Omnisens AI
Omnisens AI provides infrastructure for reproducible generative AI systems, addressing the problem of stochastic language models producing inconsistent decisions. Its Omnival™ diagnostic measures interpretation drift, while the Kernel™ API acts as a deterministic runtime validator that returns conformance verdicts in under 10ms. The company's Substrate Engineering discipline enables single-shot cross-model convergence without deterministic decoding.
- Artificial Intelligence
- Developer Tools
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Most AI systems are built to survive stochastic behavior through after-the-fact guardrails, validators, retries, and LLM judges, which increase cost, latency, and complexity. This approach fails to address a deeper issue: when the same input is processed under the same conditions, systems often do not make the same decision again, making correctness and reliability measured against a moving target. This "Interpretation Drift" leaves systems unpredictable, difficult to control, and harder to trust and audit.
Solution
Omnisens AI treats stochasticity as a feature, not a bug, and deliberately engineers the conditions that shape the decision distribution itself. The company's engineering discipline detects interpretation drift, shapes the pre-sampling decision distribution, moves authority out of the stochastic layer, and validates deterministically. Omnival™ is a diagnostic instrument that measures where interpretation drift enters a decision pipeline and whether instability affects the reproducibility of correct outcomes. Substrate Engineering specifies task meaning with explicit reproducibility criteria, reducing interpretive multiplicity and separating interpretation from computation. TCP/AP (Trusted Cognition Protocol / Agentic Protocol) is an open protocol layer for reproducible LLM-native execution, inspired by how TCP/IP made reliable communication possible over unreliable networks.
Target Audience
Primary customers are engineering teams and organizations building agentic AI systems that require reproducible, auditable, and controlled decision-making, including those in regulated industries and enterprises deploying LLM-native execution.
Features
- Omnival™ measures reproducibility—whether the same input under the same conditions produces the same decision—rather than mere accuracy
- Substrate Engineering achieves single-shot cross-model convergence without deterministic decoding
- TCP/AP defines how meaning, intent, and authority must be specified and validated across stochastic AI systems
- Kernel™ API is a stateless, deterministic runtime validator that returns binding conformance verdicts in under 10ms with no inference or model loading
- Kernel validates via HTTP 200 for conformance or a deterministic HTTP error taxonomy for inadmissible states, making semantic errors explicit, machine-readable, and traceable
- Every validated decision carries a cryptographically verifiable chain of custody, acting as a cryptographic notary for machine decisions
- Available as self-serve hosted API and air-gapped on-prem, with SOC 2 Type II infrastructure and encryption in transit and at rest