Decision framework

One memory across every AI you use, and every chat it joins.

Vendor memory works beautifully inside its own product. Memoria works alongside it — joining the conversations and decisions that happen in the rest of your day.

Just shipped memory
Anthropic OpenAI Google Microsoft
Register your interest See where vendor memory breaks

Section 1 — Where vendor memory breaks

Four structural reasons it doesn't scale

These aren't faults of any specific vendor. They're consequences of the single-ecosystem assumption all vendor memory is built on.

01

Your AI memory only sees one vendor's conversations

Picture an ordinary week:

The analyst is on Claude for research. The marketer is on ChatGPT for copy. The engineer is on Cursor. Three teams, one customer call, three disconnected memories.

Each vendor's memory only sees the work that happens inside its own product. The same decision discussed across three tools becomes three half-pictures, none of which can answer a cross-functional question. The wider your AI surface, the wider the gap. And the meeting where everyone agreed on the customer's actual pain point lives in nobody's memory at all.

Cross-vendor fragmentation
02

Your teams shouldn't have to converge on one chat tool

Picture how your teams actually communicate:

The Sydney team lives in Slack. The London office runs on Teams. Field ops are on WhatsApp. Clients email. Vendor memory assumes one of these wins.

Deploying vendor-controlled memory creates an internal change-management problem — "please move to Teams so AI memory works" — that has nothing to do with the actual job. Channel choice should follow the work, not the limits of a memory feature.

Channel fragmentation
03

Compliance won't allow vendor-controlled memory at scale

Picture a regulated buyer reading your roadmap:

Defence, finance, healthcare, government. They need data residency in specific jurisdictions, customer-managed encryption keys, audit logs for every access event, and certification pathways like SOC 2, ISO 27001, IRAP.

Vendor memory features are designed for ease of adoption, not for procurement. They're built for self-service signup, not to clear a security review. If your roadmap touches regulated work — even eventually — vendor-controlled memory is a non-starter.

Regulatory & sovereignty
04

Vendor memory stores; it doesn't curate

Picture eighteen months from now:

Your AI remembers what you said. It doesn't synthesise across conversations, deduplicate redundant claims, detect contradictions, or maintain a living knowledge base. It's a longer chat history, not an organisational brain.

Memory that doesn't curate becomes a digital landfill. The fix is a curation layer — a Librarian — that actively keeps the knowledge base coherent. Storage is a starting point. Curation is the actual product.

Storage vs curation

Four structural problems. Four very different organisations affected.

None of them get fixed by a feature update.

Section 2 — Side by side

What's actually different

A flat comparison, no marketing weight on the scale.

Cross-AI coverage

Claude, ChatGPT, Gemini, Copilot

Vendor

One vendor only

Memoria

All of them

Cross-channel coverage

Slack, Teams, WhatsApp, email

Vendor

Vendor's products only

Memoria

Any channel

Customer-controlled storage

Where the data physically lives

Vendor

No

Memoria

Yes

Customer-managed encryption keys

BYOK / KMS integration

Vendor

No

Memoria

Yes

Audit logging for compliance

Every access event recorded

Vendor

Limited

Memoria

Full

Curation, synthesis, dedup

Active knowledge management

Vendor

No

Memoria

Librarian agent

Knowledge graph relationships

Entities, decisions, threads connected

Vendor

No

Memoria

Yes

Portable export

Take your memory with you

Vendor

None

Memoria

Standard formats

Switch AI vendors without losing memory

Decoupled from any single model provider

Vendor

No

Memoria

Yes

Section 3 — Who should use what

A framework, not a sales pitch

Read both lists. Whichever sounds more like your organisation, that's the right answer for you. If you're leaning independent, see common scenarios on the homepage.

Use vendor memory if

Single ecosystem, simple stack

  • Your work happens inside one vendor's AI products
  • Your team conversations stay on one platform
  • You're fine with memory that lives in your AI's chat window
  • No compliance or sovereignty requirements
  • You don't expect to switch AI vendors

Use an independent layer if

Multiple AIs, multiple channels, real compliance

  • You use multiple AI tools (Claude, ChatGPT, Gemini, Cursor)
  • Your team works across Slack, Teams, WhatsApp, email, or meetings
  • You want memory that's part of the team conversation itself
  • Compliance, residency, or sovereignty matters to you
  • You expect the AI landscape to keep changing

Section 4 — How Memoria fits the picture

An independent memory layer, on your terms

If your second list looked more like your organisation, here's how Memoria fits into your team's day in practice.

Meets each team where they are

Slack, Microsoft Teams, WhatsApp, Telegram, email, and custom integrations — six channels in production today. The Sydney team stays in Slack, the London office stays in Teams, field ops stays in WhatsApp. Same memory layer underneath. No change-management project to make AI memory work.

Reads across every AI

Claude, ChatGPT, Gemini, Copilot, Cursor, or your own self-hosted model — Memoria works the same regardless of which one your people open today. Switch AI vendors as your needs change; your memory stays.

You own the institutional knowledge

Customer-controlled storage. Encryption keys you hold, not us. Full audit trail on every access. Certification pathway for SOC 2, ISO 27001, and IRAP. Built to clear procurement review, not just to onboard quickly.

Built to outlast the current vendor cycle

Models will keep changing. Pricing will keep shifting. Features will be deprecated. An independent layer means switching AI vendors costs you a contract, not your organisational memory. The lock-in problem is solved by not having the lock-in.

Memory that improves itself

A continuous curation process synthesises related conversations into compiled topic pages, surfaces contradictions, and prunes redundancy. Your knowledge base improves over time instead of decaying into a digital landfill. Vendor memory stores what you said — ours actively organises it.

How Memoria's hybrid actually works

If your memory needs to outlast your current AI vendor, let's talk.

We're working with a small group of organisations on early deployments.

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