We help the people responsible for the implementation of tools and processes find out what exactly needs to improve for employees to get productive in their daily workflow.

To measure an AI tool’s impact on productivity, we analyze specific activities, or “work moments,” where AI can play a role, such as writing code or reviewing pull requests for a software developer. For each activity in employees’ daily workflow, we measure: Time spent (where applicable) Satisfaction scores with the specific activity in the daily workflow Effort and quality score Satisfaction scores with tools, processes or people they interact with to get the activity done

The timeframe for getting a survey set up and go live is typically between a few days and a few weeks. If the customer is using our own survey capability, the results are automatically processed and displayed in FOUNT dashboards as the data comes in.

Today, most companies rely on generic engagement surveys, focus groups, or data from tools provided by vendors. These methods often fail to give a clear picture of what’s really happening in employees’ daily work. The feedback tends to be broad and subjective, leaving leaders without actionable insights. Current approaches also struggle to prioritize which challenges need immediate attention, and they don’t show how these issues impact productivity or ROI. As a result, leaders end up with data that’s hard to act on and miss opportunities to make meaningful improvements. We use an activity-based framework to measure effort level, time spent and experience of workers doing their work, with minimal employee disruption. This is much more precise than a typical engagement survey or a satisfaction survey sent by AI tools themselves, because it digs deep into people’s day-to-day workflow, making the data more actionable.