Lab-to-field acceleration for AI, robotics, and advanced security systems
Build. Test. Prove
Product and Application Testing
We stress-test hardware, firmware, and software under adversarial conditions—static/dynamic analysis, fuzzing, SBOM/provenance checks, and red-team abuse cases. Only capabilities that survive hostile inputs, power/EMI faults, and supply-chain scrutiny move forward to deployment.
Drone and Robotics Solutions
We design, integrate, and field-test UAS/UGV platforms with encrypted comms, ISR payloads, and autonomous navigation—then validate them against jamming, spoofing, and counter-UAS tactics. The result is mission-reliable robotics that operate when GPS, networks, or weather don’t cooperate.
Artificial Intelligence Engines
We build and harden AI models for detection, triage, and decision support—edge and cloud—backed by auditable data pipelines and adversarial-robust training. Safety gates, red-team prompting, and model telemetry ensure outputs are reliable under pressure.
Advanced Security Systems
We fuse physical and cyber: access control, video analytics, LPR/biometrics, RF/TSCM, and sensor fusion into a single operating picture. Every system is lab-validated for failover, evidence capture, and rapid response—so facilities act like fortified platforms, not just buildings.
Experimentation and Sandboxing
Isolated ranges and digital twins let us detonate malware, simulate ICS/OT failures, and run purple-team drills without production risk. Snapshots and kill-switch rollbacks keep experiments fast, safe, and repeatable.
Defensive Mitigation Research
We prototype proactive defenses—deception layers, honeytokens, moving-target configurations, zero-trust micro-segmentation, and automated containment playbooks. Findings feed directly into hardened defaults for field deployments.
Development and Integration
We take prototypes to production—engineering modular, secure-by-default systems with CI/CD gated by SAST/DAST, SBOMs, and signed releases. We fuse sensors, platforms, and APIs across edge/on-prem/cloud behind zero-trust and mTLS, delivering IaC-driven deployments with telemetry, runbooks, and instant rollback so capabilities ship fast and stay hardened.
Managed Research and Development (MRD)
Data pipelines, evaluation harnesses, and secure prototyping to move ideas into production
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Signed, governed data pipelines. Ingest only approved sources through signed connectors; encrypt in transit/at rest (mTLS + KMS), auto-classify/strip PII with DLP, enforce least-privilege/ABAC, and record full lineage with immutable audit logs.
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Secure prototyping sandboxes. Spin up ephemeral, isolated labs (namespaced VPCs or air-gapped nodes) via IaC; vault secrets, apply zero-trust network policies, snapshot/rollback on demand, and stream telemetry to your SIEM without exposing customer data.
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Software supply-chain integrity. Generate SBOMs for every build, pin dependencies, sign artifacts and builds (provenance attestation), harden containers/base images, and block promotion on critical CVEs via SAST/DAST/container scans.
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Controlled productionization. Use progressive delivery (canary/feature flags), real-time health and security metrics, drift/anomaly detection, kill-switches with auto-rollback, and operational runbooks/IR playbooks aligned to defined RTO/RPO.
What is Blade Labs, and when should we use it instead of standard engineering?
Blade Labs is our adversarial test and build environment where products, applications, drones/robotics, AI models, and security systems are stress-tested under real attack conditions before fielding. Use Labs when failure has safety, regulatory, or reputational impact—i.e., when you need hard validation, not hopeful deployment.
What do we receive at the end of a Labs engagement?
You get decision-grade artifacts designed for deployment, audit, and exec sign-off, including:
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Threat model & attack path map, with severity scoring and exploitation evidence
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Findings report with prioritized fixes, remediation playbooks, and retest results
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SBOM & provenance (where applicable), signing/attestation notes, and dependency risk
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Operational runbooks (install, rollback, telemetry, alarms, and SLAs)
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Domain-specific packages: flight logs & C2 hardening (UAS/UGV), red-team transcripts & evals (AI), failover/evidence capture configs (security systems)
How do you protect our IP, data, and compliance posture during testing?
We isolate workloads in segmented or air-gapped ranges, enforce least-privilege access, encrypt data at rest/in transit, and maintain full chain-of-custody logging. Engagements run under strict NDA/MSA terms; we default to client-owned data or synthetic datasets and can host on-prem as required. Regulatory controls (e.g., export/sanctions/privacy) are built into workflow gates so experiments don’t become compliance liabilities.
Are drone/robotics, RF, and offensive security experiments safe and legal?
Yes—Labs operations run with documented safety gates and jurisdictional compliance. UAS/UGV work adheres to applicable flight rules and test-range constraints; RF work observes spectrum licensing and deconfliction; and all offensive tooling is confined to controlled sandboxes with explicit authorization scopes. No production networks or live environments are touched without written scope and controls.
How do you move from prototype to production without adding risk?
Our Development & Integration track promotes only what passes gates: CI/CD with SAST/DAST, signed releases, SBOM checks, zero-trust service identities, and observability baked in (health, audit, and security telemetry). We stage pilots with rollback plans, measure MTTD/MTTR deltas, train operators, and hand off hardened defaults so the fielded capability is fast, reproducible, and defensible.