Skip to main content

Documentation Index

Fetch the complete documentation index at: https://wiki.mira.tg/llms.txt

Use this file to discover all available pages before exploring further.

​
Memory

Mira operates within real conversations — across personal and group chats — retaining contextual and structured memory over time. This is Mira’s core defensive advantage: a social memory layer built inside Telegram’s existing social graph.

​
How Memory Works

Mira builds memory on three levels:

​
1. Personal Memory (Private)

Everything you share in 1-on-1 chats with Mira stays strictly private. Mira remembers:
  • Profile: name, location, occupation, timezone, language
  • Preferences: communication style, topics of interest, answer format
  • Facts: anything you share — “I’m launching a startup”, “I prefer bullet points”
  • Context: ongoing projects, recurring tasks, past decisions
Personal memory persists across conversations and improves over time. No one else — not group members, not other users — can ever access your private memory.

​
2. Group Memory (Shared)

In group chats, Mira retains shared context:
  • Summarizes long discussions on demand
  • Remembers decisions made by the group
  • Surfaces missed updates across chats and channels
  • Participates like a digital teammate — aware of who said what
Group memory is scoped to the group. Mira never leaks private memory into group chats — your personal context, preferences, and facts stay invisible to other members.

​
3. Amortized Memory

Mira uses amortization to manage memory efficiently:
  • Older conversations are compressed into summaries, preserving key facts without storing every word
  • Active topics and recent context are kept in full detail
  • This means Mira remembers what matters, without requiring infinite storage — and without degrading response quality over time
Amortization ensures Mira stays fast, relevant, and privacy-respecting even after thousands of conversations.

​
Privacy Architecture

Mira is designed with strict privacy boundaries:
BoundaryRule
Private → GroupNever. Your personal memory, preferences, and facts are never shared in group chats.
Group → PrivateNever. Group context doesn’t leak into your 1-on-1 conversations.
Group → GroupNever. Each group’s memory is isolated. Mira doesn’t carry context from one group to another.
AmortizationSummaries are anonymized and scoped. No raw conversation data is retained long-term.

​
What This Means in Practice

  • If you tell Mira in a private chat that you’re allergic to shellfish, it will never mention that in a group chat when someone asks for restaurant recommendations.
  • If a group decides on a launch date, Mira will not bring that up in another group or in your private chat unless you ask.
  • Your communication style preferences (e.g., “I like short answers”) only affect how Mira responds to you, not how it responds to others.

​
AI-Powered Recall

Mira helps users stay on top of their Telegram:
  • Surface missed updates across chats and channels
  • Instant retrieval from personal and group conversation history
  • AI-powered search — ask in natural language, get precise results
What did John send me last week about the contract?
Summarize what happened in this chat while I was away
What are the open action items from today's discussion?

​
Network Effects

The more people use Mira together, the more valuable the network becomes. Anonymized, aggregated insights from group interactions create a defensible social intelligence layer — something no standalone AI app can replicate.
All aggregated insights are anonymized. Individual conversation data is never shared between users.