Deadlights combines configurable AI security software with practical architecture and secure gateway implementation—helping small and midmarket teams move from pilot to production without losing visibility, policy, or control.
Deadlights is being built as a product-and-services company. The software creates a configurable security control layer; professional services turn architecture decisions into a working, supportable system.
Classify workload intent, apply security policy, protect sensitive information, route to approved models, and record decisions across local, private, and external AI services.
Explore the platform vision →Get focused AI/LLM architecture and secure AI gateway implementation from practitioners who can design, integrate, validate, document, and hand off the result.
Review professional services →Start with the business problem—not a predetermined product stack. Deadlights connects governance, data protection, identity, routing, observability, and delivery into one practical architecture.
Establish approved access paths, workload profiles, model choices, and security controls for employees, applications, developers, and agents.
Integrate identity, DLP, data security, observability, SIEM, model providers, and custom services instead of adding another isolated security silo.
Resolve architecture, governance, resilience, audit, operating ownership, and implementation details that commonly stop AI initiatives before production.
Web chat, developer assistance, and agentic workflows do not have the same risk, latency, model-quality, data, or tool-access requirements. Profiles make those differences explicit and enforceable.
Deadlights engagements are structured around small, testable increments. Decisions are documented, configuration is validated, operational owners are prepared, and the final result is designed to survive beyond the engagement.
Clarify use cases, stakeholders, data, controls, constraints, risks, and success criteria.
Define trust boundaries, workload profiles, policy decisions, integrations, and deployment patterns.
Configure, integrate, automate, test, and demonstrate the selected architecture.
Deliver evidence, runbooks, ownership, knowledge transfer, and a production-ready handoff.
Enterprise-quality thinking, practical implementation, and software that can adapt to the way the environment actually works.
Focused at the intersection of model platforms, data protection, identity, infrastructure, and security operations.
Profiles, policy, deployment choices, and integrations are shaped around the customer.
Existing controls become part of the solution through deliberate APIs, telemetry, identity, and workflows.
Architecture and implementation stay connected, producing testable outcomes and ownership.
Initial content helps decision-makers and practitioners understand secure AI architecture, governance, and the controls required to reach production.
Architecture, controls, and deployment patterns.
Read →Translate policy into accountable controls and measurable progress.
Read →Security controls organizations commonly miss.
Read →Discuss your use cases, constraints, existing controls, and practical path toward secure production adoption.