcomes
- **Bayesian Updates** - When predictions resolve (confirmed/refuted), related beliefs adjust confidence automatically
- **Confidence Propagation** - Updates flow through memory relationships via causal graph
- **Belief Queries** - Find weak/strong/conflicting beliefs, track open/expired predictions

```bash
memory-tool believe "TypeScript reduces bugs vs JavaScript" --confidence 0.75
memory-tool predict "Next rewrite will have 30% fewer runtime errors" --based-on 1 --deadline 2026-06-01
memory-tool resolve 1 --confirmed "Runtime errors down 42%"  # Belief → 0.85
memory-tool beliefs --weak                                    # Show lowest confidence beliefs
memory-tool predictions --open                                # Show active predictions
```

### Knowledge Graph
- **Entities** - `person`, `project`, `org`, `feature`, `concept`, `tool`, `service`
- **Relationships** - `knows`, `works_on`, `owns`, `depends_on`, `built_by`, `uses`, `related_to`, `PREVENTS`, `RESOLVES`, `LEADS_TO`, `REQUIRES` (causal edges)
- **Facts** - Key-value metadata on entities with history tracking
- **Spreading Activation** - Find related context by traversing relationships with decay
- **Auto-Linking** - Link memories to entities by name/keyword matching

```bash
memory-tool graph add project WhatsAuction "Real-time auction platform"
memory-tool graph add tool Redis "In-memory cache"
memory-tool graph rel WhatsAuction uses Redis "For session storage"
memory-tool graph rel WhatsAuction REQUIRES Redis "Cache must be up before app starts"
memory-tool graph fact Redis version "7.2.4"
memory-tool graph spread WhatsAuction --depth 2    # Find all related context
memory-tool graph auto-link                        # Link existing memories to entities
```

### Dream Mode (Unique to AI-IQ)
Autonomous consolidation inspired by REM sleep in biological memory:

- **Duplicate Detection** - Finds 85-95% similar memories, auto-merges with provenance
- **Reconsolidation** - Strengthens frequently-accessed patterns, weakens unused ones
- **Contradiction Detection** - Warns on >80% similar memories with negation patterns (but doesn't block)
- **Metadata Normalization** - Standardizes dates, project names, tags
- **Decay Processing** - Flags stale memories, reduces priority, expires old TODOs

```bash
memory-tool dream
# Output:
#   Consolidated 5 duplicates (kept newer, marked old as superseded)
#   Detected 2 potential contradictions (flagged for review)
#   Normalized 8 dates to ISO format
#   Expired 3 pending items past deadline
#   Strengthened 12 high-access memories (+1 priority)
#   Weakened 4 low-access memories (-1 priority)
```

### Self-Learning Feedback Loop (Unique to AI-IQ)
Meta-learning that improves search quality over time:

- **Outcome Tracking** - Every search logs which results you actually use
- **Effectiveness Scoring** - Calculates keyword vs semantic hit rates
- **Weight Tuning** - Auto-adjusts RRF fusion weights based on what works
- **Promotion/Demotion** - High-value memories get priority boost, noise gets flagged

```bash
memory-tool search-quality          # View effectiveness metrics
# Output:
#   Keyword effectiveness: 68% (102/150 searches)
#   Semantic effectiveness: 84% (126/150 searches)
#   → Semantic weight boosted from 1.0 to 1.3

memory-tool hot                     # Show most accessed memories (immune to decay)
# Output: Top 20 memories by access_count (>= 5 accesses = immune to stale)

memory-tool feedback <search_id> <used_memory_ids>  # Manual feedback logging
```

### Identity Layer (Unique to AI-IQ)
Discovers behavioral traits from memory patterns:

- **Trait Detection** - Mines decisions, errors, beliefs for tendencies (e.g., `prefers_docker`, `ships_fast`, `tests_first`)
- **Confidence Tracking** - Each trait has evidence count and confidence score
- **Evolution Tracking** - Snapshots show how traits change over time
- **Pattern Recognition** - Detects anti-patterns and conflicts

```bash
memory-tool identity --discover
# Output:
#   Detected traits:
#     prefers_docker (0.85) - 17 evidence, 2 counter
#     automation_first (0.78) - 12 evidence, 1 counter
#     sqlite_lover (0.92) - 23 evidence, 0 counter
#     ships_fast (0.45) - 5 evidence, 6 counter [CONFLICT with over_engineers]

memory-tool identity --snapshot "After WhatsAuction rewrite"
memory-tool identity --evolution prefers_docker    # Show trait changes over time
```

### Narrative Memory (Unique to AI-IQ)
Builds cause-effect stories from causal graph edges:

- **Causal Chains** - Walks `LEADS_TO`, `PREVENTS`, `RESOLVES`, `REQUIRES` edges
- **Chronological Stories** - Sorts by timestamp to show progression
- **Linked Context** - Includes related memories for full narrative
- **Deduplication** - Removes redundant events for clean stories

```bash
memory-tool narrative WhatsAuction
# Output:
#   Entity: WhatsAuction (project)
#
#   Narrative (12 events):
#     2026-02-10: Created Redis cache service
#     2026-02-11: WhatsAuction REQUIRES Redis (cache must be up first)
#     2026-02-15: Redis PREVENTS race conditions in auction bids
#     2026-02-20: Deployed with PM2 process manager
#     2026-03-01: PM2 auto-restart RESOLVES downtime issues
#     ...
```

### Integrations

**Claude Code Hooks** - Auto-captures errors, generates session snapshots, logs feedback:
```bash
# PostToolUse hook: auto-logs failed Bash commands as error memories
# Stop hook: auto-generates snapshot from git/file changes, runs decay
# Daily cron (3:17 AM): decay + gc + backup + meta-learning tuning
```

**OpenClaw Bridge** - Bidirectional sync with OpenClaw's file-based memory:
```bash
memory-tool sync          # Two-way sync
memory-tool sync-to       # AI-IQ → OpenClaw
memory-tool sync-from     # OpenClaw → AI-IQ
```

**Session Tracking** - Structured workflows with steps and outcomes:
```bash
memory-tool run start "Fix authentication bug" --agent claude --project MyApp
memory-tool run step 1 "Identified issue in JWT validation"
memory-tool run complete 1 "Fixed, all tests passing"
memory-tool run list --status completed
```

---

## Architecture

**Inspired by biological memory principles:**
- **Hippocampus → Neocortex** - Short-term memories (recent sessions) consolidate into long-term via dream mode
- **REM Sleep Consolidation** - Dream mode strengthens important patterns, prunes noise
- **Spreading Activation** - Graph traversal mimics how human memory retrieves related concepts
- **Confidence Updates** - Bayesian-style learning from prediction outcomes

**Database schema (SQLite 3.37+):**
- `memories` - Core storage with FTS5 index + vector embeddings (384-dim all-MiniLM-L6-v2)
- `memory_relations` - Bidirectional links between memories
- `graph_entities` - Knowledge graph nodes (people, projects, tools, concepts)
- `graph_relationships` - Causal edges (PREVENTS, RESOLVES, LEADS_TO, REQUIRES) + semantic edges (uses, depends_on, etc.)
- `graph_facts` - Entity metadata with history tracking
- `beliefs` - Confidence-scored statements with Bayesian update tracking
- `predictions` - Testable hypotheses with deadlines and resolution tracking
- `identity_traits` - Behavioral patterns with evidence counts
- `runs` - Workflow/session tracking with steps and timing
- `search_feedback` - Meta-learning data for weight tuning

**Hybrid Search (RRF fusion with k=60):**
1. Keyword search via FTS5 (fast, exact matches)
2. Semantic search via sqlite-vec embeddings (conceptual similarity)
3. Graph traversal via spreading activation (relationship-based)
4. Recency/confidence/access bonuses
5. Meta-learned weights adjust fusion based on effectiveness

See [ARCHITECTURE.md](ARCHITECTURE.md) for implementation details.

---

## Claude Code Integration

### 1. Install AI-IQ
```bash
pip install ai-iq[full]
```

### 2. Set up hooks in `~/.claude/settings.json`
```json
{
  "hooks": {
    "PostToolUse": "~/.claude/projects/-root/memory/error-hook.sh",
    "Stop": "~/.claude/projects/-root/memory/session-hook.sh"
  }
}
```

### 3. Add CLAUDE.md to your project root
See [CLAUDE.md template](CLAUDE.md) - tells Claude to auto-load MEMORY.md each session and use `memory-tool` commands.

### 4. Set up daily maintenance cron
```bash
17 3 * * * ~/.claude/projects/-root/memory/daily-maintenance.sh >> ~/.claude/memory/cron.log 2>&1
```

**Automation flow:**
- **Session start** - MEMORY.md auto-loads (last session + pending items)
- **During work** - PostToolUse hook auto-captures failed commands as error memories
- **Session end** - Stop hook generates snapshot from git/file changes, runs decay, exports MEMORY.md
- **Daily 3:17 AM** - Dream consolidation, meta-learning tuning, garbage collection, backup

See [INSTALLATION.md](INSTALLATION.md) for detailed setup.

---

## Full Command Reference

### Core Operations
| Command | Description |
|---------|-------------|
| `memory-tool add <category> "<content>" [options]` | Create memory with optional --project, --tags, --priority, --expires, --key |
| `memory-tool update <id> "<new content>"` | Update memory (auto re-embeds for semantic search) |
| `memory-tool delete <id>` | Soft delete (recoverable) |
| `memory-tool get <id>` | Full detail view with relationships |
| `memory-tool list [--project/--category/--tag/--stale/--expired]` | Filter and list memories |

### Search & Discovery
| Command | Description |
|---------|-------------|
| `memory-tool search "<query>" [--full/--semantic/--keyword]` | Hybrid search (default), verbose (--full), mode-specific |
| `memory-tool conflicts` | Find 50-85% similar memories (potential duplicates) |
| `memory-tool merge <id1> <id2>` | Merge similar memories (keeps newer) |
| `memory-tool supersede <old> <new>` | Mark old as superseded by new |
| `memory-tool pending` | Show TODO items |
| `memory-tool hot` | Most accessed memories (access_count >= 5 = immune to decay) |
| `memory-tool next` | Smart suggestions: what needs attention now |

### Beliefs & Predictions
| Command | Description |
|---------|-------------|
| `memory-tool believe "<statement>" --confidence 0.7` | Create belief with confidence score |
| `memory-tool predict "<prediction>" --based-on <id> --deadline YYYY-MM-DD` | Make testable prediction |
| `memory-tool resolve <pred_id> --confirmed/--refuted "<outcome>"` | Resolve prediction (auto-updates belief confidence) |
| `memory-tool beliefs [--weak/--strong/--conflicts]` | List beliefs by confidence |
| `memory-tool predictions [--open/--confirmed/--refuted/--expired]` | Filter predictions by status |

### Knowledge Graph
| Command | Description |
|---------|-------------|
| `memory-tool graph add <type> <name> [summary]` | Create entity (person/project/org/feature/concept/tool/service) |
| `memory-tool graph rel <from> <rel_type> <to> [note]` | Add relationship (uses/depends_on/PREVENTS/RESOLVES/LEADS_TO/REQUIRES) |
| `memory-tool graph fact <entity> <key> <value>` | Set entity metadata (tracks history) |
| `memory-tool graph get <name>` | Entity details with facts + relationships + linked memories |
| `memory-tool graph spread <name> [depth]` | Spreading activation (find related context) |
| `memory-tool graph auto-link` | Auto-link all memories to entities by keyword matching |

### Identity & Narrative
| Command | Description |
|---------|-------------|
| `memory-tool identity --discover` | Detect behavioral traits from memory patterns |
| `memory-tool identity --snapshot "<desc>"` | Save current trait snapshot |
| `memory-tool identity --evolution <trait>` | Show how trait changed over time |
| `memory-tool narrative <entity>` | Build cause-effect story from causal graph edges |

### Meta-Learning & Feedback
| Command | Description |
|---------|-------------|
| `memory-tool search-quality` | View keyword/semantic effectiveness metrics |
| `memory-tool feedback <search_id> <used_ids>` | Manual feedback logging (which results were useful) |
| `memory-tool tune-weights` | Re-calculate RRF fusion weights from feedback data |

### Session Management
| Command | Description |
|---------|-------------|
| `memory-tool snapshot "<summary>" [--project X]` | Manual session snapshot |
| `memory-tool auto-snapshot` | Auto-detect changes from git/filesystem |
| `memory-tool run start "<task>" --agent <name> --project <name>` | Start tracked workflow |
| `memory-tool run step <id> "<description>"` | Add step to active run |
| `memory-tool run complete/fail/cancel <id> "<outcome>"` | Finish run |
| `memory-tool run list [--status running/completed/failed]` | List runs with filters |

### Maintenance
| Command | Description |
|---------|-------------|
| `memory-tool dream` | Consolidate duplicates, resolve conflicts, normalize metadata, run decay |
| `memory-tool decay` | Flag stale memories, reduce priorities, expire old TODOs |
| `memory-tool stale` | Review stale memories |
| `memory-tool gc [days]` | Garbage collect inactive memories (default: 180 days) |
| `memory-tool reindex` | Rebuild vector embeddings for all memories |
| `memory-tool backup` | Manual backup to ~/.claude/backups/ |
| `memory-tool restore <file>` | Restore from backup |
| `memory-tool stats` | Full statistics (memories + vectors + graph + beliefs + runs) |

### Cross-Tool Sync
| Command | Description |
|---------|-------------|
| `memory-tool sync` | Bidirectional sync with OpenClaw |
| `memory-tool sync-to` | Export to OpenClaw workspace format |
| `memory-tool sync-from` | Import from OpenClaw workspace |

---

## Real-World Usage

**Production stats from 6 months of daily use:**
- 220+ active memories across 7 projects (WhatsAuction, FlashVault, AI-IQ, AutoClaw, Baileys)
- 32 entities, 45 relationships in knowledge graph
- 109 vector embeddings for semantic search
- 18 beliefs with confidence tracking
- 12 predictions resolved (9 confirmed, 3 refuted)
- 24 identity traits discovered
- 697 duplicates consolidated via dream mode
- Zero data loss, zero corruption

**Common workflows:**

```bash
# Debugging session with run tracking
memory-tool run start "Fix Redis connection timeout" --agent claude --project FlashVault
memory-tool run step 1 "Checked Redis logs: no errors"
memory-tool run step 1 "Found network_mode mismatch in docker-compose.yml"
memory-tool add learning "Docker containers need network_mode: host for Redis access" --project FlashVault
memory-tool run complete 1 "Fixed network_mode, Redis connects successfully"

# Architecture decision with belief tracking
memory-tool add decision "Use SQLite instead of PostgreSQL for Overwatch feature" --project FlashVault --priority 8
memory-tool believe "SQLite performs well enough for <10K users" --confidence 0.7 --project FlashVault
memory-tool predict "No performance issues with SQLite in production" --based-on 1 --deadline 2026-06-01

# Weekly consolidation
memory-tool dream
memory-tool conflicts              # Review suggested merges
memory-tool merge 42 58           # Merge duplicates
memory-tool identity --discover   # Update behavioral profile
memory-tool search-quality        # Check if search is improving
```

---

## Requirements

**Core (zero dependencies):**
- Python 3.8+
- SQLite 3.37+ (with FTS5 support)

**Optional (for semantic search):**
```bash
pip install ai-iq[full]
```
Adds: `numpy`, `onnxruntime`, `tokenizers`, `sqlite-vec`, `huggingface-hub`
Downloads all-MiniLM-L6-v2 model (~90MB) on first use.

**Development:**
```bash
pip install ai-iq[dev]
```
Adds: `pytest`, `mypy`, `pylint`

---

## Project Status

**Active development.** Stable for production use. Used daily for multi-project AI-assisted development.

**Versioning:** Follows semver. Currently v5.0.0 (major upgrade with beliefs, identity, narrative, meta-learning).

**Tests:** 478 tests across 24 test files, 100% coverage on core modules.

**Roadmap:**
- [ ] Hierarchical memory (workspace → project → file scopes)
- [ ] Multi-modal embeddings (code, images, audio)
- [ ] Distributed sync (multi-machine workspaces)
- [ ] Web UI for memory visualization
- [ ] LangChain/LlamaIndex adapters

---

## Contributing

Issues and pull requests welcome!

**Development setup:**
```bash
git clone https://github.com/kobie3717/ai-iq.git
cd ai-iq
pip install -e .[dev,full]
pytest                          # Run tests
mypy memory_tool/              # Type checking
pylint memory_tool/            # Linting
```

See [ARCHITECTURE.md](ARCHITECTURE.md) for implementation details.

---

## Credits

Inspired by research on 25+ open-source memory systems:

- **Engram** - Temporal decay and graph-based memory
- **LedgerMind** - Sequential memory with branching
- **Vestige** - Semantic clustering and decay
- **OpenClaw** - Multi-tool workspace sync
- **Sediment** - Layered memory architecture
- **Mem0** - Managed memory-as-a-service
- **Zep/Graphiti** - Temporal knowledge graphs
- **Letta** - OS-inspired tiered memory

Built for real-world use with Claude Code in production environments.

---

## License

MIT License - see [LICENSE](LICENSE)

---

## Community

- **GitHub:** [github.com/kobie3717/ai-iq](https://github.com/kobie3717/ai-iq)
- **Discord:** [https://discord.gg/Y2jCXNGgE](https://discord.gg/Y2jCXNGgE)
- **PyPI:** [pypi.org/project/ai-iq](https://pypi.org/project/ai-iq/)

---

**Give your AI the context it needs, when it needs it.**
