Sagheer Labs builds an inline network appliance that detects threats using behavioral AI — no cloud connection, no data egress, no exceptions. For defense, energy, and critical infrastructure operators who are legally prohibited from sending telemetry outside their perimeter.
Defense agencies, critical infrastructure operators, and regulated finance networks are legally prohibited from sending telemetry to the cloud. UAE PDPL, EU NIS2, and US DoD regulations explicitly mandate that sensitive operational data remain within national borders and organizational perimeters.
Cloud-native security vendors like CrowdStrike, Palo Alto, and Zscaler require data egress to function. For regulated buyers, this is not a missing feature — it is a structural disqualifier. The result: operators deploy outdated signature-based IDS boxes while attackers exploit the detection gap with lateral movement, DNS tunneling, and encrypted command-and-control traffic.
Detection Gap
Cloud-dependent tools cannot enter the perimeter. Passive sensors cannot stop what they see.
National regulations prohibit cloud telemetry from classified and OT networks. Data localization is no longer optional.
Modern AI security tools assume outbound connectivity. They cannot operate without it.
Existing air-gapped solutions rely on passive monitoring. They miss behavioral anomalies and cannot block threats in real time.
A single-rack physical appliance that sits between your perimeter router and core switch. All traffic passes through it. Three layers of defense operate entirely within your air-gapped perimeter.
Field-programmable gate array handles known threats at the hardware level. DDoS, SYN floods, port scans, known C2 IPs — dropped in sub-millisecond timeframes. 10–25 Gbps sustained throughput. Zero CPU overhead for 99% of traffic.
Quantized behavioral neural network on a local GPU cluster analyzes flow metadata. Detects lateral movement, DNS tunneling, encrypted exfiltration. 192 GB VRAM supports models up to Llama 3.1 405B and DeepSeek — all running entirely on-device. Target: <0.1% false positive rate.
Local LLM analyst correlates anomalies into incidents. MITRE-mapped reports, SOAR tickets, breach notifications — all generated on-device. Self-hosted inference. Forensic packet capture. Zero cloud telemetry.
Intel TDX + ARM CCA + TPM 2.0. Model weights encrypted in memory. Tamper detection triggers automatic key zeroization. TPM attestation verifies integrity on every boot. Your models and your data never exist in plaintext.
Proprietary protocol for appliances to share encrypted model-weight deltas. No raw traffic ever leaves the perimeter. The fleet learns collectively without centralizing sensitive data. Isolated sites benefit from global threat intelligence without compromising their air-gap.
Signed physical media or local bastion servers deliver threat intelligence, retrained models, and firmware patches. Full operation maintained without any outbound connection. Designed for environments where USB is the only data path.
We occupy a specific intersection that no single vendor currently serves: inline FPGA-accelerated behavioral AI for air-gapped OT/ICS environments.
Classified networks require Common Criteria EAL4+ and zero data egress. Our appliance meets both requirements with TPM attestation, encrypted model weights, and no outbound connections.
Power grids, water treatment, and oil/gas facilities face a 24% CAGR in targeted attacks. Behavioral AI detects anomalies in SCADA and other industrial protocols that signature-based tools miss entirely.
Central banks and sovereign wealth funds operate isolated trading and settlement networks. Our appliance provides SOC-grade detection without violating data residency mandates.
National agencies require FIPS 140-3 and NIAP compliance. Our certification roadmap targets these standards from day one, with architecture designed for evaluation readiness.
We are 17 and 18 years old, which means we did not adapt to AI. We grew up inside it.
Co-Founder & Co-CTO — GTM, Systems Architecture, Sales
Spent a year at Kai Dubai shipping production AI voice agents for real estate lead generation, taking models from Jupyter notebooks to live customer calls. Now studies cybersecurity at Curtin University. Has trained multiple custom AI models for side projects. Bridges technology and deployment.
LinkedInCo-Founder & Co-CTO — AI/ML Research, Detection Pipeline
Completed a year-long cybersecurity course and actively researches adversarial AI and edge inference. Focuses on machine learning and network protocols. Has built neural networks, broken them, and hardened them. Brings the AI/ML depth to the detection pipeline.
LinkedInSee how Sagheer Labs can secure your air-gapped environment. No cloud required.