Everything Khwan adds to your model.
The cognition layer that turns a stateless model call into an agent with memory, identity, and receipts — without ever running your model.
Persistent memory
Structured, queryable memory that survives every session. The agent recalls what's relevant to this turn instead of re-filling a context window that resets.
- Persists between sessions
- Relevance-based recall, assembled into each prompt
- Works with whatever model you call
Constitutional identity & coherence gate
Give the agent a written identity. Before each response ships, the coherence gate checks it against that constitution — so behavior stays consistent instead of drifting.
- A written identity the agent is held to
- Each response checked before it ships
- Consistent across long-running sessions
Overnight learning
Between sessions, Khwan consolidates recent turns into durable memory. Next run, the agent starts from what it worked out — not a blank slate.
- Recent turns consolidated into memory
- Resumes with prior context intact
- Runs in the background
Isolated cores
One account, many separate brains — test, staging, per-client. Each core has its own memory and identity; select one with a single line. Plan limits stay pooled at the account level.
- Separate memory per core — no crossover
- Select a core with the `core` option (one line)
- Plan limits shared across the account
Traceability
Every memory write and gate decision is recorded with its source. See why the agent answered the way it did — for debugging and for compliance.
- Source recorded for every memory and decision
- Auditable trace behind each response
- Answer: why did it say that?
Model-agnostic (BYOM)
Khwan is the layer around your model, not a replacement. Bring your own — swap providers, run open weights, mix per task — and keep the same memory, identity, and traceability. Khwan never touches your model.
- Bring your own model on every plan
- No provider lock-in
- Never touches your model or your key