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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.

Read the docs
  • Runs on-device or hybrid
  • Consistent behavior across both
  • Built on peer-reviewed research (ACM MobileHCI 2026)
Syni device showing Understanding your state

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.

Woman at a laptop with Syni messages around her

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:

  • API keys

    Create, rotate, and revoke keys scoped to exactly what each app needs. A leaked key can be revoked in seconds without affecting other apps.

  • Usage

    See what your integrations are doing in one place, without instrumenting it yourself. Track activity across every app your team has registered.

  • Billing

    Manage your plan, payment methods, and invoices in a self-service portal. Upgrade or downgrade without contacting anyone.

  • Team access

    Invite teammates and manage who can see and change what, so access matches how your team is actually structured.

The code we build by

What makes it state-aware.

Smartwatch showing a live focus score of 42
  • 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.

Why Synapse

Plans include free on-device inference.

Every plan includes on-device inference at no cost. You only pay for what crosses into the cloud.

Woman in profile against an orange background

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.

Person in a backbend, in black and white

Platform walkthrough — coming soon.

A terminal showing Python source code

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.