We bring dedicated AI product management across the full lifecycle — from strategy and ownership to governance and delivery.
AI Product Strategy
We build the product vision and roadmap for AI-based systems — translating business objectives into model strategies, feature priorities, and go-to-market sequencing for AI products
Agentic AI Product Management
End-to-end product ownership for agentic AI applications — designing multi-agent workflows, defining agent responsibilities, and managing the full lifecycle from prototype to production deployment.
LLM Application PM
Specialised product management for LLM-based applications — prompt strategy, evaluation frameworks, context window design, model selection, and iterative improvement pipelines.
Business & AI Opportunity Analysis
We map your business processes, identify where AI creates real product value, and build the business case — surfacing high-impact use cases backed by feasibility analysis and ROI modelling.
End-to-End Project Management
Full lifecycle delivery management for AI system builds — sprint planning, stakeholder alignment, resource coordination, risk management, and quality gates from kickoff to release.
AI Governance & Responsible AI
Product-level governance for AI systems — fairness assessments, explainability requirements, safety testing, compliance mapping, and the product practices that make AI trustworthy in production.
IcicleLabs is a research-led AI product management company — a small group of researchers, product managers, and AI engineers working at the intersection of applied AI research and real product delivery.
A four-step engagement model built around deep domain understanding, honest AI leverage mapping, and full product ownership through to production.
Understand the product domain
We map your existing workflows, team structure, data landscape, and competitive context — building real domain knowledge before making any product recommendations.
Identify AI leverage points
We surface where AI — whether LLM features, agentic workflows, or predictive systems — creates the most product value, and where it doesn't. We're honest about both.
Design & own the AI product
We take full product ownership — roadmap, backlog, stakeholder alignment, sprint management — treating the AI system as a product with its own quality metrics and iteration cycle.
Ship, measure, improve
We instrument the AI system, define the right product metrics, and run continuous improvement cycles — using production data to drive model updates and feature decisions.
From research synthesis to agentic pipelines — our stack is fully AI-native across all layers of the work.
We work with leading universities and industry organisations on applied AI research, product innovation, and responsible AI development.
Interested in a research collaboration?
Get in touch →Our research on AI product management, agentic systems, and responsible AI.
Whether you need product management for a new AI system, a strategy review for an existing one, or a research collaboration — we're a small team and we take on work selectively.