Advancing emerging technology and AI for the good of secure communities

Building tomorrow’s security and resilience—responsibly.

366 Labs is a science and technology development corporation focused on research, prototyping, and applied innovation that strengthens community safety, continuity, and critical infrastructure. We work at the intersection of AI, systems engineering, and human-centered design—prioritizing privacy, transparency, and operational integrity.

Start a conversation How we work Trust & governance

AI-assisted decision support Secure-by-design engineering Privacy-preserving analytics Field-ready prototyping

What we deliver R&D to prototype

We translate emerging science into deployable capability—without hype, without lock-in, and without exposing sensitive communities to unnecessary risk.

Applied research Evaluations, red-teaming, and feasibility studies for emerging technology in real-world contexts.

Prototype development Rapid builds for decision support, situational awareness, and secure operations workflows.

Responsible AI integration Model selection, guardrails, observability, and governance aligned to mission risk tolerance.

Mission

Strengthen security and resilience across communities by accelerating safe, ethical, and practical technology adoption.

Why 366 Labs

Complex threats do not respect organizational boundaries. Community safety requires coordination, high-integrity information flows, and tools that reduce friction under stress. We develop technology that helps teams move from uncertainty to action—while preserving civil liberties and operational trust.

We do not publicize specific operational initiatives on this site. Our work is intentionally described at a capability level.

What “secure communities” means

Preparedness, continuity, and recovery for disruptions to daily life.
Safer public spaces through better sensing, communication, and coordination.
Reduced systemic risk across critical services and infrastructure.
Decision advantage for responders—without sacrificing privacy.

Our default stance is “minimize collection, maximize value,” with strong access controls and auditability.

Focus areas

Our R&D portfolio concentrates on cross-cutting capabilities that can be adapted across jurisdictions, environments, and operating models.

AI for situational understanding

Multi-source fusion, summarization, and confidence-aware insights designed to reduce cognitive load while improving traceability and human oversight.

Privacy-preserving analytics

Methods that prioritize minimization and protection: on-device processing, encrypted workflows, differential privacy strategies, and secure auditing patterns.

Secure communications & coordination

Resilient message routing, role-based access, integrity checks, and operational workflows that maintain continuity when networks are degraded.

Edge computing & field systems

Lightweight, ruggedized architectures for constrained environments—balancing performance, reliability, and maintainability with a security-first posture.

Model evaluation & assurance

Benchmarking, red-teaming, drift detection, and guardrails that align AI behavior with mission needs, regulatory constraints, and stakeholder expectations.

Human-centered operational design

Interfaces and procedures built for high-stakes environments—clear handoffs, explainable outputs, and controls that keep humans meaningfully in the loop.

How we work

A disciplined path from concept to capability—optimized for speed, safety, and stakeholder trust.

Define the mission problem Clarify outcomes, constraints, data realities, and risk tolerance. Define what “good” looks like in the field.

Design for security and governance Threat modeling, access control patterns, audit trails, and privacy posture established before build-out.

Prototype and evaluate Rapid iteration with measurable performance, failure analysis, and human factors validation.

Operationalize responsibly Deployment playbooks, monitoring, model lifecycle management, and training aligned to real-world operations.

Trust, ethics, and governance

Security technology must be worthy of public trust. We engineer safeguards into the system—not as an afterthought.

Core commitments

Accountability by design: audit logs, reproducibility, and clear ownership.
Human oversight: AI outputs are decision support, not decision authority.
Data minimization: collect less, protect more, retain only as necessary.
Security-first engineering: threat modeling, least privilege, secure defaults.
Transparency: communicate limitations, uncertainty, and appropriate use.

Where appropriate, we support third-party review, evaluation frameworks, and policy alignment.

Responsible AI posture

Emerging models are powerful, but they are not magic. They can hallucinate, drift, and embed bias. We emphasize measurable performance, explicit uncertainty handling, and robust guardrails:

Evaluation suites tailored to mission scenarios and failure modes
Adversarial testing and prompt/agent hardening
Observability for model behavior, latency, and safety events
Fallback modes that preserve operations when AI is degraded

Our default recommendation is to deploy the least-complex solution that meets the operational requirement.

Contact

If you are exploring emerging technology and AI to improve community security, continuity, or coordination, we can help scope a responsible path forward.

Send an inquiry

This form is a front-end demo. Wire it to your preferred email or CRM endpoint when you deploy.

What to include

Operating context (urban, rural, campus, industrial, remote)
Primary outcome (reduce response time, improve coordination, strengthen continuity)
Constraints (privacy, policy, budget, staffing, connectivity, data access)
Risk posture (acceptable failure modes and guardrail requirements)

We can support exploratory discovery, feasibility studies, and prototype development for stakeholders who require high-integrity outcomes.