
ServiceRocket's global solutions architecture team manages a high volume of customer engagements, each requiring discovery calls, tailored proposals, and clean handoffs to project managers. Before adopting Auctor, the team relied on a patchwork of tools: AI assistants that could process transcripts but couldn't produce finished documents; editing platforms with no awareness of customer context; and manual workflows stitching the two together. The result was slow, fragmented, and prone to losing critical detail along the way.
By consolidating statement of work (SOW) generation, editing, and context into a single platform, Auctor addressed the team's core friction. Where the old workflow required jumping between tools and manually transferring output, everything now lives in one place, with full awareness of the customer context at every step.
Meeting preparation, previously one of the most time-consuming parts of the engagement cycle, became more efficient. Instead of reviewing full recordings of prior sales calls to prepare for a discovery session, the team can now query Auctor's chat to surface key concerns, open questions, and relevant history in minutes.
"Before my first discovery call, I can use the chat to pull out key pieces of information," says Scott Spinali, Solutions Architect at ServiceRocket.
"I can ask it questions like, 'What are the customer's largest concerns?' based on previous calls and be prepared with those answers and related questions. That prep now takes a couple of minutes rather than watching a whole half-hour call and manually extracting details."
ServiceRocket's engagements often share structural similarities, including common assumptions, solution patterns, and delivery approaches, even when the specific scope differs. Rather than manually cutting and pasting content from past proposals, the team can now pull that material and have Auctor reshape it automatically for a new customer's context.
"I can reuse assumptions and solution approaches we've prepared for other customers and quickly insert them into a proposal," Spinali said.
Once a deal closes, project managers can query Auctor's chat for engagement history rather than hunting through scattered documents, keeping institutional knowledge intact during transitions. This reduces the need for synchronous knowledge-transfer meetings and ensures new team members don’t ask the customer the same questions twice.
"It preserves the context for the project managers who carry the project forward after signing, and that's been a big help," said Spinali.