Alexis Lee

We chose MongoDB for thegro.ai because modern outbound data isn’t clean or predictable — it’s dynamic, layered, and constantly evolving. From enriched lead profiles to campaign signals and CRM activity, we needed a flexible schema that could adapt as our product grows. MongoDB gives us the speed, scalability, and structure we need to handle complex AI-driven workflows without rigid constraints.

We chose AWS Cloud for thegro.ai because reliability and scale aren’t optional when you’re building an AI Sales Co-Pilot. From day one, we needed infrastructure that could handle high-volume outbound workflows, real-time data enrichment, and secure CRM integrations without compromise. AWS gives us the flexibility to scale fast, maintain strong security standards, and deploy globally as we expand across markets.

We chose Gemini 3 for thegro.ai because we needed more than text generation — we needed reasoning. Across real outbound workflows (lead research, prioritization, structured outputs, and human-sounding outreach), Gemini consistently handled long context and multi-step logic better than the alternatives we tested. It gave us strong performance, predictable formatting for Gro IQ, and a cost profile that makes scaling a self-serve AI Sales Co-Pilot viable. For us, it wasn’t about hype — it was about building on a foundation that thinks clearly at scale.

We needed production-ready authentication without slowing the team down. Clerk let us ship securely from day one and stay focused on core product work. Setup was fast, UX is polished out of the box, and it scales cleanly without us constantly revisiting edge cases.

As a lean team, speed mattered. Vercel let us go from commit to production in minutes. Setup was faster, deployments were more reliable, and preview environments made collaboration dramatically easier. It let us move fast without cutting corners. Less time on infra, more time building the product.