Human-verified memory for AI agents
Your tools capture everything.SPONGE turns it into trusted memory.
SPONGE sits after meetings, transcripts, CRM, email, and documents. It turns raw records into candidate memories, gives people the evidence to review and approve them, then lets every agent query the same source-backed record.
- transcript · Mar 2“Renewal is March 14.”
- transcript · Mar 2duplicate“Renewal is March 14.”
- email · Apr 1“Actually — renewal moved to April 14.”
- crm note · May 8Prefers email over phone.
- chat · Jun 12uncertain“Might move to annual billing?”
The problem
More context does not create reliable memory.
Transcripts and records contain duplicates, tentative ideas, corrections, contradictions, and facts that stopped being current. Retrieval can find every version, but it cannot decide which version your organization has approved for an agent to use.
Raw history
Five records. Three versions of one fact.
Retrieval alone
Four close matches, equally weighted. The agent still has to guess.
Human-approved memory
One approved current answer, with its evidence and history attached.
How it works
From raw records to approved memory.
- 01
Absorb
Connect or import the places knowledge already lives — meeting transcripts, CRM records, email, documents, and agent observations — without replacing the tools that captured them.
- 02
Reconcile
AI turns raw records into candidate memories — not verified truth. It groups duplicates, detects corrections, surfaces contradictions, and attaches the supporting evidence to each candidate.
- 03
Review & approve
A person reviews each proposed memory alongside its meeting, speaker, exact quote, AI confidence, and history — then edits, approves, rejects, merges, or marks it temporary. Only approved items enter verified memory.
- 04
Query
Agents query approved memory by default and get the current answer with its provenance, approval state, and revision history — no reinterpreting the raw transcript every time.
The layer after capture
SPONGE is not another meeting notetaker.
Capture tools tell you what was said. Retrieval systems find relevant passages. SPONGE is the control layer that turns those records into memory people have approved and agents can safely reuse.
Capture and retrieval tools
“What was said, or looks relevant?”
SPONGE
- What has been approved as current?
- Who approved it, and from which evidence?
- What did it replace, and when?
- What remains tentative, conflicting, or temporary?
AI proposes. People decide. Agents retrieve.
The verified memory object
Every approved memory carries its proof.
SPONGE’s unit is not a text chunk. It is a human-approved claim connected to its source evidence, current state, approval history, relationships, and the memory it superseded.
- Approval and AI confidence are separate signals. A model’s score never stands in for a person’s decision.
- Every approved value links to its exact source — the meeting, the speaker, the quote, and the timestamp.
- New approvals replace without erasing. The current value changes; the previous one stays in the revision history.
- Temporary, disputed, or unapproved claims stay outside verified memory until someone decides otherwise.
For agents
Agents read from memory people have approved.
SPONGE gives ChatGPT, Claude, custom agents, and internal copilots one model-independent memory layer. Agents query approved memory by default. New observations can create proposals, but they do not silently change what is verified.
For developers
Query approved memory, not raw context.
Ask a question and receive the approved current answer with its status, reviewer, source evidence, and revision history — instead of a pile of similar transcript chunks.
SPONGE is pre-release. The interface shown here is the target developer experience — the API surface we’re designing toward — published for feedback, not yet a shipping SDK or schema.
const memory = await sponge.memory.resolve({
subject: "acme-corp",
question: "What renewal date should we use?",
status: "approved",
}){
"value": "2027-04-14",
"status": "current",
"verification": "human_approved",
"approved_by": "revops-lead",
"approved_at": "2027-04-02",
"supersedes": "2027-03-14",
"revisions": "mem_9f2c4/history",
"sources": [{
"meeting": "mtg_0412",
"speaker": "M. Chen",
"quote": "Let’s move renewal to April 14.",
"at": "2027-04-01T16:04Z"
}]
}Product architecture
A human approval boundary between raw records and AI action.
SPONGE separates source evidence, candidate memory, and verified memory. AI can extract and reconcile. People decide what becomes durable. Agents consume only the approved layer by default.
Evidence stays linked
Every candidate and every approved memory keeps its connection to the meeting, speaker, quote, and timestamp it came from.
Approval is explicit
Nothing becomes verified memory implicitly. A person reviews, and the record shows who approved what, and when.
History remains intact
New approvals supersede older values without deleting them. The revision history is part of the memory, not a log somewhere else.
Sources
Candidate-memory pipeline
Human approval boundary
Verified-memory layer
Access layer
Consumers
Conceptual product architecture. SPONGE is being built toward this workflow; not every integration or interface shown is currently available.
Why now
Agents are taking on long-term responsibility. Memory needs governance.
AI now runs across sessions
Assistants and agents operate across sessions, applications, and longer-running workflows. What they remember follows them everywhere they act.
Context changes constantly
Renewals move, owners change, decisions get revised. Raw history grows less reliable with every week that passes — unless someone maintains what is current.
Action requires accountability
When AI acts on memory, organizations need evidence, ownership, and accountability for what it believed and why.
The model can change. Approved memory should remain.
Starting with meeting-driven work
Turn conversations into memory every agent can use.
Revenue teams
Preserve current customer commitments, preferences, pricing, renewal details, and changes across meetings and connected records.
Operations & project teams
Maintain approved decisions, action items, owners, risks, and deadlines.
AI assistants
Carry approved personal or company context across sessions without replaying raw history.
Agent builders
Add human-governed, source-backed memory without building the full review and reconciliation system from scratch.
Trust
Human approval is the trust boundary.
SPONGE can organize evidence and recommend what changed. It does not silently promote a model inference into organizational truth.
- AI proposes; people approve.
- Every approved memory links to its exact evidence.
- Approval records who reviewed or changed the memory.
- Corrections update the current state without deleting history.
- Temporary and uncertain information stays outside verified memory until approved.
- Users can inspect, update, export, and delete their memory.
Give your agents memory your team can stand behind.
SPONGE is building the human-verified memory layer between your records and the AI systems acting on them.
Or email us directly at hello@spongememory.com.