Skyrocket AI

We had a great experience with Skyrocket. They took time to understand how our agency operates and identified our biggest pain points—the manual review of quotes, policies, and endorsements. This wasn't a straightforward AI project, but their team handled the complexity well. They were thoughtful and organized throughout, translating the technical work into something practical that our staff could actually use. The final product directly addressed our operational needs and delivered real value to our business.

Working with Skyrocket AI, their team communicated proactively and translated our technical needs into practical results that improved our workflow and online presence. They understood what we needed for AI integration in our marketing work and delivered exactly what they promised.

Working with Skyrocket AI was a very different experience than working with standard "no-code" AI vendors. From the initial discovery phase, it was clear that they prioritize the technical architecture over flashy UI. They didn't just give us a generic chatbot; they mapped out our internal workflows and built agents that actually understood the nuances of our advertising data. The integration phase was thorough. They handled the API connections with our existing tech stack (HubSpot and Google Ads) with zero downtime. Since the rollout, we’ve seen a 30% reduction in time spent on administrative reporting. The founder-led approach they mention on their profile is real, we had direct access to their lead architects during the critical deployment week, which made a huge difference in how quickly we could iterate on the lead-scoring logic.

The experience was Refreshingly high-touch. As a CEO, I’ve seen many agencies promise the world with AI but fail on the execution of the "boring" stuff, infrastructure and reliability. Skyrocket AI focused on the engineering first. Every milestone was led directly by the founder, which gave us the senior-level confidence we needed for a $50k+ investment. They were particularly skilled at model optimization. Our initial RAG tests had high latency, but they refactored the deployment on our AWS stack to ensure the response times were viable for live client meetings. It wasn't just about the code; it was about ensuring the AI aligned with our business outcomes. We now have a stable, high-concurrency system that our team actually trusts.