Discovery & requirements intelligence
Capture signals, stakeholder input and system context as structured discovery material — and draft requirements grounded in what the organisation already knows.
Demetra product
PDLC Intelligence Platform
Turn product knowledge into coordinated execution.
PDLC Intelligence Platform is an agentic product development platform. Specialised AI agents work across discovery, requirements, refinement, planning, stakeholder decisions and delivery insight — grounded in your product context and connected to the tools you already use.
Product work is fragmented by default
The product development lifecycle runs across tools, teams and meetings — and loses context at every boundary.
- Requirements are scattered across tickets, documents, boards and chat threads, with no single view of what has been agreed.
- Refinement is repeated manually for every story, by every team, with uneven quality.
- Context is lost in the hand-offs between stakeholders, product and engineering.
- Decisions are made in meetings and buried in minutes — the same questions resurface weeks later.
- Traceability from an idea to what actually shipped is reconstructed after the fact, if at all.
One intelligence layer across the lifecycle
The platform connects discovery, requirements, refinement, planning, stakeholder decisions and delivery insight into coordinated workflows. Specialised agents operate across the stages, drawing on a shared base of product knowledge — so context created in discovery is still available, and still linked, at delivery. It is not another ticket tracker: it is the intelligence and orchestration layer that works across tools like Jira, rather than replacing them.
What the platform does
Refinement & planning
Draft and refine stories and requirements against your definition of ready. Keep planning workflows structured and consistent, independent of individual habits.
Stakeholder & decision intelligence
Collect and synthesise stakeholder input. Keep decision logs that preserve the reasoning alongside the outcome, so decisions stay consistent and reusable.
Reusable product knowledge
Turn scattered product knowledge into reusable AI capabilities: terminology, rules, templates and workflows that agents apply the same way every time.
Delivery & release insights
Trace requirements into engineering execution. Follow what shipped, what changed and why — with links back to the decisions and inputs behind it.
How the agents work together
Each agent has a role, product context and a defined place in a workflow. Agents hand work to each other with the context attached: a discovery agent feeds the requirements agent, refinement raises open questions for stakeholders, and decisions flow back into the knowledge base that every agent draws on.
Role-specialised
Agents are purpose-built for product-management and business-analysis work.
Context-grounded
Agents operate on your product knowledge, terminology and rules from the first interaction.
Workflow-native
Agents work inside coordinated workflows with defined inputs, outputs and hand-offs.
Works with your product ecosystem
The platform connects to the tools where product work already happens, and moves context between them: a stakeholder thread in Slack informs a requirement in Jira; a decision references the Confluence page and the Figma design it was based on; delivery insight draws on engineering activity in GitHub.
- Jira
- Confluence
- Figma
- Slack
- Miro
- GitHub
Adapted to your product operating model
The platform’s building blocks are configured and extended around how your organisation actually develops products:
- Workflows mapped to your lifecycle stages and governance gates
- Agent roles aligned with how your product, analysis and delivery roles divide the work
- Templates and rules that encode your definition of ready, standards and terminology
- Integrations and knowledge sources connected to your existing ecosystem
Built around your product operating model
PDLC Intelligence Platform is configured around your product processes, knowledge sources, collaboration tools and governance requirements. Depending on enterprise requirements, the platform can be deployed into a customer-controlled environment or delivered through an agreed managed deployment model. Agents, workflows and integrations can be adapted to the organisation’s terminology, lifecycle and decision processes.
The exact deployment and integration architecture is confirmed during solution discovery.
From stakeholder input to engineering-ready work
A representative workflow — the same pattern applies from discovery through delivery.
Stakeholder input
A workshop outcome, a Slack thread and support feedback are captured as structured discovery input.
Requirement & refinement
The requirements agent drafts a structured requirement with acceptance criteria, grounded in existing product rules and terminology.
Decision context
Open questions are routed to the right stakeholders; the decision and its reasoning are logged and linked.
Engineering-ready output
A refined, traceable work item lands in Jira — linked to the decision, the design and the original input.
REQ-214 · Refined
Corporate customers can delegate account access
Acceptance criteria
- An account owner can grant and revoke delegate access per workspace
- Delegate actions are recorded in the audit log with the acting identity
- Existing sessions lose access within one minute of revocation
Linked context
Decision D-58 · Figma flow · 3 stakeholder inputs · 2 product rules
Evaluate it against your own workflow
The fastest way to evaluate the platform is a working session on one of your real product workflows — your tools, your terminology, your governance requirements.