AI that doesn’t forget.
A Database keeps the outputs worth remembering, connects them, and hands them to the next piece of work. Your AI work compounds instead of evaporating.
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Value that stops evaporating
AI produces things worth keeping every day, then they scatter across chats, documents and spreadsheets. A Database gives them one persistent home, across every chat, session and project.
Information with a shape
Outputs land as rows with typed fields and long-form notes, so every record holds the facts and the story behind them. Edit it by hand, or ask in Chat.
Connected to what it belongs to
Share and link rows with a person, a project, a chat or the whole organization. The meeting stays attached to the lead, and the proposal can see both.
Read by the next workflow
Chats and agents write in what is worth keeping and query it before they generate. One system does the work and remembers it, with no exports or sync jobs in between.
Compounding context
Day one, a lead is stored. Day seven, a meeting is connected to it. Day fifteen, research on the company lands beside them. Day thirty, a proposal is written with all of it in view.
- [1]
Generate
A chat, a Skill or an agent produces something useful.
- [2]
Store
What is worth remembering lands as a structured row.
- [3]
Connect
The row is linked to the people, projects and Databases it belongs to.
- [4]
Accumulate
Each kept output adds to the same layer, not a new silo.
- [5]
Reuse
The next workflow starts from that context instead of from zero.
And round again. The same knowledge never has to be generated twice, which can reduce repeated processing and model and API costs.
Built for the outputs your work produces.
Explore all use cases- Sales
Leads, meetings and follow-ups connected, so no lead gets researched twice.
- Research
Findings accumulate, so new research builds on what you already know.
- Meetings
Decisions and open items tied to the accounts and projects they involve.
- Content
Ideas, drafts and past work kept as raw material for the next piece.
- Operations
Tasks and decisions with their context attached, ready to query.
- AI agents
Agents read the history before they act and write back what matters.
How to put a Database to work
Get Started Free- [1]
Create a database
Define the fields for what a piece of work needs to keep.
- [2]
Point a workflow at it
Chats and agents write the results worth keeping straight in.
- [3]
Connect what belongs together
Share it with a person, project, chat or organization, and link related rows.
- [4]
Query it before you generate
Every task that follows starts from what is already there.
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