Systemic Punk

Innovate

Transform your business with cutting-edge innovation

We build enterprise-ready disruptive startups fast—using AI-native workflows, milestone funding, and hybrid expert teams to turn top opportunities into validated, scalable products in weeks.

Each venture is shaped by deep execution experience from both startups and enterprises, ensuring strategic alignment, technical robustness, and real-world scalability from day one.

01

Opportunity Discovery & Problem Validation

• AI-driven market & trend scanning
• Automated opportunity scoring
• Rapid customer interviews & pain-point mapping
• Competitive + regulatory scan using AI synthesis
• Alignment with enterprise strategy & BU needs
• Define validated problem statements + value hypotheses
02

Concept Ideation & Solution Design

• AI-assisted ideation & solution sketching
• Generate variants of business models & pricing
• Early feasibility checks (tech, data, compliance)
• Fast mockups with reusable UI & logic components
• Validate desirability with small customer samples
• Select 1–2 strongest solution concepts
03

Prototype & MVP Development

• Low–high fidelity prototypes using shared design system
• AI-generated flows, logic, and content
• Build MVP using reusable auth, connectors, AI agents, analytics
• Technical feasibility tests in sandbox environment
• Pilot readiness checks + leading KPI definition
04

Pilot & Market Validation

• Launch MVP pilot with selected customers/BUs
• Track adoption, engagement, activation, retention
• Validate willingness to pay & ROI signals
• Optimize pricing & operating model
• Refine product using AI-driven feedback clustering
• Prepare scaled business case + next-stage investment ask
05

Scale-Up, Integration, or Spin-Out

• Full product build with composable modules
• Enterprise integration (IT, security, data, ops)
• Expand GTM channels & customer acquisition
• Formalize long-term ownership model (BU, venture arm, spin-out)
• Scale team with internal/ external/ AI talent blend
• Continuous improvement cycles using AI analytics