From feedback chaos to self-orchestrating operations
Product data doesn't improve products. Closed loops do.
Intelligence that operates the feedback loop. Not monitors it.
End-to-end product operations with intelligence embedded at every layer
Product support intelligence
AI agents analyze support interactions to surface patterns that matter—what's blocking adoption, where workflows break, which capabilities are missing. Not ticket counts—intelligence showing recurring friction and high-impact gaps. Product roadmaps informed by operational reality, prioritized automatically.
Usage intelligence that triggers action
AI agents monitor product telemetry continuously—detecting adoption stalls, feature abandonment, and workflow friction in real-time. When customers struggle, interventions trigger automatically. Onboarding sequences adjust. Feature discovery gets guided. Adoption accelerates because AI identifies and eliminates blockers before customers disengage.
Defect and quality feedback loops
AI-powered quality feedback loops analyze telemetry, error patterns, and performance signals continuously. Defects flagged before customers encounter them. Root cause analysis automated. Fixes prioritized by impact, not ticket volume. Engineering learns what's breaking in production before support queues explode.
Time-to-value acceleration
AI identifies adoption blockers systematically—where onboarding breaks, which features confuse, what complexity causes abandonment. Friction removed continuously. Flows optimized based on what works. Customers reach value faster every quarter because intelligence eliminates obstacles in real-time.
Intelligence connecting product performance directly to operational execution.
01
Product Data Fabric
Every support ticket, usage event, defect, and adoption signal — unified. One source of truth connecting product performance to operational execution.
02
Embedded AI Agents
Intelligence that analyzes support patterns, identifies usage drop-offs, prioritizes defects, and tracks adoption. Operating inside workflows, not generating reports.
03
Feedback Loop Architecture
Built to close loops automatically. Quality rising. Adoption accelerating. Time-to-value declining. By design, not by sprint retrospective.
Anchored where product velocity and quality determine market position
High-Tech / SaaS
Product quality directly impacts retention and expansion. Intelligence embedded in design, development, testing, and adoption operations—ensuring what ships drives value, not churn.
Telecom
Network infrastructure and platform reliability are non-negotiable. Intelligence connecting service performance to product development—defects caught before customer impact, features built based on operational reality.
What this looks like in practice
Fintech Leader Accelerates Market Expansion Through QA CoE
Device testing and quality engineering CoE enables synchronized POS validation across eight markets with AI.
Global enterprises slash RPA migration time by 80% with Agentic AI-powered migrAIte
Accelerated migration cycles. Reduced manual effort. Scalable, reliable automation transition across complex environments.
Global media agency migrates automation bots from UiPath to Power Automate at scale
Faster bot migration. Reduced operational friction. Streamlined automation continuity across enterprise workflows.
