Labour Relations Intelligence
Decision-support methods for workplace change, consultation, and employee relations across complex enterprise environments.
RESEARCH
Applied AI research for enterprise labour relations and decision intelligence.
Our research is driven by real delivery: Graylark LRM, the InsightMesh framework, KAI, Polyglot Batch, TaskForge, and our EU AI Act classifier work. We focus on secure, grounded, multilingual systems that support high-stakes enterprise decisions.
Current research tracks
InsightMesh Graph Reasoning
Entity-linked insight graph construction connecting change context, historic outcomes, legal advisories, and proprietary models.
EU AI Act Classification Modeling
Model training and fine-tuning pipelines for fast, consistent AI Act classification across high-volume use cases.
Policy Knowledge Assistants
Secure HR knowledge delivery research powering KAI, including grounded retrieval, policy attribution, and safe response behavior.
Multilingual Batch Translation
Domain-aware contextual translation research for high-accuracy, end-of-day batched localization workflows.
Autonomous Task Execution
Long-horizon orchestration research for TaskForge, converting Jira and Markdown task definitions into completed outputs.
Grounded Regeneration
Controlled regeneration pipelines that refresh answers with updated evidence while preserving traceability and consistency.
Enterprise AI Safety + Evaluation
Evaluation suites for country-specific accuracy, compliance alignment, latency, and reliability before production deployment.
RESEARCH METHOD
Product-led loops with measurable evidence.
Every research track maps directly to production systems and customer-facing outcomes.
- Define high-impact enterprise decisions and formalize them into measurable AI tasks.
- Assemble country-aware datasets from policy artifacts, legal advisories, and historical outcomes.
- Train, fine-tune, and evaluate models for grounded accuracy, speed, and safety under real workload constraints.
- Ship validated capabilities into LRM, InsightMesh, KAI, Polyglot Batch, and TaskForge without exposing client data to shared-model training.