Cognitia AI

Your AI Memory Layer

Memory Layer Context Assembly MCP Integrations For Developers

Why Memory Matters

Most assistants forget your context after each interaction. Cognitia keeps persistent memory so each response can build on what actually matters to you.

Without Persistent Memory

115k+ tokens resent per query as conversation history grows, driving up cost and latency every turn.

28.9s median response time on GPT-4o at full context—too slow for interactive use.

Critical facts buried in long transcripts suffer from the "lost in the middle" effect, degrading accuracy.

Total amnesia between sessions—every new conversation starts from zero context.

With Cognitia Memory Layer

Only ~1.6k structured tokens injected per query—a 98% reduction in context size and cost.

2.6s median response time with sub-200ms memory retrieval—90% faster than full-context.

Graph traversal captures relationships, temporal order, and causal chains—92% recall vs 85% for vector RAG.

Knowledge persists and consolidates across every session, growing more precise over time.

Explore Memory Layer For Developers

Research-Backed

Why a Memory Layer Outperforms the Alternatives

Session-based chatbots forget everything. Naive RAG dumps raw text into the context window. A structured memory layer delivers order-of-magnitude improvements in cost, speed, and relevance.

98%

Fewer Tokens

1.6k vs 115k context tokens per query

~90%

Lower Latency

2.6s vs 28.9s median response time

92%

Retrieval Recall

Graph memory vs 85% for vector RAG

<200ms

Retrieval Latency

P95 memory retrieval in production

Session-Based Chat

Baseline

Token Usage

Grows linearly

Full conversation history resent every turn; 115k+ tokens at scale

Response Latency

28.9s median

GPT-4o on 115k context window (Zep LongMemEval)

Accuracy

Degrades over time

Critical facts buried in long transcripts; 'lost in the middle' effect

Scaling

Cost and latency scale linearly with conversation length. Hits model context limit and must truncate.

Key Limitations

Total amnesia between sessions

Context window overflow after extended conversations

No cross-session learning or preference retention

Processing 1M tokens takes ~60s, blocking interactive use

Naive RAG

Partial Fix

Token Usage

Moderate savings

Retrieves relevant chunks but often pulls redundant or low-relevance text

Response Latency

Variable

10–100ms retrieval + LLM inference; still sends unstructured context

Accuracy

85% recall / 75% precision

Vector similarity misses relationships and temporal ordering

Scaling

Retrieval cost is roughly flat, but accuracy degrades as the corpus grows without structured organization.

Key Limitations

No understanding of entity relationships or causality

Temporal ordering of facts is lost in embedding space

Chunks lack structured context—raw text fragments

Cannot resolve conflicting information across sessions

Structured Memory Layer

Cognitia Approach

Token Usage

~1.6k tokens

98% reduction—only relevant structured facts injected into context

Response Latency

2.6s median

90% faster than full-context; <200ms P95 retrieval (Zep benchmarks)

Accuracy

92% recall / 88% precision

Graph traversal captures relationships, temporal order, and causal chains

Scaling

Fixed retrieval cost regardless of memory size. Knowledge graph grows without impacting per-query latency or token budget.

Key Limitations

Initial write cost for memory extraction

Requires structured ingestion pipeline

The Economics of Memory

Research from March 2026 shows that at 100k-token context lengths, a structured memory system becomes cheaper than full-context approaches after just 10 interaction turns. The break-even point decreases as conversations grow longer.

Full-context LLMs incur per-turn charges that grow with history. Memory systems pay a one-time write cost, then maintain a roughly fixed per-turn read cost—making them increasingly economical for persistent, long-running assistants.

Cost per Turn Over Time

Turn 1

Turn 10

Turn 50

Turn 100+

Full context: Cost rises linearly — 115k tokens by turn 50

Naive RAG: Moderate cost, but accuracy degrades as corpus grows

Memory layer: Fixed ~1.6k tokens per turn regardless of history length

Sources

Zep AI, "State of the Art in Agent Memory," LongMemEval benchmarks — 1.6k vs 115k tokens, 90% latency reduction, 2.58s vs 28.9s median (GPT-4o). getzep.com/state-of-the-art-agent-memory

"Beyond the Context Window: A Cost-Performance Analysis of Fact-Based Memory vs. Long-Context LLMs," arXiv:2603.04814, March 2026 — break-even at ~10 turns for 100k context.

MAGMA: Multi-Graph Agentic Memory Architecture, arXiv:2601.03236, Jan 2026 — 55.1% F1 on multi-hop reasoning, dual-stream ingestion for latency-sensitive writes.

SparkCo, "AI Agent Memory Comparative Guide," March 2025 — graph-based retrieval 92% recall / 88% precision vs RAG 85% recall / 75% precision.

How It Works

Get up and running in three simple steps

Step 1

Sign Up

Create your free account in seconds with email, Google, or iCloud sign-in. No credit card required to get started.

Step 2

Connect Your Tools

Link your email, calendar, bank accounts, cloud storage, social media, and local devices. Cognitia securely connects to the tools you already use.

Step 3

Let AI Agents Work For You

Cognitia orchestrates multiple specialized agents that browse the web, manage emails, analyze finances, generate documents, and automate multi-step workflows — all powered by MAGMA, a persistent memory layer that learns who you know, what you care about, and how your life evolves over time.

Step 1

Sign Up

Create your free account in seconds with email, Google, or iCloud sign-in. No credit card required to get started.

Step 2

Connect Your Tools

Link your email, calendar, bank accounts, cloud storage, social media, and local devices. Cognitia securely connects to the tools you already use.

Step 3

Let AI Agents Work For You

Interactive Knowledge Graph

See how Cognitia builds a living knowledge graph from your emails, calendar, documents, and conversations — then uses it for contextually aware actions.

Entity Types

Person

Organization

Place

Product

Topic

Event

Loading knowledge graph...

AI Assistant

Live

Prepare me for my meeting with David Kim

What's the Q1 launch status?

Who works on AI strategy?

What Memory Looks Like

Cognitia transforms your interactions into structured memory: summaries, relevant facts, and temporal context for better decisions.

Example memory context block

<USER_SUMMARY> You are preparing a Tokyo trip in April and prefer nonstop flights when prices are comparable. You prefer calm neighborhoods, vegetarian-friendly restaurants, and morning schedules. </USER_SUMMARY> <RELEVANT_FACTS> - Prefers nonstop flights for long-haul travel. (2026-02-10 - present) - Budget target for flights is under $1,200 round trip. (2026-02-11 - present) - Wants 2 hotel options in Shibuya and Asakusa. (2026-02-12 - present) - Previously preferred evening meetings, now prefers morning meetings. (2025-11-01 - 2026-01-15) - Updated preference to morning meetings. (2026-01-16 - present) </RELEVANT_FACTS>

Measurable User Outcomes

Benchmarked against full-context and RAG baselines across published research.

Token Efficiency

98% fewer

Structured memory injects only ~1.6k relevant tokens per query instead of dumping 115k+ tokens of raw history into the context window.

Response Speed

~90% faster

2.6s median response time versus 28.9s for full-context approaches—memory retrieval completes in under 200ms at P95.

Retrieval Precision

88%

Graph-based memory achieves 92% recall and 88% precision, outperforming vector-only RAG at 85% recall and 75% precision.

Cost Break-Even

~10 turns

Memory systems become cheaper than full-context after roughly 10 interaction turns at 100k-token scale, then stay flat as conversations grow.

Consumer Proof in Real Workflows

Memory quality should be judged by outcomes users feel: fewer repeats, faster completion, and more consistent responses across sessions.

Travel Planning Continuity

Before memory, users restate budgets, airline preferences, and date constraints every session. With persistent memory, follow-up planning starts with known preferences and active constraints.

Lower prompt repetition across sessions
Faster itinerary revisions with prior context
More stable recommendations over time

Project and Communication Memory

Before memory, communication style and project history get reset each day. With memory, Cognitia keeps who is involved, prior decisions, and style preferences available by default.

Fewer corrections in drafts and summaries
Better continuity in multi-day work
Higher relevance in follow-up actions

Research context: MAGMA reports stronger long-horizon memory performance on LoCoMo and LongMemEval benchmarks, supporting the memory-layer approach for persistent agents. See MAGMA (arXiv:2601.03236) and related temporal-memory benchmark references such as Zep temporal memory architecture.

Powerful Features

Everything you need to supercharge your productivity

Core

Advanced AI Chat

Engage with cutting-edge AI models including GPT-5.4, GPT-5.4 Mini, and Claude Opus 4.6 for intelligent conversations enhanced with real-time web search and up-to-date knowledge.

Smart

Persistent Memory

Your AI remembers context across all conversations, creating a truly personalized experience that grows smarter over time.

Advanced

Multi-Agent Orchestration

Intelligent task coordination across specialized agents for email analysis, financial insights, calendar management, and cross-domain processing.

Connected

Email Integration

Connect Gmail, iCloud, and Outlook to read, send, and analyze emails. Draft replies, search conversations, and manage your inbox seamlessly.

Secure

Financial Intelligence

Connect your bank accounts via Plaid to get insights into spending patterns, transaction analysis, and financial summaries.

Social

Social Media Management

Connect Social Media apps to share posts, analyze social activity, and manage your professional presence directly from the chat.

Smart

File Processing

Upload and analyze documents, images, and code files. Extract text, generate descriptions, and get AI-powered insights from your files.

Organized

Calendar & Contacts

Sync with iCloud and Google services to manage events, contacts, and schedule coordination with intelligent context awareness.

Extensible

MCP Marketplace

Browse and connect external MCP servers from the Official MCP Registry to extend your AI assistant with hundreds of third-party tools and capabilities.

See What Cognitia Can Do

Autonomous AI agents that take action on your behalf across every connected tool

MAGMA Memory

Memory

MAGMA (Multi-Agent Graph Memory Architecture) builds a persistent knowledge graph of your life — people, relationships, temporal facts, and behavioral signals — extracted automatically from every interaction. Ask about anyone, anything, or any time period.

What do you know about Sarah Chen? When did I last interact with her and what was it about?

Let me query your MAGMA knowledge graph for everything about Sarah Chen...

memory_agent_query

**Sarah Chen** — Product Manager at Acme Corp **Relationship:** You've interacted with Sarah across 23 touchpoints over the past 4 months. She's connected to the Q1 product launch project. **Last interaction:** Email thread on Feb 12 about the design review timeline. She requested pushing the review to next Wednesday. **Key facts:** - Works on the mobile app team at Acme Corp - Prefers async communication over meetings - Involved in 3 shared calendar events this month - You exchanged 8 emails in the past 2 weeks **Behavioral signal:** Your communication style with Sarah tends to be direct and bullet-point based.

Your Personal Memory Layer

A persistent, intelligent knowledge base that lives across every interaction—accessible by you, your apps, and the services you trust.

What Is the Memory Layer?

Every conversation you have, every preference you express, and every piece of knowledge you share is stored in a structured, persistent memory graph. Unlike traditional chatbots that forget everything when the session ends, Cognitia builds a living knowledge base that continuously learns and evolves with you.

Your memory layer organizes information into entities, relationships, and context—forming a personal knowledge graph that any AI interaction can draw from instantly. It is the bridge between isolated conversations and truly intelligent, context-aware assistance.

How It Works

Automatic extraction: Key facts, preferences, and relationships are identified and stored as you chat naturally.

Structured graph: Information is organized as interconnected entities—people, places, projects, preferences—not just raw text.

Cross-session continuity: Your AI picks up exactly where you left off, with full awareness of past context.

Always improving: The memory layer refines and consolidates knowledge over time, resolving conflicts and strengthening connections.

Why an AI-Native Memory Graph Changes Everything

Higher Accuracy

Grounded in your real data instead of guessing. The memory graph supplies verified facts, preferences, and history to every response—dramatically reducing hallucinations and irrelevant answers.

Greater Efficiency

No more repeating yourself. Your AI already knows your background, projects, and preferences—so every interaction starts with full context instead of a blank slate.

Deeper Personalization

Responses are tailored to your unique situation, communication style, and goals. The more you interact, the more precisely the AI adapts to serve you.

Cross-Domain Intelligence

Your memory graph connects insights across emails, finances, calendars, and conversations—surfacing patterns and relationships no single tool could discover alone.

Access Your Memory Through External Services

Your memory layer is not locked inside a single chat interface. Cognitia exposes your personal knowledge graph through secure APIs and integrations, so any authorized service or application can tap into your memory—with your explicit permission.

REST API

Query, read, and write to your memory graph programmatically. Build custom workflows, dashboards, or integrations that leverage everything your AI knows about you.

MCP Protocol

Connect third-party AI tools and agents through the Model Context Protocol. External services can read your context to deliver hyper-personalized experiences.

Privacy-First Access

Every external access request requires your explicit approval. Granular permission controls let you decide exactly what data each service can see—and revoke access at any time.

Privacy and Control by Design

Cognitia keeps you in control of what gets shared, who can access it, and how memory is managed.

Permissioned Access

External services only access memory after explicit approval, with revocable controls.

Security Commitments

Sensitive data handling and processing protections align with your existing privacy policy terms.

Deletion Rights

You can request deletion and manage consent settings based on the controls described by Cognitia.

Read Privacy Policy

Real-World Workflows

One message triggers a complete multi-step workflow across all your connected tools

Morning Briefing Agent

"Good morning, catch me up."

With a single message, Cognitia gathers information from all your connected services and delivers a consolidated morning briefing.

Scans Gmail for unread emails

gmail_search_emails

Checks today's calendar events

gmail_search_calendar_events

Reviews Telegram messages

telegram_context

Searches web for relevant news

web_search

Delivers your personalized briefing

orchestrator

Travel Planning Workflow

"I need to plan a trip to Tokyo next month."

Cognitia coordinates browser automation, calendar management, document creation, and cloud storage to plan your trip end-to-end.

Searches flights and hotels online

browser_agent_execute

Checks calendar for conflicts

gmail_search_calendar_events

Creates a trip itinerary document

create_document

Saves itinerary to Google Drive

google_drive_upload

Adds trip dates to your calendar

gmail_create_calendar_event

Social Media Content Pipeline

"Draft a LinkedIn post about our Q4 results using the data from this spreadsheet."

Upload a file, and Cognitia extracts insights, drafts professional social media posts, cross-posts across platforms, and sends you the drafts for review.

Reads the uploaded spreadsheet

file_read

Extracts key metrics and insights

analysis

Drafts a LinkedIn post

linkedin_create_post

Cross-posts summary to X/Twitter

x_create_tweet

Emails draft for your review

gmail_send_email

Your Data, Your Fortune

Take control of your digital assets and unlock their true value

Data is the Oil of the New Age

In today's digital economy, data has become the most valuable resource—more precious than oil. Yet while platforms compete fiercely for access to your personal information, you're left out of the equation. Your data generates tremendous value, but that value flows to corporations, not to you.

It's time to change that. Imagine a platform where you own your data,you control who accesses it, and you set the price. A future where sharing your data means getting paid for it—fairly and transparently.