Give Your AI a Second Brain That Actually Remembers Your Work

You brief your AI on your industry, your role, your clients, your frameworks — and then the session ends. Tomorrow you do it again. Weeks of accumulated context, refined prompts, and hard-won synthesis vanish every time you close a tab. The AI is fast, but your institutional knowledge of how to use it is constantly being thrown away.

Structured memory, not flat notes — MemoryLake stores your knowledge in six distinct types — Background, Fact, Event, Conversation, Reflection, and Skill — each optimized for how that information is used and retrieved. A research finding stored as a Fact Memory behaves differently than a project milestone stored as an Event, which behaves differently than a reusable research methodology stored as a Skill.

Cross-model portability — Your memory travels with you across ChatGPT, Claude, Gemini, Perplexity, and any API endpoint. Switch models without losing context. The second brain belongs to you, not to any one AI vendor.

Searchable history at millisecond latency — Every conversation, decision, and document you've processed is permanently archived and instantly searchable. MemoryLake ranked #1 on the LoCoMo long-context memory benchmark at 94.03% — it retrieves the right memory, not just recent memory.

1. Connect — Link MemoryLake to your AI tools via MCP protocol, REST API, or Python SDK. Works with any model or platform you already use.
2. Structure — As you work, MemoryLake automatically categorizes information into the right memory type: stable identity facts go into Background Memory, time-stamped events into Event Memory, reusable processes into Skill Memory.
3. Reuse — Every future session opens with your relevant memory already loaded. Your AI knows who you are, what you're working on, and how you prefer to work — without you repeating yourself.

Knowledge workers who use AI daily and need it to function more like a long-term collaborator than a stateless tool. This includes analysts, consultants, researchers, writers, strategists, and product managers who accumulate significant domain knowledge over time and lose productivity every time they have to re-establish context. MemoryLake is also suited for teams that want to share institutional knowledge across members through a common memory layer.