amaiko vs Read.ai: Personal Knowledge Graph vs Corporate Memory (2026)

What Read.ai does genuinely well

Most Read AI comparison pages open by dunking on the bot. Let’s open with respect instead, because Read.ai is the closest conceptual rival amaiko has on the question that matters most: memory.

The most comprehensive knowledge graph in its class. Read.ai’s Search Copilot connects meetings, email and Slack into a cross-channel knowledge graph — further than anything else in the meeting-AI category goes. Ask what was agreed with a customer and it can pull from the call, the follow-up email and the Slack thread. Whoever designed this understood that transcripts alone are not knowledge.

Proven traction. Roughly 5 million monthly active users and a $450 million valuation. This is not a weekend project — it is a serious company executing a serious thesis.

CRM Copilot earns its keep. Automatic Salesforce and HubSpot updates after calls remove one of the most reliably hated chores in sales. If your pipeline hygiene depends on reps remembering to log calls, this feature alone justifies a look.

EU data residency exists. Multi-region storage covering the EU is available — on the enterprise tier. Hold that qualifier; we will come back to it.

So why does this page exist? Because Read.ai and amaiko agree on the thesis — AI without memory is a toy — and disagree on the architecture. A personal knowledge graph fed by a meeting bot and a shared corporate memory are two different machines, and the difference decides what your company actually gets.

Five structural differences

The amaiko vs Read.ai question is more interesting than most comparisons on this site, precisely because both products take memory seriously. Here is where the architectures part ways.

A personal graph is not a corporate memory

Read.ai’s knowledge graph is per-user and meeting-fed. It grows when the bot attends your meetings, and it answers questions about what you were in the room for. Your colleague’s graph doesn’t know what yours knows. The new hire starts with an empty graph. And when an employee leaves, their graph — every decision they witnessed, every context they carried — walks out the door with them. That is personal memory, and it is genuinely useful. It is just not organizational memory.

amaiko builds a persistent corporate memory shared across the company: decisions, context, who knows what, why things were done the way they were. Knowledge captured once is available to everyone with the right to see it, and it survives staff turnover. The measurable effect for amaiko teams: 35% less time spent searching and onboarding up to 57% faster — because new hires inherit a memory instead of starting a graph from zero.

The bot in the room

Read.ai’s intelligence arrives as a visible participant in your calls — and that bot is the product’s biggest liability. The consent problem is not theoretical: there are documented GDPR complaints because Read.ai emails meeting summaries to all invitees, including external participants who never agreed to anything. Corporate IT departments have responded the way corporate IT departments do: by blocking the bot on Zoom and Teams outright. Every external meeting now opens with a variant of “what is Read.ai and why is it in this call?” — not the first impression most companies want to make.

amaiko sends no bot. It works inside your existing Microsoft 365 environment, where your meetings, mail and files already live. No visible participant, no auto-mailed summaries to people outside your company, no awkward consent conversation at the top of every client call.

Analytics after vs assistance before

Read.ai tells you what happened: transcripts, summaries, action items, talk-time, sentiment and engagement scores. Useful — and structurally reactive. The meeting is over by the time the value arrives, and the analytics describe the past. amaiko works on the other side of the clock: your morning briefing is ready before you open the laptop, your inbox is triaged before you read it, meeting follow-ups appear without anyone asking. A rear-view mirror and a navigator are both useful instruments; only one of them changes where you end up.

Teams is one platform. For amaiko, it’s home.

Read.ai supports Microsoft Teams the way it supports Zoom and Google Meet: the bot joins the call. There is no native Teams app interaction model — no chat surface where the actual work happens, no presence in the place your company already spends its day. amaiko is Teams-native by design: a multi-agent network of 24 specialized AI agents — for meetings, email, research, knowledge linkage and more — operating inside the Teams environment you already have. Onboarding is a single Teams chat: install it, say hello, it starts working. See how the agent network operates.

Where your data lives by default

Read.ai is headquartered in San Francisco, and processing happens in the US by default. SOC 2 Type II and HIPAA are real attestations, and GDPR compliance is claimed — but for a European company, “claimed, US-processed, complaints pending” is a sentence your data protection officer reads twice. amaiko’s answer is structural: 100% German hosting and ISO 42001 certification, the management standard for AI systems — on every plan, not as an enterprise upgrade.

The EU residency nuance

Credit where it is due: Read.ai actually offers EU data residency, which is more than most of the meeting-AI category can say. But read the conditions. It is enterprise-only — $29.75 per user per month and up — and a recent addition. Residency also doesn’t touch the consent problem: where the data sits is a separate question from whether a bot should be mailing summaries to your customers’ inboxes. And Read.ai remains a US company under US jurisdiction, a residual exposure no EU storage region removes. For a company that wants the data question settled rather than tiered, that is the difference between a feature and a foundation.

The pricing reality

Read.ai’s free tier covers 5 meetings a month — a well-built funnel into Pro at $19.75 per user per month ($15 billed annually). But here is the European math: EU data residency requires Enterprise at $29.75 per user per month ($22.50 annual), and Enterprise+ runs $39.75 with a 10-user minimum. For an EU company that takes data protection seriously, the real Read.ai price starts at the enterprise tier.

amaiko starts at €19.92 per user per month, billed annually — with German hosting and the full corporate memory included from the first seat. Data protection is not an upsell.

Who should choose which

Honest segmentation, no sales reflex.

Choose Read.ai if your meeting culture spans Zoom, Meet and Teams in equal measure, you want engagement and sentiment analytics on those meetings, your sales team lives on automatic CRM updates — and a visible bot plus US-default processing, or enterprise pricing to avoid it, doesn’t bother you. Within those lines, it is the most capable meeting-intelligence product you can buy.

Choose amaiko if Teams is where your company works, you want a memory the whole organization shares rather than per-user graphs, no bot in the room with your customers, proactive assistance instead of post-meeting analytics, and German hosting on every plan rather than behind an enterprise gate.

Running both is possible — Read.ai for cross-platform meeting analytics, amaiko for corporate memory and proactive work in Teams — but check with your IT and legal teams first, because the bot is exactly the kind of guest they have started turning away at the door.

If you are surveying the wider field, our roundup of Read.ai alternatives covers the other contenders. And if you would rather see a corporate memory than read about one: book a demo — it takes one Teams chat, and no bot will attend.