kanoniv-mem0 0.1.0

Identity resolution for mem0. Same person, different IDs = unified memory.

kanoniv-mem0

Identity resolution for mem0. Same person, different IDs = unified memory.

The Problem

mem0 stores memories keyed by user_id. If two agents use different identifiers for the same person, mem0 treats them as separate users:

from mem0 import Memory
m = Memory()

m.add("Prefers annual billing", user_id="[e-mail]")
m.add("Needs 50 seat quote", user_id="[e-mail]")

m.search("billing", user_id="[e-mail]")
# Only finds 1 memory. The other is invisible.

Bill and William Smith are the same person. But mem0 doesn't know that.

The Fix

from kanoniv_mem0 import KanonivMemory
m = KanonivMemory(kanoniv_api_key="kn_live_...")

m.add("Prefers annual billing", user_id="[e-mail]")
m.add("Needs 50 seat quote", user_id="[e-mail]")

m.search("billing", user_id="[e-mail]")
# Finds BOTH memories. Same canonical entity.

KanonivMemory resolves every user_id to a canonical entity via Kanoniv's identity graph before mem0 stores or retrieves anything. Different IDs that belong to the same person get the same entity_id. Memories unify automatically.

Install

pip install kanoniv-mem0

Quick Start

from kanoniv_mem0 import KanonivMemory

# Drop-in replacement for mem0's Memory
m = KanonivMemory(kanoniv_api_key="kn_live_...")

# Agent A - support agent
m.add(
    "I'm Bill, VP of Engineering at Acme. Switch us to annual billing.",
    user_id="[e-mail]",
)

# Agent B - sales agent (different email, same person)
m.add(
    "This is William Smith. Quote me for 50 Enterprise seats.",
    user_id="[e-mail]",
)

# Agent C - searches by either ID, gets everything
results = m.search("billing", user_id="[e-mail]")
# Returns memories from BOTH agents

results = m.get_all(user_id="[e-mail]")
# Returns ALL memories for this person, regardless of which ID was used

How It Works

Your code                KanonivMemory              mem0
   |                         |                        |
   | add(user_id="bill@..")  |                        |
   |------------------------>|                        |
   |                         | resolve("bill@..")     |
   |                         |-----> Kanoniv API      |
   |                         |<----- entity_id: ENT_7f|
   |                         |                        |
   |                         | add(user_id="ENT_7f")  |
   |                         |----------------------->|
   |                         |                        | store

1. You call add() or search() with any user_id (email, phone, name, internal ID)
2. KanonivMemory calls Kanoniv's resolve endpoint to get the canonical entity_id
3. The canonical ID is passed to mem0 as the user_id
4. Different identifiers for the same person resolve to the same entity
5. mem0 stores and retrieves using the unified ID

The resolve call adds ~5ms (sub-ms if cached in Kanoniv's Redis layer). Results are also cached locally per session.

API

KanonivMemory is a drop-in replacement for mem0.Memory. All the same methods work:

Method	Identity Resolved?	Description
add()	Yes	Add memories from messages
search()	Yes	Search memories by query
get_all()	Yes	Get all memories for a user
delete_all()	Yes	Delete all memories for a user
get()	No	Get a specific memory by ID
update()	No	Update a specific memory
delete()	No	Delete a specific memory
history()	No	Get memory change history
reset()	No	Reset all memories

Additional methods

# Check how a user_id resolves
m.get_entity_id("[e-mail]")
# -> "ENT_7f82..."

# Same person, same entity
m.get_entity_id("[e-mail]")
# -> "ENT_7f82..."

# Clear the local resolve cache
m.clear_cache()

Configuration

m = KanonivMemory(
    # mem0 config (optional - pass any mem0 MemoryConfig or dict)
    config={"vector_store": {"provider": "qdrant", ...}},

    # Kanoniv config
    kanoniv_api_key="kn_live_...",       # Get free key at app.kanoniv.com
    kanoniv_base_url="https://api.kanoniv.com",  # Default
    source_name="mem0",                  # Source name in identity graph
    cache_resolves=True,                 # Cache resolve results (default: True)
)

Using Kanoniv's sandbox (free, no limits during development)

m = KanonivMemory(
    kanoniv_api_key="kn_test_...",  # Sandbox keys start with kn_test_
)

Sandbox gives you 1,000 entities for free, instant reset, full API access.

Graceful Degradation

If Kanoniv's API is unreachable, KanonivMemory falls back to using the raw user_id - exactly like vanilla mem0. Memory still works, you just lose cross-ID unification until the connection is restored. No data loss, no errors.

Why Kanoniv?

Kanoniv is deterministic identity infrastructure for AI systems. It resolves records to canonical entities using configurable matching rules (email, phone, name, company), probabilistic scoring, and constraint-based merging.

• Deterministic: Same input always produces the same entity_id
• Real-time: Resolve calls return in <10ms
• Explainable: Every resolution includes confidence scores and match reasons
• Multi-signal: Matches on email, phone, name, company, and custom fields

Get a free API key at app.kanoniv.com.

License

Apache 2.0