Travis Capps

QUIN | Query-driven Unified Intelligence Network Role: Founder, Product Architect, UX/UI Designer & Full-Stack Engineer Developed by: knXw Labs Website: https://www.twine.net/signin The Challenge Cybersecurity investigations require analysts to navigate fragmented search engines, intelligence databases, infrastructure records, and specialized research tools. Manually constructing queries, correlating evidence, and validating relationships consumes valuable time and increases the risk of incomplete or misleading findings. The challenge was to unify these capabilities into an intelligent, evidence-driven investigation platform. The Solution I conceived, architected, designed, and developed QUIN, an AI-assisted OSINT and cybersecurity intelligence platform that transforms natural-language investigations into structured research workflows. QUIN combines multi-engine query translation, live intelligence collection, evidence-backed relationship analysis, and specialized investigation tools within a unified interface. Key Capabilities Natural-Language Investigation: Convert research objectives into structured queries and executable investigation plans. Multi-Engine Query Translation: Generate specialized search syntax for Google, Bing, Shodan, Censys, GitHub, and other research platforms. Live OSINT Collection: Retrieve infrastructure evidence through DNS-over-HTTPS, certificate transparency, RDAP, and Internet Archive CDX. Nexus Graph: Visualize relationships between digital assets using evidence-backed observations. Infrastructure Intelligence: Investigate domains, certificates, hosting relationships, and exposed digital assets. 12 Specialized Modules: Access query planning, validation, live collectors, attack-surface research, and OSINT launchers. Security Playbooks: Support Red Team, Blue Team, and Purple Team investigation methodologies. Evidence Integrity: Separate verified source observations from heuristic suggestions and external research launchers. Technical Architecture & Engineering I led product strategy, UX/UI design, technical architecture, full-stack engineering, AI integration, and quality assurance.

• AI Developer
• Product Designer
• Project Manager
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GasGarda | Intelligent Gas Safety & Remote Shut-Off Role: IoT Solutions Architecture, Software Engineering & Systems Integration Client: Planet Safety Systems Technologies Website: https://www.twine.net/signin The Challenge Natural gas infrastructure demands reliable monitoring and rapid emergency response. Undetected gas leaks, carbon monoxide exposure, equipment failures, and delayed intervention can threaten lives, property, and critical infrastructure. The challenge was to integrate wireless sensing, intelligent monitoring, and automated control into a scalable safety system capable of detecting hazardous conditions and supporting timely intervention. The Solution I contributed to the technical architecture, software engineering, and systems integration of GasGarda, an Industrial Internet of Things (IIoT) gas safety platform developed by Planet Safety Systems. GasGarda integrates wireless environmental sensors, industrial gateways, remote monitoring, and connected control equipment to identify hazardous conditions and support automated or remotely initiated safety responses. Key Capabilities Gas & Environmental Detection: Wireless monitoring of carbon monoxide (CO), hydrogen sulfide (H₂S), and other environmental conditions. Automated Safety Controls: Trigger connected relays and control devices when predefined conditions are detected. Remote Gas Shut-Off: Support remote gas isolation through integrated valve-control systems. Wireless Telemetry: Long-range wireless sensor networks connected through industrial and 4G LTE gateways. SCADA & PLC Integration: Modbus RS-232/RS-485 connectivity with existing industrial infrastructure. Real-Time Monitoring: Centralized sensor reporting, equipment status, and configurable alerts. Distributed Infrastructure: Architecture supporting residential, commercial, industrial, and utility applications. Technical Architecture & Engineering My work involved connecting physical sensing infrastructure with software-driven monitoring and control systems, addressing device communication, system integration, telemetry, and operational reliability. The architecture incorporates wireless sensor networks, cellular gateways, industrial communication protocols, cloud connectivity, and automated control logic. Operational Workflow: Detect → Communicate → Evaluate → Respond → Monitor Outcome & Vision GasGarda demonstrates how connected hardware, industrial software, and intelligent automation can work together to improve visibility and response capabilities across safety-critical environments. The technology has potential applications in natural gas utilities, industrial facilities, commercial buildings, distributed infrastructure, and automated environmental safety systems. Explore: https://www.twine.net/signin

• AI Developer
• Product Designer
• Project Manager
• +2

knXw | The Missing Intelligence Layer Role: Founder, Product Architect, UX/UI Designer & Full-Stack Engineer Project: https://www.twine.net/signin Developed by: knXw Labs The Challenge Traditional analytics platforms track what users do but rarely explain why. Businesses struggle to understand user intent, hesitation, confidence, and decision-making behavior, resulting in static digital experiences, unnecessary friction, and missed opportunities for engagement. The Solution I conceived, architected, designed, and developed knXw, an AI-powered behavioral and psychographic intelligence platform that enables software applications to interpret human behavior and adapt intelligently in real time. knXw acts as an intelligence layer between user interactions and application logic, transforming behavioral signals into contextual insights, explainable recommendations, and adaptive user experiences. Key Capabilities Behavioral Intelligence: Analyze real-time interactions, engagement patterns, hesitation, and user intent. Psychographic Inference: Estimate motivations, confidence, preferences, and decision-making tendencies from behavioral evidence. Adaptive UI: Enable applications to personalize interfaces, messaging, and user journeys dynamically. AI-Powered Recommendations: Generate contextual interventions supported by explainable reasoning. Predictive Analytics: Identify engagement trends, potential friction, and churn indicators. Developer SDK & APIs: Integrate behavioral intelligence into existing software products. Governance & Transparency: Support auditable AI decisions, user controls, and responsible data handling. Product Design & Engineering I led the complete product lifecycle, including concept development, product strategy, UX/UI design, technical architecture, AI orchestration, full-stack engineering, and API/SDK development. The system follows a four-stage intelligence architecture: Sense → Infer → Adapt → Govern This modular approach connects behavioral data collection, AI-assisted interpretation, contextual adaptation, and transparent decision governance. Outcome & Vision knXw establishes a foundation for more intelligent, responsive digital experiences, with potential applications across SaaS, e-commerce, enterprise software, education, customer engagement, and digital marketing. The long-term vision is to make contextual behavioral intelligence an accessible infrastructure layer for modern applications, enabling software to understand user needs, reduce friction, and deliver increasingly relevant experiences. Explore: https://www.twine.net/signin

• AI Developer
• Product Designer
• Project Manager
• +2