We monitor systems and devices for behaviour that falls outside what is expected or authorised. When something changes, deviates or looks wrong, It is detected, recorded in line with defined policy – no guesswork.
Events are timestamped, attributed and preserved, allowing issues to be identified early, evidence to be retained and action to be taken safely and proportionately.
No Hype. No magic. Just governed detection.
Anomaly DetectionDetect What’s Wrong. Prove What Happened. Act Safely.
Detect unusual behaviour before it becomes a breach
Every behaviour event is captured with time, source and context, so there is a clear record of what occurred and when. Behaviour is assessed against defined expectations and policy, not assumptions. Then response is taken within agreed boundaries rather than automatically or blindly. This ensures issues can be reviewed, decisions explained and actions justified. Whether for operation teams, auditors or insurers.
Evidence is Key
Detect unusual behaviour before it becomes a breach.
Get real-time alerts across every SIM in your network.
Guarantee fewer false alerts with continuous machine learning.
Stop threats at the source with protection built into your network.
Scale securely without adding security headcount.
Improve network uptime and reliability.
Permission. Audit. Policy & Trust at Source.
Identity is anchored at the physical edge. Evidence is sealed at the point of creation and never altered. Behaviour is constrained by explicit, human authored policy, with systems enforcing rules but never creating intent. Whan anomalies occur, they trigger human decision rather than machine autonomy. All actions and refusals are fully traceable end-to-end within a private trust boundary, ensuring accountability always resolves to a human.
Assuring behaviour. Wherever it matters
Built for Evidence. Designed for Accountability & ROI from Month One!
Hyper Logical gives partners a better way to manage evidence, behaviour and accountability by design and with responsibility that always resolves to people. Return on investment in IoT is often positioned as future value, but the reality is simpler. Most organisations are already paying today through uncontrolled cost, operational disruption and time lost investigating incidents after the event. Behavioural Assurance delivers immediate return by reclaiming spend and reducing incidents, lowering investigation effort and enabling earlier intervention when systems drift out of bounds. The economics are straightforward: ROI=Cost Paid Today + Time Reclaimed + Risk Controlled. For most organisations, this return is realised from the first month of operation, because the cost already exists and it is simply made visible, governed and productive.
Built at the Edge. Governed End-to-End
Behind the scenes, assurance is enforced where it matters most and that is at the physical Edge. Identity is established at source, data is sealed on creation and every interaction is secured within a private trust boundary from device to platform. Policies are executed locally, decisions are logged immutably and nothing acts without traceability. This is not security bolted on in the cloud but real provenance, control and accountability designed into the fabric of how systems v=connect and behave.
- What do you actually mean by Behavioural Assurance?
The means understanding how devices and systems are expected to behave and detecting when they don’t so that it is provable, governed and accountable. We focus on behaviour and ensure that detection, response or escalation follows defined policy rather than automated guesswork.
- How is this different from traditional anomaly detection or monitoring tools?
Most monitoring tools generate alerts based on thresholds or patterns and leave teams to work out what happened after the event. Behavioural Assurance goes further by recording events with context, evaluating them against known baselines and policy and preserving evidence as issues unfold. The result is earlier visibility, clearer understanding and safer decision making.
- Does this rely on AI making decisions on our behalf?
No AI is used to assist detection and pattern recognition, not to create intent or take uncontrolled action. Decisions remain governed by human authored policy and anomalies trigger human judgement. The system enforces rules, but responsibility always remains with people.
- Where does evidence come from?
Evidence is captured at source, timestamped and attributed and preserved as part of the system’s normal operation. This creates a trusted record of what happened, when and in what context. Evidence is not reconstructed later or inferred. The data is retained as evidence occurs, making it suitable for operational review, audit and investigation.
- How do you avoid overwhelming teams with alerts?
Behaviour is evaluated against expected norms and defined policy, which helps distinguish genuine issues from noise. This reduces false positives and ensures alerts are meaningful, actionable and relevant. The aim is not more alerts, but better ones that come with context that supports calm, informed response.
- What are the business benefits?
If I don’t do this, I’m exposed and financially, operationally and personally at risk. Avoid uncontrolled spend, reduce downtime, shorten incident reporting and shorten investigation. At the same time limit regulatory and compliance exposure. Prevent small issues becoming reputational events. With orchestration alert fatigue and team burnout we minimise overload by focusing on the meaningful data. By working smarter you can cut out the noise and data that doesn’t need to be accumulated for years on end at vast hosting fees. Protects careers as well as systems.<BR>
Behavioural Assurance doesn’t just protect systems it protects budgets, operations and the people responsible for them.
- What problem does this actually solve for us today?
It gives teams earlier visibility into issues, clearer understanding of what’s happening and confidence that responses are controlled and defendable. Instead of reacting late or guessing under pressure, organisations can act deliberately, with evidence and accountability already in place.
For Example:
- Unidentifiable data spikes across a device estate
- Devices operating outside approved ptterns
- Gradual degradation rather than a single event
- Supporting incident review and audit
- Operating safely in regulated environments
These aren’t edge cases they are the everyday realities of running connected systems at scale.
- What application examples can you give?
Designed for connected systems operating at scale, where failure, misuse or drift carries real operational, financial or regulatory risk. Just some applications we cover:-<BR>
- CCTV & Body-Worn Video
- Smart Buildings and Critical Infrastructure
- Fleet, Transport and Assets
- Healthcare & Remote Monitoring
- Industrial IoT
- Public Sector
- Enterprise Device Estates