Give your users someone who knows them.

The AI inside your product is probably excellent and completely amnesiac. Oolkin serves a colleague with a consistent character and per-user memory over an API, so your second session is better than your first without you building a memory system.

Create a colleague

Free to start. No card. Takes about a minute.

What actually goes wrong

01Every user's conversation restarts from nothing, so the product never feels like it is getting better at knowing them.
02You could build memory yourself, and then you own an isolation problem, a retrieval problem and a privacy problem that are not your product.
03Your assistant's personality drifts between features because it is three prompts in three files.

What Oolkin does about it

One character, every surface

Define the colleague once. Every feature that calls it gets the same voice, the same standards and the same refusals — instead of three prompts drifting apart in three files.

Memory isolated per end user

Pass who you are acting for and the memory is scoped to them by construction, not by convention. One user's history can never surface in another's answer, because the isolation is a condition of the read rather than a label on the data.

It sharpens where it is used

Feedback from real use accumulates as memory. The version that formed each judgement is recorded, so when you tune the character you can actually tell whether it worked.

What that looks like

worked example

You type

“A coffee expert with strong opinions about extraction, serving thousands of devices, each remembering its own brews.”

You get

Your product's colleague

Answers this user about this user's grinder, at this user's altitude, remembering the last brew they complained about.

Three weeks later

A thumbs-down becomes a judgement it carries. Next answer is sharper for that user, and no one else's.

Describe them once. They take it from there.