Industries - Defence & Aerospace
Full autonomy on networks that cannot call out, with no external model dependency.
Defence and aerospace environments are frequently disconnected by design, and an external inference call is not a procurement concern to be negotiated but a condition that rules a platform out. Spharaka Sphere™ runs the entire loop inside the customer controlled network, with SAGE™ served locally, so autonomous investigation is available on networks that never reach the internet.
Cybersecurity Landscape
Defence networks inverted the usual security trade-off long ago. Where a commercial enterprise weighs connectivity against exposure, a classified environment starts from isolation and asks what capability can survive it. Most modern security tooling cannot: it assumes a cloud back end, a threat intelligence call and, increasingly, a model API somewhere else.
That assumption has become the binding constraint on AI in defence security operations. A platform whose reasoning happens behind a vendor's inference endpoint is not deployable in an environment where evidence cannot leave, regardless of how the contract is written. The question is not whether the vendor is trustworthy. It is whether the architecture makes the question necessary at all.
Classified and mission networks operate disconnected by design, which rules out any capability that depends on a remote service.
An inference endpoint outside the boundary is not a risk to be mitigated in these environments; it is a condition that ends the evaluation.
AI has compressed the attack lifecycle into an automated operation that executes faster than most teams receive their first alert.
The staffing shortage that affects every SOC is sharper where every analyst also requires clearance and vetting.
Aerospace and mission systems remain in service for decades, frequently past any supported patch path.
Every investigation step and response action must be traceable for governance, accreditation and review, not summarised after the fact.
Autonomous Cyber Defence
Spharaka Sphere™ was built autonomous-first rather than retrofitted, and the on-premises deployment moves the reasoning rather than the interface. AuraXP™, the agentic investigation engine, runs inside the local platform and queries local data stores and entity context directly. SAGE™ is served locally, with local inference. No alert, log, prompt, evidence, embedding or investigation context is sent outside the environment.
The consequence is that autonomy survives disconnection. Investigations, detections and response workflows continue while the environment has no path to the internet. Threat content, parsers, model updates and product upgrades arrive through controlled offline packages, approved transfer media or private update channels, on terms the customer sets.
SAGE™ is deployed and served inside the boundary, so there is no public model API dependency and no external inference call to assess.
AuraXP™ forms competing hypotheses and queries local telemetry to test them, reaching a verdict without any external service.
Detection, investigation and response continue while the environment is cut off, because nothing in the loop depends on connectivity.
Every investigation step, evidence query and response action is traceable for governance, accreditation and review.
Threat content and model updates delivered through approved packages and transfer media rather than an open update channel.
Built in India with full data residency control for every deployment, and cloud agnostic where a cloud is permitted at all.
The AI Cybersecurity Analyst
SAGE™ is Spharaka's proprietary cybersecurity model, fine-tuned from state-of-the-art open foundation models on Spharaka's own cybersecurity datasets, reasoning frameworks and autonomous investigation technology. It is a security reasoning model by design, not a general model adapted for security afterwards.
The distinction that matters in a classified environment is not accuracy but location. A general model brings broad knowledge, shallow security context and inference that usually runs on external infrastructure. SAGE™ is domain-trained, grounded in security reasoning, and runs entirely within the deployment boundary. No investigation data leaves the platform.
Inside that boundary it explains multi-signal detections in plain language, generates competing investigation hypotheses with the evidence that tests each one, interprets obfuscated or decompiled malware, and produces post-incident reports and documentation, which is where cleared analyst time is scarcest.
Natural language investigations
Guided AI-assisted analysis
Root cause reconstruction
Contextual threat intelligence
Accelerated analyst productivity
Executive-friendly explanations
Industry Use Cases
The full detection, investigation and response loop running on a network with no external connectivity of any kind.
Endpoint, identity, network and host telemetry collected and reasoned about entirely within the accredited boundary.
Dormant account misuse, privilege anomalies and off-hours access elevated behaviourally rather than by manual triage.
Vendor and contractor sessions reconstructed and monitored, including first-time geography and unusual session shape.
Long-lived systems assessed passively against the vulnerability catalogue where scanning and agents are not deployable.
Spharaka Signal™ extends the same investigation surface to OT on estates, depots and installations.
Traceable investigation and response records assembled continuously rather than reconstructed for a review.
Tenant-level data separation for organisations running several enclaves that must not share telemetry.
Why Spharaka
Local inference removes reliance on public model providers and external API calls entirely, rather than contracting around them.
Investigations and response continue with the environment disconnected, because the reasoning is inside it.
Built in India, for the world, with full data residency control on every deployment.
AirWatch™ validates every autonomous action against verified evidence and policy, with escalation, deferral and override as first-class controls.
Every step of every investigation is recorded, which is what accreditation and review actually require.
Containment within 60 seconds of confirmation, against an adversary that no longer operates at human pace.
Deployment
Spharaka Sphere™ is engineered for the operational realities of modern enterprises. Whether your infrastructure is fully in the cloud, on-premises, air-gapped for regulatory reasons, or spread across hybrid environments, Sphere deploys where your data lives and where your security teams operate.
Elastic, multi-region cloud deployment for born-in-cloud enterprises.
Full control within your data centre for strict data residency needs.
Isolated environments for regulated, classified, or critical operations.
Unified visibility across cloud, on-prem, and edge in one platform.
Yes. Sphere On-Premises supports on-premises, secure enclave and fully air-gapped deployment. Ingestion, detection, investigation, decision and response all complete inside the customer controlled network, and SAGE™ inference runs locally.
No. SAGE™ is deployed and served locally. No alert, log, prompt, evidence, embedding or investigation context is sent outside the environment, and there is no public model API to call.
Through controlled offline packages, customer approved transfer media or private update channels. The environment stays disconnected and content arrives on terms the customer sets.
Government covers public sector delivery, citizen services and the infrastructure behind them. This page covers disconnected and classified environments, where external model calls and internet access are not acceptable at all and the deployment model is the deciding factor.
AirWatch™ validates every action against verified evidence and customer policy before execution, and prevents unsafe actions while preserving auditability. Humans set the policy boundaries; autonomy acts only within approved scope, and escalation, deferral and override are tunable controls.
No. Autonomous investigation, local SAGE™ reasoning, entity profiling, attack correlation, case summarisation, endpoint visibility through EdgeProtect™ and governed SOAR response are all present. What changes is where each part runs and how content is delivered.
Yes. Spharaka Signal™ monitors industrial and control networks passively and feeds the same investigation surface, so base infrastructure and installation OT do not require a separate platform.
Both. Deployment is customer controlled, and model inference happens inside that same boundary, which is the part most platforms leave outside it.
Book a personalized demonstration of Spharaka Sphere™ and see how AI-native security operations transform detection, investigation, and response for your organization.