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UMO · Decision
Q2 budget approved at $40K
Sarah J. · Board call · Mar 3
Confidence: 0.97Receipted
UMO · Preference
Brand voice shifted to "Warm & Direct"
Strategy session · Feb 28
Source: SlackEncrypted
UMO · Relationship
Sarah J. is lead on ACME account
Inferred from 14 interactions
Provenance: Multi-source
UMO · Timeline
April 15 launch window confirmed
Email thread · Mar 5
Hash: 8f3a...c2Portable
UMO · Insight
Retargeting outperformed cold 3:1
Analytics · Q1 report · Feb 20
Confidence: 0.94Queryable
UMO · Context
Client prefers muted earth tones
Design review · Jan 15
Source: Figma comments
UMO · Approval
CEO signed off on messaging pivot
Slack DM · Mar 1 · Verified
ReceiptedE2E
UMO · Pattern
Team velocity drops 40% on Fridays
Inferred from 8 weeks of data
Auto-enriched
UMO · Reference
Competitor launched similar feature Feb 12
RSS + Slack mention · Cross-ref
Linked: 3 UMOs
UMO · Sentiment
Client satisfaction trending up since Feb
NPS + Slack tone analysis
Confidence: 0.89
UMO · Dependency
Campaign blocked until legal reviews copy
Project tracker · Mar 8
Status: Pending
UMO · Identity
You prefer bullet-point briefs over long-form
Inferred from 23 documents
MI™ is you.
UMO · Rhythm
Engagement peaks Mon/Tue mornings
12 weeks of data · Auto-enriched
Confidence: 0.91
UMO · Trigger
Brand tone shifts after budget reviews
Semantic correlation · 6 events
PatternEnriched
UMO · Commitment
Legal review promised by Friday EOD
Email thread · Mar 10
Hash: 2d9b...f4
UMO · Preference
Client favors short-form video over carousels
3 campaign reviews · Q1
Source: Multi
UMO · Decision
Retargeting budget increased 20%
Board call · Mar 3
Receipted
UMO · Context
Sarah OOO next week, handoff to Mike
Slack · Mar 12
Linked: 2 UMOs
UMO · Insight
Email open rates 2x higher with personalization
Analytics · Feb 2026
Queryable

The memory API your stack is missing.

SETTING THE STANDARD FOR AI
Memory

The memory API your stack is missing.

Intelligence
Private Structured Traceable Portable Permanent

The suite

MemoryIntelligence™ · MemorySpace™ · SpaceAgent™

Everyone is talking about how the answer to better AI is more “context.”

But nobody is asking what “context” actually means.

Getting data closer together does not make it mean anything.

A standard does. There is no standard today.

Until now.

Context versus Memory Intelligence new standard SNIP LOG CHAT DOC ? “Context” Memory Intelligence™ CAPTURE STRUCTURE RECEIPT NOT A STANDARD NEW STANDARD

THE PROBLEM IN NUMBERS

This is what broken data costs right now.

Before any AI tool. Before any new software. This is the tax your team is already paying every single day just to find things that already exist.

1.8 hrs
McKinsey Global Institute
Spent searching for information every single day

Per employee. Not browsing. Not working. Just searching. That is 9.3 hours a week per person.

Team cost
For a team of 10, that is 18 hours a day just searching for stuff.
50%
IDC Research
Of internal searches fail on the first try

Half the time, the first search returns the wrong thing. IDC found workers take up to 8 searches to find one specific document.

Search depth
Average of 8 searches to find one specific document.
$2.5M
IDC Research
Lost per 1,000 employees annually

The direct financial cost of the inability to find and retrieve internal information. Not productivity losses. Not opportunity cost. Just the raw number.

14%
Harvard Business Review 2025
Of time spent recreating work that already exists

On top of searching, employees spend another 14% rebuilding things they know exist but cannot find. The same work, done twice.

Team cost
5.6 hours a day rebuilding work that was already done for a team of 10.
23 min
University of California Irvine
To return to deep work after one interrupted search

Every failed search costs 23 minutes of lost focus. Multiply that by 8 failed searches per document.

1/5
McKinsey Global Institute
Employees is essentially a full-time searcher

For every five people you hire, only four are actually working. The fifth is spending their entire week finding information for the other four.

THE FIX

We solve that in three steps.

See how it works

MI™ fits anywhere data exists.

Every memory comes with five guarantees.

Built into every memory.

PRIVATE
Your memory stays on your infrastructure.
Imagine your AI learns from your notes without your notes ever leaving your laptop.
STRUCTURED
Raw input becomes a searchable, meaningful object.
Imagine every Slack message, email, and doc becoming one searchable Memory object.
TRACEABLE
Cryptographic receipts at every stage.
Imagine knowing exactly where every AI answer came from and when.
PORTABLE
Your memory travels across every tool and session.
Imagine switching from ChatGPT to Claude and keeping everything you taught it.
PERMANENT
Memory persists and compounds. No expiration.
Imagine never re-explaining yourself to an AI that forgot you existed.

The difference is structure.

Features MI™ Semantic Search
Pinecone, Weaviate
RAG Frameworks
LangChain, Llama Index
Enterprise Search
Elastic, Vertex AI
LLM Context Windows
Claude, GPT, Gemini
Memory survives session endX-XX
Runs on your own infrastructure---X
Works with any LLM or tool---X
Structures data at ingestionXXXX
No context limit across sessions---X
HIPAA / compliance built-in-X-X
Reduces LLM compute 30%+XXXX
API-first memory in minutes-X-X
Cryptographic hashing every step of pipelineXXXX

YES X NO - PARTIAL

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