Evidence · first-party tested/Best AI Tools for Memory for AI Agents

Kept client scope isolated: BetaCorp under a different account ID did not inherit ACME's troubleshooting history and received a first-touch support reply instead.

✓ Worked🧾 artifact-verifiedinput + output shownTest date not recordedZep →
What was measured
Scope Control

Checks whether memory is separated correctly across user, project, customer, workspace, or agent boundaries.

decisive for this rankingtransformation

Correct separation across users, projects, workspaces, or agents is fundamental to whether retrieved memory is actually the right memory. (3 of 3 judges)

What was given, what came back

Test input: Client Relationship Memory · text · group: memory-for-ai-agents
Input — what we sent
The exact prompt
Session 1:
Use this under account_id: client_acme_001

ACME is a client using our AI support assistant. They prefer clear next steps and do not like repeated troubleshooting. Their team already tried password reset, clearing browser cache, and switching browsers. The issue is still happening only for users with SSO enabled.

Session 2:
Use this under account_id: client_acme_001

ACME came back today and said: "Our users still cannot log in with SSO. What should we try next?"

Draft a support reply that respects what they already tried and moves to the next useful step.

Session 3:
Use this under account_id: client_acme_001

Update the client memory: ACME is no longer using SSO for this rollout. They moved to email-password login for the first launch. Do not keep treating SSO as the active issue unless they mention it again.

Session 4:
Use this under account_id: client_acme_001

ACME says: "Some users are still unable to log in during launch testing."

Draft the next support reply.

Session 5:
Use this under account_id: client_beta_002

BetaCorp is a new client. They say: "Our users cannot log in for the first time."

Draft the first support reply for BetaCorp.

A client-support memory test that checks whether the assistant remembers prior troubleshooting, handles a changed rollout context, keeps client scope isolated, and avoids leaking one client’s history into another client’s support reply.

Why this input is hard
  • · client history recall
  • · avoid repeating troubleshooting
  • · update handling
  • · scope isolation between clients
  • · support response continuity
Output — unretouched
image
Provenance
Observation
93a526cd-3eea-4b8b-84d0-5e3221af8c8d
Evidence run
6e31afbb-34d7-459a-b688-68ef76fc615a
Study
Memory for AI Agents
Research task
86ba16xrp
Tested at
not recorded
Source
first-party
Evidence state
verified
Proof shown
input + output shown
Cost / latency
not captured
Repeat run
not captured
Tester
not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this
get_evidence({
  tool: "zep",
  scenario: "memory-for-ai-agents"
})
MCP · mcp.aidemos.com/api/mcp
JSON · ai.aidemos.com/v1/observations/93a526cd-3eea-4b8b-84d0-5e3221af8c8d
Free with attribution.
Same input, same check — 4 other tools
measured on Scope Control
Cognee✓ WorkedKeeps client containers isolated: a fresh `client_beta_002` reply does not inherit ACME's troubleshooting history or preferences.Hindsight✓ WorkedIt keeps BetaCorp isolated as a new client bank, so ACME's troubleshooting history does not leak into the first BetaCorp reply.Mem0✓ WorkedKeeps client scope separated so BetaCorp does not inherit ACME's prior troubleshooting history or SSO context.Supermemory✓ WorkedThe tool kept client memories isolated: the separate BetaCorp container showed 'No memories retrieved yet' and did not inherit ACME's SSO history, troubleshooting steps, or support preferences.
This evidence is published in
Best AI Tools for Memory for AI Agents →
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com