The operational data layer for AI-driven organizations

Enables full control, automation, and reliability of operational data pipelines feeding analytics and AI, across clouds and enterprise systems.

PROBLEM

AI is only as good as the data behind it

• Data is fragmented across multiple clouds and enterprise applications
• Organizations rely on too many disconnected tools to prepare data
• Slow, unreliable and poorly governed data makes AI slow, risky and inaccurate

WHY NOW

The bottleneck moved from models to data readiness

• GenAI and AI agents require constant, fresh context
• Multi-cloud and SaaS are now the default enterprise reality
• Governance, regulatory and internal audit pressure is increasing

SOLUTION

One platform instead of five

integration, quality, orchestration, analytics readiness

advanexus connects, prepares and governs operational data from multiple clouds and applications, making it ready for analytics and AI.

• No full stack rebuild
• No complex infrastructure redesign
• One operational layer between data sources and AI

HOW IT WORKS

From fragmented data to AI-ready context

POSITIONING

We don’t compete where others win

• Confluent – data in motion
• Databricks / Snowflake – storage & analytics
• advanexus – operational data layer
• Designed to complement existing data stacks, not replace them

VALUE

Productivity beats complexity

• Faster time to value
• Fewer tools and lower cognitive load
• Lower operational and compliance risk
• Clear ownership, traceability and governance

MARKET

Every AI initiative depends on data readiness

• AI-first companies
• Enterprises & regulated industries
• Data teams, integrators & consultants

BUSINESS MODEL

Low entry, high expansion

• SaaS subscription
• Enterprise plans
• Add-ons & premium services
• Expansion via team adoption and enterprise scale

TRACTION

Early validation from real data teams

• AWS demo environment live
• Platform actively used for real-world scenarios
• Validated through real enterprise use-cases and feedback

TEAM

Built by a founder who lived the problem

• Founder with two university degrees and two PhDs
• 2 years in high-performance computing
• 10+ years building systems in complex enterprise environments
• Worked across 6 countries and 9 banks
• Hands-on full-stack development + business ownership
• Supported by an investor/advisor focused on business development and go-to-market

ASK

What we’re building next

• We are raising capital to:
  • Build a dedicated product team
  • Deliver a production-ready, enterprise-grade platform
  • Strengthen security, governance and scalability
  • Prepare go-to-market for enterprise and AI-driven customers
• Goal:
  • Reach a stable production version ready for broader enterprise adoption.