One platform, three places it has to work

Security platforms are usually divided by function: one product detects, another responds, a third manages cases. That division looks tidy on a slide and produces exactly the integration burden that makes security operations expensive, because a single incident has to be handed between products that each hold a partial view of it.

Spharaka divides by environment instead, because environment is the thing that genuinely differs. A corporate laptop, a cloud workload and a programmable logic controller cannot be instrumented the same way. The laptop can run an agent. The workload can stream logs and API events. The controller can do neither: it cannot take an agent, it usually cannot be scanned without risk, and stopping it to apply a patch has a physical cost.

So the collection surface changes between the three products, and nothing else does. The reasoning, the case, the policy envelope and the evidence trail are shared. An analyst investigating a compromised engineering workstation that reached a plant network sees one case, not an endpoint alert in one console and an OT anomaly in another.

Spharaka Sphere™ is the core. It unifies SIEM, SOAR, XDR and EDR into a single system: universal log collection across hybrid and multi-cloud estates, correlation into events rather than alerts, autonomous investigation that assembles an evidence chain, and response executed through playbooks generated per incident. It is the product the capability pages describe, and the one the other two feed.

Spharaka EdgeProtect™ is the endpoint half, where speed matters more than anywhere else because encryption starts locally. It provides application control, ransomware protection and one-click containment, and it is what lets a containment decision made centrally take effect on a device in seconds rather than through a ticket.

Spharaka Signal™ is the industrial estate. Collection is passive by default: sensors observe mirrored traffic from a SPAN port, a network tap or ERSPAN and never inject traffic into a safety controller. It reads industrial protocols at register level, so a write that changes a burner setpoint is legible as that rather than as a TCP session on port 502, and it produces continuous compliance evidence against IEC 62443, NERC CIP, NIST SP 800-82r3 and AWWA G430 instead of an audit scramble.

For most software, deployment topology is a procurement detail settled after the platform is chosen. For an AI-native security platform it is closer to the opposite, because where the model runs determines what the platform can be asked to do with your data.

A platform that reasons about incidents at a public API cannot reason about telemetry you are not permitted to send there, which in regulated sectors is most of it. Sphere On-Premises runs SAGE™ inference locally, inside your own data centre, so an air-gapped deployment loses no capability rather than degrading to log storage with a rules engine. That is what makes the platform usable in defence, in government and in banks whose regulator has a view about data residency.

Cloud, hybrid, on-premises and fully air-gapped are all supported topologies, and the deployment models guide sets out what each one lets you ask of the platform, along with the trade-offs that come with each.