Pre-seed · Stockholm

Train better. Serve cheaper.
Verify safer.

Fidelity Horizon is building governed AI infrastructure: three products that make AI models more efficient to train, cheaper to serve, and safe to trust. Built on a shared mathematical framework across the full AI lifecycle.

Model intelligence verified

Structural analysis verified across 10+ architectures from 11M to 72B parameters. Redundant layers identified and removed with quality preserved or improved. Harmful layers discovered that actively degrade model performance.

Inference cost reduction verified

Response-aware routing verified on public benchmarks with significant cost reduction at near-complete quality retention. Consistency routing verified to exceed single-model quality. Provider-agnostic architecture.

Deterministic verification built

Byte-identical reproducibility across runs. Zero false positives on critical test cases. Cryptographic audit trail per decision. Verified against leading models across multiple clinical scenarios.

Detailed results with methodology →

From training to verified output

Pre-deployment screening finds model failures. Runtime routing optimizes cost. Deterministic verification catches what confidence misses.

Attractor mapping
Pre-deployment screening. Identifies failure modes, including cases where the model is confidently wrong. Results feed into new verification contracts.
MCG training
TTU routing
Safety routing
Runtime safety layer. Detects safety-critical queries and flags cases where model output may be unreliable. Flagged queries route through CoF Audit for verification.
CoF Audit

Each component works standalone. The stack multiplies value.

AI is expensive, opaque, and unverified

Cost without control

Every query is treated equally expensive, regardless of difficulty. No quality signal per response, just a flat cost per token. Organizations overpay systematically.

Quality without visibility

AI models produce answers with no quality check. There is no visibility into when the model was uncertain. No warning when a provider update changes answer quality.

Regulation without infrastructure

EU AI Act, DORA, and NIS2 drive demand for traceability and documented risk management. But delivering that per response remains an infrastructure gap.

From analysis to autonomous governance

Today, each product addresses a specific gap. Over time, the shared mathematical foundation enables capabilities that isolated tools cannot deliver.

Near term

Model audits that reveal internal structure. Inference routing that adapts to each response. Verification gates that produce reproducible audit trails. Each product independently valuable.

Medium term

Cross-product intelligence: training insights informing runtime decisions. Automatic rule discovery from traffic patterns. Drift detection across fine-tuning cycles. The stack becomes self-reinforcing.

Long term

A governance layer for AI systems, from training through production. Continuous model health monitoring. Autonomous verification scaling across verticals. The infrastructure that makes AI trustworthy.

Common questions

What is Fidelity Horizon?

Fidelity Horizon is a Stockholm-based AI infrastructure company building three governed AI products: MCG for model intelligence, TTU Router for inference intelligence, and CoF Audit for deterministic verification. All three are connected by one mathematical framework.

What is Conservation of Fidelity?

Conservation of Fidelity is the mathematical framework connecting all three products. It defines how we quantify layer importance, assess response quality, and verify output correctness, so insights from one product strengthen the others.

What stage is Fidelity Horizon at?

Pre-seed stage, headquartered in Stockholm. Verified results across multiple architectures on public benchmarks. Looking for design partners and aligned investors.

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Interested in what we're building?

We're looking for design partners and aligned investors.