Duped integration engineering — composable connector mesh for SaaS teams

Across an estimated 2 million software and digital-native teams, integration work is a repetitive, fragile drag on product velocity: teams spend weeks or months building point-to-point connectors, debugging schema drift, and maintaining brittle glue code while paying an average of roughly $20K per year in integration infra and duplicated engineering effort—a component of what we estimate as a $40.0B addressable market. This problem is especially acute for mid-market and enterprise product teams juggling 10–50 SaaS endpoints and real-time event streams where failures cause customer-visible breakages and slow feature delivery. A viable product is a composable connector mesh: an SDK-first integration runtime with versioned contracts, pluggable adapters, an event-driven backbone, policy and observability primitives, and LLM-assisted schema inference with human-in-loop validation. The timing is favorable—the market scores 92/100 and revenue potential 88/100—because composable SaaS architectures increase integration surface area, AI makes automated mapping realistic, and developers prefer code-first, contract-driven platforms; combined, these trends can plausibly cut implementation time materially (target a conservative 40–60% reduction) and unlock adoption. To stand out you must be developer-centric (code and contracts first), deliver a deterministic runtime with enterprise-grade SLAs, and treat AI mapping as an assist with auditable human review and governance controls. Strengths include alignment with developer preferences and clear ROI if you can prove reliability; challenges are building and maintaining a wide connector surface, earning trust in automated mappings, and competing with established iPaaS players. This idea is worth pursuing if your team can commit 12–24 months to a hardened core runtime, a prioritized set of connectors, and a few pilot enterprise customers to validate ROI and build momentum.