SYBERLABS

SYBERLABS / TECHNICAL PRIORITY 01

Intelligence
at the decision
boundary.

Unstructured state and named questions in. Typed, probabilistic answers out. SyberLabs is engineering the boundary that turns those answers into permitted product actions.

Explore Jev SaaS architecture

Jev is TypeSafe AI's model. SyberLabs is independently evaluating and integrating it. This page does not imply a partnership or a verified production deployment.

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MODEL / INTERFACETYPED ANSWERS

STATE → TYPED ANSWER

A decision is
an interface.

TypeSafe describes Jev as a System One model: state and a set of named questions go in; structured, probabilistic answers come out. The output space is declared before inference, so the application can compose those answers in code.

One request can combine different question types. The examples are illustrative, not live model calls or benchmarks.

TypeSafe API quick start ↗
CURRENT QUESTION

Which reading action fits this moment?

The product supplies only permitted choices. Jev selects among them; product code still decides whether to act.

SPECIFICATION, NOT A PROMISE

The integration contract

The request holds a bounded snapshot of product state and explicit question criteria. The provider response is parsed into a versioned internal decision. A separate policy step then validates the chosen action against consent, authorization, and current state.

REQUEST → ANSWERILLUSTRATIVE
COURSE / POLICY + LIMITSMODEL → POLICY → EVIDENCE

JEV / ENGINEERING SYLLABUS

A probabilistic answer.
A deterministic system.

Turn typed answers into permitted actions, then evaluate them against real outcomes.

MODULE 02Policy derivation

Convert judgment into an admissible action.

Jev returns an answer. The application computes the action using the current state and an independently maintained permission set. If state is stale, output is malformed, or no action is permitted, the policy returns hold.

APPLICATIONa = π(s_now, J(s, Q), grants, consent, policy_version)a ∈ permitted_actions(s_now) ∪ {hold}

A Choice or Score confidence value summarizes distribution concentration. It is not the probability that an action is safe, correct, or authorized. For a calibrated binary correctness estimate p, a simplified policy acts only when (1 − p) × cost_wrong < cost_review, then separately checks authorization. Estimate p and both costs from labeled outcomes; this formula assumes review resolves the decision.

MODULE 03Known limits

Put arithmetic and invariants in code.

TypeSafe documents jagged behavior for jev-1.13: literal interpretation, numeric precision, date comparisons, irrelevant state, and adversarial text. Test these failure modes. Keep counting, date arithmetic, budgets, and authorization outside the model.

MODEL TASKSemantic judgment

“Does this message request a refund?”

CODE TASKDeterministic fact

“Were two charges captured within the allowed window?”

HUMAN TASKConsequential acceptance

“Should this customer remedy be approved?”

Version specific source: TypeSafe's jev-1.13 limitations. Recheck the deployed version before relying on them.

SYSTEM / B2B + B2CREFERENCE ARCHITECTURE

TWO DEPLOYMENT SHAPES

The model is shared.
The boundaries differ.

Proposed B2B and B2C systems. Both keep credentials server side and require scoped audit records, a safe fallback, shadow rollout, and an off switch. Tenant isolation and operator rights differ from consumer consent and reversibility.

WORKED B2B FLOW

Support triage across tenants

REFERENCE PSEUDOCODEPROPOSED
EVIDENCE / EXPERIMENT DESIGNEVIDENCE GATES

FROM DEMO TO DEPLOYMENT

A syllabus for
proving value.

Every proposed Jev seam needs a predeclared baseline, observable outcome, and failure budget. Measure the complete product action, not the model answer alone.

01 / CONTROLLED COMPARISON

Same cases. Same rules.

Use consented, held-out decision moments with independent labels. Run the existing route and Jev route under the same permissions, review budget, and completion criteria. Stratify by tenant, task, language, and risk.

02 / ERROR SURFACE

Calibrate and break it.

Compare predicted probabilities with observed frequencies by segment. Test prompt injection, stale state, missing choices, cross-tenant references, revoked consent, timeout, and model changes.

03 / SHIP GATE

Measure the whole action.

Count accepted outcomes, false actions, review load, p95 latency, retries, and fully loaded cost. Start in shadow mode; stop exposure when a predeclared limit fails.

PASS CONDITION / PROPOSED

Advance only when the Jev route improves an independently verified user outcome over baseline within the product's risk, privacy, latency, and cost limits. Publish denominators and failure cases.

CURRENT STATUSRISE / READING

ONE CONCRETE SEAM

RISE has a bounded
reading decision.

The route selects continue, slower, or pause. Consent, passage admission, cancellation, and presentation limits remain in code. The adapter exists; provider activation and representative live reading outcomes are unverified.

Next proof: exercise the configured provider in a connected preview, then compare reader outcomes with the existing path.

Inspect RISE ↗