MemoryLake
Research & Analyticsresearch memory for analysts

Give Analysts a Research Memory That Compounds Quarter Over Quarter

Analysts read the same papers, reach the same conclusions, and re-paste the same context into every new AI session. MemoryLake gives analysts a research memory layer — across PubMed, arXiv, SEC filings, and their own notes — so each new query starts from what's already been learned.

DAY 1 · WITHOUT MEMORYAnalysts read the same papers, reach the same conclusions, and re-paste the s…Got it, I'll remember.DAY 7 · NEW SESSIONSame task, please?Sure — what was the context again?(forgot every detail you taught it)WITH MEMORYLAKEMemory auto-loadedBuilt-in open research dataPersonal note memoryConflict detection across papersSESSION OUTPUTSame prompt, on-brand answerGet Started Free →

Give Analysts a Research Memory That Compounds Quarter Over Quarter

Get Started Free

Free forever · No credit card required

The problem: analyst research doesn't compound across sessions

The literature review you ran last quarter exists as a Google Doc nobody opens again. The AI tool you used has no memory of the four papers you already vetted. Every new question starts at zero. The analyst's institutional knowledge dies with each cleared cache.

How MemoryLake solves research memory for analysts

Built-in open research data — PubMed (40M+ papers), arXiv, bioRxiv, SEC EDGAR (3M+ filings), USPTO patents (10M+) available without setup.

Personal note memory — Your annotations, takeaways, and conclusions become structured memory you can re-query forever.

Conflict detection across papers — When two sources disagree, MemoryLake flags it instead of silently averaging.

Reflection memory for analyst patterns — How you reason about a topic gets captured so future AI assistance aligns with your judgment.

DAY 1 · WITHOUT MEMORYAnalysts read the same papers, reach the same conclusions, and re-paste the s…Got it, I'll remember.DAY 7 · NEW SESSIONSame task, please?Sure — what was the context again?(forgot every detail you taught it)WITH MEMORYLAKEMemory auto-loadedBuilt-in open research dataPersonal note memoryConflict detection across papersSESSION OUTPUTSame prompt, on-brand answerGet Started Free →

Give Analysts a Research Memory That Compounds Quarter Over Quarter

Get Started Free

Free forever · No credit card required

How it works for analyst research

  1. Connect — Tap built-in data sources or import your own papers, notes, and reports.
  2. Structure — Papers become fact memory; your annotations become reflection memory.
  3. Reuse — Each new research question loads the relevant prior memory before the AI drafts.

Before vs. after: analyst research memory

Without MemoryLakeWith MemoryLake
New literature reviewRe-read 30 papersRetrieve prior takeaways
Cross-source conflictSilently averagedSurfaced and flagged
Switching from ChatGPT to ClaudeLose research contextMemory follows the analyst
Five-year longitudinal studyNotes scattered everywhereOne queryable memory

Who this is for

Equity research analysts, academic researchers, biomedical analysts, and policy researchers — anyone whose work requires re-engaging the same source corpus across months and years.

Related use cases

Frequently asked questions

Which research databases are included by default?

PubMed (40M+), arXiv, bioRxiv, SEC EDGAR (3M+), Clinical Trials (500K+), FDA, DrugBank (2M+), USPTO patents (10M+), plus real-time financial data via World Bank and FRED.

Can I add private research?

Yes. Internal papers, proprietary data, and personal notes all live in your private memory namespace.

How does it handle paywalled sources?

You ingest the content you have access to. MemoryLake structures and stores it; access remains yours.