Every new chat. Same context gone. Same project explanation. Same preferences lost.
Meanwhile OpenAI's building a profile of you that you'll never see or own.
We built Onoma because we needed it to exist.
Your memory. Every AI. Actually yours.
We were power users. ChatGPT Plus, Claude Pro, API keys for everything. Custom GPTs, prompt libraries, the works. But we kept hitting the same wall:
Starting over. Every. Single. Time.
That perfect project description from yesterday? Gone. The context you built over three hours of back-and-forth? New chat, who dis. Want to try Claude instead? Hope you like explaining yourself again.
The breaking point was realizing OpenAI remembers everything about us - our code, our strategies, our personal details - while we can't even export it. They're training GPT-5 on our work patterns. We get amnesia. They get our data.
Model lock-in wasn't a bug. It was the business model.
Onoma is what we wanted: one place to chat with any AI, and they all remember you. Your context lives in our Cortex, not their servers.
We made Spaces because folders are stupid for thoughts. Your work stuff naturally separates from personal research. Side projects stay distinct from client work. No organizing - patterns emerge from how you actually think.
The privacy part wasn't an afterthought. Before any prompt hits an LLM, we strip out every piece of PII. OpenAI sees anonymized tokens. You see normal text. They learn nothing about who you are.
Switch models mid-conversation? Your context follows. Compare GPT-4 and Claude side by side? Same memory for both. Let Onoma pick the best model for each query? It knows coding goes to Claude and creative writing to GPT-4.
We built Cortex because middleware shouldn't be dumb. Seven systems working in parallel to make memory real:
Your messages break into atomic contexts - facts, preferences, insights - each timestamped and embedded. These naturally cluster into Spaces based on patterns we detect, not folders you maintain. When you ask something, we pull relevant memories using vector similarity and temporal relevance, compress if needed, then route to the optimal model.
But here's the part we're most proud of: DataFog anonymizes everything before it leaves our servers. Names, emails, account numbers - all become tokens. The LLM processes your anonymized prompt and sends back a response. We restore the tokens. You see real names. They never knew who you were.
Sub-200ms for simple queries. Under 2 seconds with full memory retrieval. Fast enough that you forget it's happening.
Every day we don't have this is another day of:
Re-explaining our projects to AI
OpenAI training on our data
Losing context when switching models
Pretending ChatGPT's memory feature is enough
We built Onoma for ourselves. Turns out we weren't the only ones who needed it.
If you're tired of teaching AI who you are, you're our people. First 1,000 users get lifetime access to core features.
Launching January 2025. Built in Europe. Your data stays yours.