MemoryLake
Media, Publishing & Game

Give Journalists AI That Holds the Full Story, Not Just the Last Prompt

Investigative work builds over weeks. Sources contradict each other. Facts shift. A story you started in January connects to a document you found in March. MemoryLake stores source notes, interview context, and research threads persistently — and flags when new information conflicts with what you already have. Your AI doesn't forget the story.

DAY 1 · WITHOUT MEMORYInvestigative work builds over weeks. 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-loadedSource notes that persist across sess…Conflict detection that protects accu…Story frameworks you reuse, not recre…SESSION OUTPUTSame prompt, on-brand answerGet Started Free →

Give Journalists AI That Holds the Full Story, Not Just the Last Prompt

Get Started Free

Free forever · No credit card required

The Memory Problem

Every new AI session starts without your reporting history. You paste in background research, re-explain source relationships, and reconstruct the story context you built last week. For investigative reporters working multi-month stories, this is not a minor inconvenience — it's a structural problem that makes AI tools nearly useless for deep reporting work.

What MemoryLake Does Differently

Source notes that persist across sessions — Conversation Memory stores every AI session where you worked through interview notes, source backgrounds, or story structure. Search across all prior sessions to find the detail you know you captured two weeks ago.

Conflict detection that protects accuracy — Fact Memory includes built-in conflict checking. When a new source contradicts a fact already in memory, MemoryLake flags it with attribution to both sources. You see the discrepancy before it reaches an editor.

Story frameworks you reuse, not recreate — Skill Memory stores your investigative frameworks — FOIA request structures, source verification workflows, narrative outlines — so you apply proven approaches to new stories without starting from scratch each time.

DAY 1 · WITHOUT MEMORYInvestigative work builds over weeks. 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-loadedSource notes that persist across sess…Conflict detection that protects accu…Story frameworks you reuse, not recre…SESSION OUTPUTSame prompt, on-brand answerGet Started Free →

Give Journalists AI That Holds the Full Story, Not Just the Last Prompt

Get Started Free

Free forever · No credit card required

How It Works

  1. Connect — Bring in interview notes, documents, and research via Google Workspace, Dropbox, REST API, or direct input. MemoryLake's D1 Engine parses complex PDFs and documents automatically.
  2. Structure — Source facts, interview records, and story frameworks are stored in the appropriate memory type. Conflict detection runs automatically as new information arrives.
  3. Reuse — Every AI session — whether in Claude, ChatGPT, or Gemini — draws from the same persistent research memory. Switch tools mid-story without losing context.

Before & After

Without MemoryLakeWith MemoryLake
Picking up a story after a week offRe-paste all research and source notesFull story context available immediately
Contradictory source informationMay go unnoticed until publicationConflict detection flags it automatically
Reusing story frameworksRebuild structure in every new storySkill Memory applies your framework in one step
Multi-reporter collaborationResearch lives in one person's chat historyShared memory accessible to the full team

Built For

MemoryLake is built for investigative journalists and reporters who work multi-week or multi-month stories with complex source networks, editors who need to verify research provenance and fact sourcing, and media researchers building institutional knowledge around beats, topics, or ongoing coverage areas. If accuracy and source memory are non-negotiable in your work, MemoryLake is built for that standard.

Related use cases

Research & AnalyticsAI Memory for Competitive IntelligenceMemoryLake gives strategy and CI teams persistent AI memory for competitor research — with conflict detection when sources disagree and access across every model.
Healthcare & Life SciencesAI Memory for Pharmaceutical ResearchMemoryLake gives drug discovery teams persistent AI memory with built-in PubMed, clinical trial, and FDA drug data — no uploads, conflict detection included.
Legal & IPAI Memory for Patent and IP TeamsMemoryLake gives patent attorneys and IP teams persistent AI memory with 10M+ USPTO patents built in — prior art research and prosecution history always available.

Frequently asked questions

How does conflict detection work for journalism use cases?

When you store a fact from one source and a later session records a contradictory claim, MemoryLake's Fact Memory flags the conflict and shows you both sources with attribution. You decide how to resolve it — the system surfaces the discrepancy, it doesn't overwrite either claim silently.

Can I search across all my past AI research sessions?

Yes. Conversation Memory makes every prior session permanently searchable at millisecond latency. You can query across hundreds of sessions — "find every session where I mentioned source X" or "pull all notes about the regulatory filing from March."

Is my source information and unpublished reporting protected?

All data uses AES-256 encryption end-to-end. MemoryLake is SOC 2 Type II certified and GDPR compliant. Your unpublished reporting, source identities, and research notes are stored within your account only and are never shared externally.

All use casesGet Started Free