Agentic AI Safety Research with Agent Bulkhead
We are providing resources and practical expertise to support Agent Bulkhead's work in agentic safety and AI research, bringing a production perspective to the design of safer AI systems.
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Longer-form writing from active projects across Graylark LRM, InsightMesh, Graylark Polyglot, EU AI Act classification, and enterprise-safe autonomous execution supporting Graylark Technologies.
We are providing resources and practical expertise to support Agent Bulkhead's work in agentic safety and AI research, bringing a production perspective to the design of safer AI systems.
Read articleDeployer obligations for high-risk workplace AI translated into system requirements: provenance-grade logging, human oversight as UX, worker notification workflows, and change management with a loop in it.
Read articleThe Pay Transparency Directive as a data brief: equal-value categories as data modelling, pay assembly across fragmented systems, small-group discipline, and reproducible runs that survive scrutiny.
Read articleWhy we built our own automated compliance-evidence and penetration-testing framework instead of buying a platform - and why continuous, evidence-based proof can stand alongside a once-a-year external pen test.
Read articleHow we built autonomous training infrastructure using autoresearch, knowledge distillation, and structured legal training data to produce domain-specific LLMs for European labour relations.
Read articleHow we integrated MCP into Graylark LRM with tenant-safe access, dual-mode authentication, and production-grade audit and governance controls.
Read articleHow we connect change context, historic outcomes, legal advisories, and proprietary models into grounded country-level intelligence.
Read articleWhy we built Graylark LRM, what is technically novel, and how we deliver controlled AI across complex labour-relations workflows.
Read articleWhy multilingual enterprise delivery needs domain context, and how Polyglot reduces translation time and cost for Graylark LRM.
Read articleHow we approach model training, fine-tuning, uncertainty control, and low-latency inference for high-volume governance workflows.
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