From AI Tools to a System of Action

THE SITUATION

A global data connectivity leader built AI productivity use cases across sales, finance, and customer success, QBR generation, pre-meeting templates, content creation, and Voice of Customer analysis. The initiative stalled. Adoption on the chosen platform was low, and a migration to a more user-friendly alternative revealed a second problem: agents existed, but nobody could find them. Users created duplicates. The agent library sat underutilised. And the original platform was costing 3x more than its replacement without delivering proportional value.

THE SOLUTION

GrowthArc assessed the full AI stack before recommending anything. The diagnosis separated the platform problem from the adoption problem. Rather than prescribing another vendor, we designed a custom, tech-agnostic orchestration layer that unified fragmented tools into a governed execution system. Glean continued as the enterprise knowledge layer. Workato handled deterministic automation. The orchestrator sat above both, routing queries, planning execution, and invoking the right agents without requiring users to know which agents existed.

WHAT WE BUILT

A custom AI agent orchestration layer hosted on Google Cloud Run, powered by Gemini models via Vertex AI. Google Redis Memorystore handled session memory. Google BigQuery supported long-term retention. Slack became the single unified interface. The orchestrator handled query understanding, on-the-fly execution planning, and agent invocation, all through natural language. No specialist knowledge required.

THE OUTCOME

Enterprise AI at this global data connectivity leader moved from assistive productivity tools into a governed, reusable system of action. By January 2026, 305 users had executed 1,748 queries with a 95% CSAT score. The nature of those queries had changed materially, from single-step, assistant-led interactions to autonomous, multi-step, cross-system execution. The orchestration layer is platform-agnostic and built to absorb new agents, new tools, and new use cases as AI maturity grows, without requiring a rebuild.

FUTURE OUTLOOK

The foundation is set for expanding autonomous execution across more functions. A discoverable agent library, a governed orchestration layer, and a user base that has already demonstrated willingness to engage, when the experience is designed correctly, positions this as a long-term system of AI coordination, not a point solution.