How do you verify remote or field employees are actually working when you can't see them?
I've been building a workforce/attendance tool for the past few months, and the more I talk to other founders and operators, the more I realize this is a genuinely unsolved problem for a lot of small teams.
The core tension: too much oversight (screenshots, constant check-ins) makes good people feel like suspects and quit. Too little oversight means you find out something's wrong months later, usually during a payroll or client audit.
I ended up building something (Trackly) to sit in the middle, GPS-verified check-ins visible to both employee and manager, no hidden tracking. But I'm genuinely unsure if this is the right model, or if there's a better approach other builders here have found.
A few real questions I'd love this community's take on:
If you manage remote or field teams, how do you currently verify attendance or output?
Where do you personally draw the line between accountability and surveillance?
Has anyone here built something similar and found a different approach that worked better?
Replies
This is an interesting problem. Personally, I think the focus should gradually shift from monitoring activity to measuring outcomes. For knowledge workers, constant tracking often creates anxiety without necessarily improving productivity.
For field teams, though, GPS-verified check-ins make sense because location is part of the job.
The key is transparency—employees should always know what is being tracked, when it's being tracked, and why.
One thing I'd be curious about is whether you've considered combining attendance with lightweight proof of work (completed tasks, client acknowledgments, or milestone updates) instead of relying primarily on location. It might provide managers with a better picture of both presence and productivity.
Looking forward to seeing how Trackly evolves!
@kartikbatchu2003Â Really glad you brought up proof-of-work, that's honestly the piece I keep going back and forth on. GPS answers "were they there," but it doesn't say much about what actually got done, and I don't want managers leaning on location as a stand-in for output. Milestone updates or client acknowledgments feel like the right layer to add on top, lightweight enough that it doesn't turn into another task-management system people dread using. Still figuring out the right balance so it stays simple though, curious if you've seen anyone pull this off without it becoming just another thing people have to fill out.
If you ever want to dig deeper into how we're thinking about this, happy to share more, feel free to drop me a line at Shahroz@contactva.com. No pressure either way, just enjoying the conversation.
@shahroz_siddique Thanks, Shahroz! I appreciate the invitation.
I really like the direction you're taking with Trackly. I think there's an interesting opportunity around preserving context, not just attendance or proof of work. It's actually one of the reasons I built ChatHop—I kept losing valuable context in long AI conversations, so I built a way to quickly rediscover the exact discussion behind an idea or decision.
Different use case, but a similar challenge: knowing why something happened is often just as valuable as knowing that it happened.
I'd be happy to continue the discussion over email and exchange ideas. I'll reach out!
@kartikbatchu2003Â Really glad this resonated, and that's a sharp parallel actually, "why something happened" being as important as "that it happened" applies more to Trackly than I initially gave it credit for. Attendance data alone answers presence, but the context behind decisions (why a shift changed, why a task got reassigned) is a gap I hadn't fully thought through until you framed it that way.
Would genuinely enjoy comparing notes, sounds like ChatHop and Trackly are solving the same underlying problem from two different angles. Talk soon over email!
on the accountability vs surveillance line, I think it's less about what data gets collected and more about who triggers the check and when they find out about it. a GPS check-in the employee taps themselves, that's visible to them the same moment it's visible to the manager, feels completely different from a system quietly pinging location in the background, even if the underlying data point is identical. the silent version is what makes people feel like suspects, not the location data itself. also, this feels like it genuinely fits field/delivery roles where location is inherently part of the job, I'd be more skeptical if you tried to sell the same model to a team of remote knowledge workers where presence and output aren't the same thing
@galdayan That distinction, who triggers it and when they find out, is sharper than how I'd been framing it. You're right that the silent version is what actually breeds distrust, not the data point itself. Trackly's check-ins are employee-triggered for exactly that reason, tap in, tap out, visible instantly on both sides, but I hadn't quite put language to why that specific mechanic matters versus passive tracking until you said it.
And agreed on the knowledge-worker caveat too, that's actually the boundary I try to be upfront about. Field and delivery roles, presence is the job. Remote knowledge work, presence tells you almost nothing about output, so the same model would be the wrong tool there.
@shahroz_siddique that's a good boundary to hold. one edge case though: what stops someone from tapping in and then just leaving for the rest of the shift? is there any passive signal after the initial check-in, or is it fully trust-based once they've tapped themselves in once
@galdayan Fair catch, that's the actual gap in a purely tap-based model. Trackly does have periodic check-ins/screenshots through the shift (not just at start), but always visible to the employee in real time, so it's not silent monitoring, just verification that isn't a one-time tap and forget. Still trust-based in spirit, employees know exactly when and what's being checked, but it's not "tap in once and disappear."