Tagsight vs an in-house P&ID extraction team
Operating companies sometimes stand up a dedicated in-house team to digitize legacy drawings and produce I/O lists for a multi-year brownfield programme. Some of them are great at it. Most get sucked into transcription work that doesn't match the engineering pay grade.
At a glance · Capital and ramp time
Pay-per-use credit model. First output produced the same day the team signs up. No headcount, no procurement, no training cycle.
Hiring 3-4 mid-level I&C engineers takes 6-12 months in most labor markets, plus 3 months of standardization before output is consistent.
Read one of your own drawings.
Drop a P&ID, instrument index, or schedule. Tagsight reads it to the tag and opens a workspace you keep when you sign in.
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Comparison.
| Axis | Tagsight | Alternative |
|---|---|---|
| Capital and ramp time | Pay-per-use credit model. First output produced the same day the team signs up. No headcount, no procurement, no training cycle. | Hiring 3-4 mid-level I&C engineers takes 6-12 months in most labor markets, plus 3 months of standardization before output is consistent. |
| Knowledge concentration | Every extracted artifact carries metadata. Institutional knowledge lives in the data, not in any one person's head. Team turnover does not erase project context. | When the senior engineer leaves, the convention chart, the cabinet-numbering rule, and the half-built MOC checklist leave with them. |
| Throughput at peak | Multiple drawing sets run in parallel. The bottleneck is review, not extraction. | Throughput is gated by the number of engineers on the bench. Adding capacity for a peak month is impossible at hiring timescales. |
| Quality and consistency | Same classification logic on every drawing, tunable per company convention. Variance is reviewable. | Variance across engineers is real. Two senior engineers will tag the same loop differently if the company convention is ambiguous. |
Capital and ramp time
Pay-per-use credit model. First output produced the same day the team signs up. No headcount, no procurement, no training cycle.
Hiring 3-4 mid-level I&C engineers takes 6-12 months in most labor markets, plus 3 months of standardization before output is consistent.
Knowledge concentration
Every extracted artifact carries metadata. Institutional knowledge lives in the data, not in any one person's head. Team turnover does not erase project context.
When the senior engineer leaves, the convention chart, the cabinet-numbering rule, and the half-built MOC checklist leave with them.
Throughput at peak
Multiple drawing sets run in parallel. The bottleneck is review, not extraction.
Throughput is gated by the number of engineers on the bench. Adding capacity for a peak month is impossible at hiring timescales.
Quality and consistency
Same classification logic on every drawing, tunable per company convention. Variance is reviewable.
Variance across engineers is real. Two senior engineers will tag the same loop differently if the company convention is ambiguous.
When this is the right call.
- Drawing volume is too lumpy to justify steady-state headcount
- Brownfield program has a 6-24 month sprint with a long tail of MOC after
- You want institutional knowledge to live in queryable data, not in spreadsheets owned by individuals
- Existing in-house team is good but bottlenecked on transcription work that frees them up for higher-value engineering
When it is not the right call.
- You have a ten-year stable run-rate of extraction work and no peak-trough variance
- Local labor market is cheap and dedicated headcount is cheaper than tooling at scale
FAQ.
Does Tagsight replace the in-house team.
Most operating companies use Tagsight as a tool the in-house team runs, not as a replacement. The team uses the time it would have spent transcribing on the engineering work that actually requires their judgment. Exception handling, edge cases, vendor coordination.
What is the right size of in-house team for a brownfield program if Tagsight is in the workflow.
1-2 senior engineers handling review and exception handling, plus 1 PM. The 3-4 transcribing engineers a manual workflow needs become unnecessary.