Intent Guide
If you are building on Gemini and need long-term user memory, stable chat history, and structured app context, Mnexium gives you a production-ready memory layer without stitching together multiple systems.
Marius Ndini
Founder · Mar 3, 2026
Most Gemini apps start stateless. Once users return, you need continuity: what the user likes, what they already said, and what the assistant should remember next. Teams typically add a vector DB, custom extraction logic, conversation storage, and glue code. That works, but it increases complexity quickly.
Mnexium gives you one runtime object to control memory learning, memory recall, and chat history in the same request. You keep Gemini, and add durable context in a few lines.
Send your normal chat request and append the mnx object.
curl -X POST "https://www.mnexium.com/api/v1/chat/completions" \
-H "Content-Type: application/json" \
-H "x-google-key: $GOOGLE_API_KEY" \
-d '{
"model": "gemini-2.0-flash-lite",
"messages": [
{ "role": "user", "content": "My name is Alex and I prefer concise answers." }
],
"mnx": {
"subject_id": "user_123",
"chat_id": "chat_abc",
"learn": true,
"recall": true,
"history": true
}
}'The first request learns memory. Later requests for the same subject_id can recall relevant facts and prior context automatically.
Mnexium Records gives you schema-backed, transactional app data alongside conversational memory. In chat requests, mnx.records controls record recall before generation and record extraction after generation.
curl -X POST "https://www.mnexium.com/api/v1/chat/completions" \
-H "Content-Type: application/json" \
-H "x-google-key: $GOOGLE_API_KEY" \
-d '{
"model": "gemini-2.0-flash-lite",
"messages": [{ "role": "user", "content": "What deals do we have with TechCorp?" }],
"mnx": {
"subject_id": "user_123",
"records": {
"recall": true,
"learn": "auto",
"tables": ["account", "deal"]
}
}
}'records.learn supports "auto", "force", or false."force", records.tables is required.records.sync: true when writes must complete before response.| Capability | Mnexium | DIY Stack |
|---|---|---|
| Memory learn + recall | Built-in | Custom extraction + retrieval |
| Chat history continuity | Built-in | Separate storage and orchestration |
| Structured app records | Built-in schemas + APIs | Separate DB integration |
| Production debugging | Request trace/audit surfaces | Custom logging pipeline |
Start free, then move to Pro with included usage and overages. For larger teams, Enterprise offers custom limits and commercial terms. See the full pricing section on the homepage for current limits.
No. Mnexium adds memory and app context on top of Gemini workflows.
Yes. Mnexium is provider-agnostic and supports OpenAI, Anthropic, and Google model flows.
No. Most teams integrate incrementally by adding the mnx object to existing calls.
Start free with trial keys, then move to Pro when your production traffic grows.