Aymo AI vs Memdex — Save your AI conversations. Use them everywhere.: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Aymo AI and Memdex — Save your AI conversations. Use them everywhere. — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Aymo AI
Pimjo
All-in-one AI workspace giving teams unified access to 51+ frontier models like GPT-5, Claude, and Gemini with shared credits and collaboration.
Key features
- Multi-Model Access: One account gives instant access to 51+ frontier LLMs including GPT-5, Claude, Gemini, DeepSeek, Grok, Mistral, and LLaMA.
- Compare Mode: Run the same prompt across several models side by side to pick the best output for each task.
- Document-Aware Chat: Upload PDFs, spreadsheets, docs, and code for grounded answers without copy-pasting content into the prompt.
- Team Workspaces: Shared chats, roles, project context, and reusable prompts included on every plan for real-time collaboration.
- Shared Credit Pool: Teams pay for shared usage credits instead of per-seat fees, so light users do not drive up cost.
- Chrome Extension: Access Aymo alongside any web app for quick assistance without switching tabs.
- Free Utility Tools: Bundled PDF summarizer, email writer, and marketing helpers usable outside the paid workspace.
Best for
- Model Comparison: Marketers or engineers can A/B-test the same prompt across GPT, Claude, and Gemini before committing.
- Team Knowledge Base: Shared project prompts and chats keep a distributed team aligned on tone, context, and templates.
- Document Q&A: Analysts upload long PDFs or spreadsheets and query them conversationally in a single workspace.
- AI Cost Consolidation: Replace multiple per-seat AI subscriptions across a small company with one shared credit pool.
- Rapid Prototyping: Product teams iterate on marketing copy, code, or design briefs across many models in one thread.
Memdex — Save your AI conversations. Use them everywhere.
Memdex
Auto-saves AI conversations across ChatGPT, Claude, and Gemini with local-first storage and searchable reuse.
Key features
- Auto-Save Across Platforms: Continuously captures conversation transcripts from major chat interfaces (ChatGPT, Claude, Gemini) so users don’t lose context across sessions or browser tabs.
- Local-First Storage: Stores all saved conversations on the user’s device (100% local storage) to eliminate vendor lock-in and reduce privacy exposure.
- Searchable Indexing: Builds a keyword/semantic index of saved chats to quickly locate relevant past exchanges, prompts, or project-specific context.
- Context Reuse & Injection: Allows users to bring selected past messages or threads into new chats or agents to preserve continuity and avoid re-telling context.
- Cross-Platform Connectors: Integrates with multiple chat providers through browser-level connectors/extensions to capture and surface memory everywhere the user interacts with an LLM.
- Organization Tools: Lets users tag, group, or filter saved conversations so project-related context can be surfaced rapidly when needed.
- Automatic capture and save of conversations across ChatGPT, Claude, and Gemini
- 100% local storage of conversation data (no cloud persistence)
- Searchable indexed archive to find and reuse past chat context
- Cross-session and cross-tool context retrieval to restore or continue workflows
- Local-first architecture to avoid vendor lock-in and preserve privacy
- Intended browser-level integration/extension to hook into chat providers
Best for
- Recovering Work Context After Session Loss: Restore conversation state and relevant details when an AI chat session is lost, crashed, or cleared.
- Ongoing Project Continuity: Maintain and reuse project-specific prompts, decisions, and background across multiple AI chat providers without repeating setup.
- Privacy-Sensitive Knowledge Storage: Keep private chat history and research locally rather than in a cloud service, meeting privacy or compliance needs.
- Cross-Tool Prompt Reuse: Extract and re-inject effective prompts or examples from past chats into new conversations on other platforms to speed iteration.
- Research and Note Consolidation: Index and search findings, suggestions, and outputs from multiple AI sessions to compile notes, summaries, or action lists.
- Restoring lost or interrupted chat context across sessions and devices
- Reusing previous conversation snippets or instructions when starting new chats
- Privacy-sensitive workflows that require local-only storage of chat history
- Developers and knowledge workers managing multiple project conversations across different chat providers
- Providing agents with persistent local memory to improve continuity across interactions