Developers · Syni LLM
An AI that already knows how someone’s doing.
Syni LLM is a state-aware language model. It reads a person’s state, focus, stress, and cognitive load, interpreting signals to decide how to respond: when to be brief or more talkative.
- Runs on-device or hybrid
- Consistent behavior across both
- Built on peer-reviewed research (ACM MobileHCI 2026)
Why Syni LLM
Context you can’t type in.
A generic model has only typed input. Syni LLM shows live human states like focus or stress. It adjusts responses accordingly, so users don't need to explain their feelings.
It Interprets The Signals For You
Syni LLM reads live human state and decides the right way to respond, brief or deeper, calm or more talkative.
No Manual Context To Feed It.
Human-state data flows in automatically from Core SDK.
No Separate Integration For State
If you already use Core SDK, Syni LLM reads what’s already there.
Why Syni LLM
Products that respond to someone’s needs.
Syni LLM is built for the kinds of experiences where knowing a person’s state changes the right response. A few of the things developers build on it:
Adjusts to state
Briefer when focus is low, fuller when there's capacity — the model shapes its response to how someone's doing.
Times its help
Holds non-urgent suggestions until attention recovers, instead of interrupting at the worst moment.
Reads from Core SDK
Consumes Core SDK's live state stream directly — no separate context setup or prompt engineering.
On-device by default
Runs locally for privacy, with optional cloud fallback for heavier requests.
The code we build by
What makes it state-aware.
Interprets live human state
Reads focus, stress, recovery, and cognitive load, then decides how to respond, when to be brief, when to go deeper, when to be more talkative.
Conditioned on human state
Every response is shaped by the person’s current state, not just their message history.
Runs on-device or hybrid
Local by default, with optional cloud fallback for heavier requests.
Consistent behavior
Responses stay consistent whether served locally or from the cloud.
On-device is free
Plans include free on-device inference.
Every plan includes on-device inference at no cost. You only pay for what crosses into the cloud.
The code we build by
Build with a persona, or bring your own.
Syni LLM offers ready-made personas for integration. Each persona provides a unique tone and response style. Choose one that suits your product, and Syni LLM takes care of the rest.
No Prompt
Integrate a provided persona in a single step, no prompt engineering required.
Distinct Approach
Each persona takes a distinct approach to users, so the same state can be met with a different style.
Swap Personas
Swap personas without changing how you read state or integrate Core SDK.
See it in action.
See It In Action.
Everything above lives in one interface. You don’t need separate tools for keys, usage, and billing.
The code we build by
Getting a response.
If Core is already integrated, Syni LLM reads the same state stream. No separate context setup required.
FAQ
Frequently Asked Questions
Build with a model that knows the moment.
Works alongside your existing Core integration. See full pricing on the Pricing page.