When you're operating across tools
Every session starts from zero. You re-explain context, re-prompt corrections, re-establish what your agent already knew.
You open Claude, Cursor, ChatGPT, or Codex to get work done. Nothing your agent learns in one session is guaranteed to be there in the next. When it gets something wrong, there's no way to correct it that sticks. You're the human sync layer between every tool. Neotoma gives you continuity so you can steer instead of drive.
Escaping
Context janitor — human sync layer between tools
Into
Operator with continuity — steering, not driving
Tax you pay
Re-prompting, context re-establishment, manual cross-tool sync
What you get back
Attention, continuity, trust in your tools
Same question, different outcome
Without a state layer, agents return stale or wrong data. With Neotoma, every response reads from versioned, schema-bound state.
Task created in Claude, invisible in Cursor
You told Claude to track a deadline. Later you asked Cursor for open tasks. The deadline didn't exist - each tool keeps its own disposable context with no shared memory.
Stale contact, wrong email sent
You updated a contact's email in one conversation. The next session used the old address because the correction was silently lost.
Receipt stored, then lost
You shared a receipt in a chat. Weeks later you needed it for an expense report. Gone - conversation-scoped memory doesn't keep documents.
Commitment forgotten between sessions
You told your AI you'd follow up with a client by Thursday. By Wednesday, neither tool remembered - the commitment was locked in a prior session's expired context.
Why this happens
Failure modes without a memory guarantee
Every session starts from scratch
You re-explain the same project context, preferences, and constraints in every new conversation. Memory doesn't follow you across tools, and it silently drifts as models compress or discard what you told them.
Commitments vanish between tools
You tell Claude to remind you about a deadline. Later you ask Cursor for open tasks. The deadline doesn't exist. Action items created in one session have no guarantee of surviving to the next.
Corrections don't persist
When your AI gets a date wrong, associates the wrong contact, or misidentifies something, you can't tell it "that's wrong" in a way that lasts. The mistake reappears next session.
Your data in someone else's memory
Your receipts, contacts, health information, and financial records live in provider-hosted memory. No transparency into retention, no guarantee against training use, no delete button.
AI needs
What you need from your AI tools, and what current tools don't provide.
- Memory that survives session resets and tool switches
- One source of truth across Claude, Cursor, Codex, and ChatGPT
- Automatic extraction of commitments, tasks, and contacts from conversations
- Corrections that stick: fix once, fixed everywhere
- Every stored fact traces back to where it came from
How Neotoma solves this
Neotoma removes the tax you pay re-explaining your world to every tool. Store a fact once and it's available everywhere — Claude, Cursor, Codex, ChatGPT. Correct once and it sticks.
Shared memory across every tool
Every agent connected to Neotoma reads from and writes to the same memory. Store a task in Claude, retrieve it from Cursor. One memory, not one per tool.
Facts extracted automatically every turn
People, tasks, events, preferences, and commitments are extracted from every conversation turn and stored before the agent responds.
Corrections that stick
Correct something once. The fix persists across every tool and session. Same question, same answer, every time.
Full history with provenance
Every conversation and fact is stored with its source. See what was known at any point in time and where each fact came from.
What actually changes
Without persistent memory, you drive every turn. Every prompt carries the full weight of what came before because the system won't hold it for you.
With Neotoma, the agent arrives at each session already knowing what it knew last time. Your role shifts from re-explaining your world to reviewing what the agent knows and correcting when it's off.
Fewer prompts, shorter sessions, more done. Not "let me re-explain my situation" - "here's what changed since yesterday."
Data types for better remembrance
The entity types you'll store most often.
conversation
Chat sessions with full turn history across tools
message
Individual turns with role, content, and extracted facts
task
Commitments, reminders, and action items with status and deadlines
note
Captured thoughts, observations, and reference material
contact
People and their details (email, role, organization)
event
Calendar events, deadlines, and commitments
preference
Settings and preferences that persist across sessions
receipt
Purchase records, invoices, and expense tracking
When you don't need this
For one-off questions or single-document analysis, your AI tools already work fine. Neotoma is for when you need what you told one tool to still be true when you open another - and for knowing that a correction you made actually stuck.
Other modes
The same person operates in multiple modes. The tax differs; the architecture that removes it is the same.
The tax is re-prompting, re-explaining, and manually syncing context between tools. Neotoma removes that tax and gives you back the attention and continuity it was consuming.
Built by someone who runs every workflow (email, finance, content, tasks) through the same multi-tool stack.