Overview
Nalvin is an AI assistant that helps product teams keep track of customer feedback, roadmap items, and cross-functional updates without manual work. It connects Attio data with your internal tools so feedback and context stay linked to the right companies and users. Nalvin reads new conversations, support threads, customer notes, and CRM updates, then organizes them into actionable insights for product management and customer success.
With Nalvin active in Attio, teams get a unified view of customer signals and product direction. Feedback automatically attaches to the correct customer records. Product ideas and issues can be tracked through your development workflow. Roadmap updates can be shared back to customer-facing teams so nothing gets lost.
The result is a cleaner workflow for handling feedback, prioritizing work, and staying aligned with customers.
How it works
Nalvin listens to activity across your customer touchpoints and uses Attio as the source of truth for company and user data. Each time customer conversations, meeting notes, support issues, or product feedback appear in your tools, Nalvin analyzes them and links them to the correct Attio records. It also enriches your product development tickets with this context, ensuring your roadmap reflects real customer needs.
As your team works, Nalvin keeps track of progress in Linear or Jira. When something ships or moves forward, Nalvin posts updates back into Attio so customer-facing teams can close the loop. Nalvin also highlights patterns such as recurring feature requests, sentiment shifts, or signals from key customer segments.
All of this happens automatically in the background, without needing to change your team’s workflow.
Configure
Setting up Nalvin with Attio takes less than a minute. Just open the Nalvin integrations page, find Attio, and connect the app. Once connected, Nalvin can read your Attio data, including companies, people, records, and lists.
Nalvin doesn’t modify your CRM data. The only thing it creates inside Attio is notes and tasks, which it uses for posting insights, feedback summaries, and loop-closure updates. Everything else stays read-only.
After connecting, Nalvin starts working immediately. No field mapping, no extra setup.