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Independent Risk Evidence for AI Workflows
As AI systems become increasingly autonomous, organisations need to understand not only whether AI is working, but whether it remains reliable, trustworthy, and safe to operate.
SignalCrux helps organisations identify AI exposure before it causes damage to a brand, operational disruption, legal liability or regulatory issues.
The duty arrived before the instrument
EU AI Act high risk obligations take effect December 2027. FCA guidance and enforcement pressure are live now. Oversight is already an evidence duty, and most firms have no evidence layer to discharge it with.
From single outputs to sequences
Failures stop being isolated outputs and start being sequences. A sequence can be tracked. That is the whole opportunity.
Identify
Detect the first node in a sequence that crosses boundary logic.
Measure
Quantify risk in pounds at the intervention window boundary.
Track
Monitor exposure accumulation as the sequence evolves through the workflow.
Discharge
Provide an immutable evidence layer to meet regulatory and oversight duties.
Green dashboards, real exposure
In the insurance workflow in our live demo, every dashboard stayed green while £508,000 of settlement exposure accumulated underneath. IS(x) crossed the 0.72 boundary at node 5 and the payout never fired.
Declining reasoning quality
Subtle shifts in logic and inference that degrade output accuracy over time.
Agent instability
Inconsistent behavior in multi-agent workflows leading to unpredictable outcomes.
Workflow inconsistency
Breakdown in complex, automated processes as variables change.
Governance breakdown
Silent drift away from established safety and operational constraints.
Exposure accumulation
Latent risks that build up before becoming visible failures.
Customer Harm
Incorrect decisions, poor customer experiences, and inconsistent outcomes that impact trust and business performance.
The cost of silent degradation often remains hidden until it escalates into enterprise scale risk.
Who this is for
SignalCrux provides the intervention window evidence required across the enterprise.
CRO
Accountable for exposure, needs intervention window evidence in pounds.
Head of AI
Needs independent reliability evidence to unblock production sign off.
Governance & Audit
Needs auditable oversight evidence from the same feed.
Engineering
Engineering owns uptime. This is not an engineering purchase.
Technical Degradation
Workflow Instability
Operational Cost
Legal Liability
The evolution of AI systems demands a shift in how we quantify risk. As workflows move from assistive to autonomous, the impact of technical degradation scales non-linearly across the enterprise stack.
Regulatory Risk
Brand Damage
The cost of AI failure is rarely the failure itself. The cost is the exposure that accumulates before anyone realises there is a problem.
From Reliability To Exposure
Why Independent Assurance Matters
AI systems increasingly involve multiple models, agents, and vendors, as well as external APIs and human interactions. No single vendor has visibility across the entire stack. The scored system cannot grade itself. A first party score fails the second line test by construction.
Independent System Visibility
SignalCrux evaluates reliability across models, agents, workflows, tools, and business processes rather than focusing on a single component of the AI stack. This provides a broader understanding of how exposure develops across autonomous systems.
Neutral Reliability Layer
As AI systems become increasingly autonomous, organisations require independent assurance that reliability is being measured objectively rather than assessed by the systems themselves. SignalCrux provides that independent reliability layer.
Published, not asserted
The IS(x) methodology and benchmark are deposited at Zenodo, DOI 10.5281/zenodo.20708678, and under peer review at PLOS ONE. Calibrated across 2,700+ sequential scenarios on Claude, Gemini and OpenAI. The scoring layer runs live. The demo scores a real insurance claims workflow on real inference, in the browser, in under four minutes.
Our Vision
Every major technology wave creates a trust layer. As enterprise AI becomes increasingly autonomous, organisations need a new way to understand, measure, and manage reliability. SignalCrux is building the risk evidence layer for enterprise AI. We believe that independent assurance is the cornerstone of sustainable innovation.