The Product Portfolio OS
for agentic enterprises
Achieve agentic speed with operating cohesion — Dragonboat provides an ontology-based foundation, live context, and intelligent apps for executives, teams, and agents to orchestrate strategy, investments, and PDLC with clarity at scale.
AI speed tears apart strategic intent without the right system
Intent decays from leaders to teams and agents, across tools. AI speeds up the cycle; agents operate on different versions of truth — expanding disconnect and wasted investment.
The Product Portfolio OS for the Agentic Enterprise
Dragonboat is an active, ontology-native platform built for modern product organizations, with domain expertise encoded at its core and elasticity for your evolving operating model. It enables executives, teams, and agents to collaborate across the PDLC, in-app or via connected tool stacks, with clarity, speed, and cohesion.
Clarity — across leaders, teams, and tools
Millions of signals. One unified portfolio reality. Your ontology.
A source of truth connecting strategy, execution, outcomes – with ambient agents continuously detecting, ingesting, and converting heterogeneous data, from both Dragonboat Apps and enterprise tools, into shared semantics in real time, orchestrating across disconnected data and tools into a live layer of meaning, context, and memory.
Speed — with Apps for your entire PDLC
Built-in apps and headless access for humans and agents.
Executives and builders act through built-in AI-powered apps — Strategy, Intake, Planner, Roadmap, and PDLC — or headless via APIs, MCP, agents, and integrated tools. All operate on a shared ontology, enabling faster decisions, tighter execution loops, and seamless movement from intent to outcomes.
Cohesion — Runtime Intelligence with context
Context Graph with encoded logic. Surface consequences.
Ambient agents traverse the portfolio graph across every decision, action, and outcome — surfacing ripple effects, upstream and downstream impacts, and bidirectional consequences in real-time, delivering thematic insights and predictive recommendations grounded in portfolio context, logic, and intent.