Free tool · 8-factor scorecard

AI Build vs Buy Decision Tool

Get a build / buy / blend recommendation based on data sensitivity, integration depth, time-to-production pressure, internal capacity, and 4 other factors.

1. How sensitive is the data the workflow will touch?

← Buy: Routine / publicRegulated / PHI / NPI: Build →

2. How deep does the AI need to integrate with internal systems?

← Buy: Shallow / standaloneDeep / multi-system: Build →

3. Time-to-production pressure?

← Buy: Need it next quarterCan wait 12+ months: Build →

4. Internal AI engineering capacity?

← Buy: None / minimalStrong existing team: Build →

5. Differentiation: is this workflow your competitive edge?

← Buy: Commodity workflowCore moat / IP: Build →

6. Volume scale?

← Buy: Mid-volume routineHyper-scale / unique pattern: Build →

7. Compliance/audit requirements?

← Buy: Light / standardHeavy regulator scrutiny: Build →

8. Budget profile?

← Buy: Capex-averse, ARR-lightStrong capex, slow ARR: Build →

Recommendation

Blended build + partner

Score: 50/100

Your profile balances build and buy considerations. Common pattern: a partner ships the first production workflow (8-12 weeks), then your internal team takes over operations during Run while the partner stays on architecture-level decisions for 6-12 months.

Quick facts

  • Typical build-in-house lead time: 9–18 months to production. Counts opportunity cost.
  • Typical partner-led lead time: 8–12 weeks to thin-slice production.
  • Best blended pattern: Partner ships v1 (6-10 weeks), internal team owns Run from quarter 2.
  • Hardest factor to assess honestly: internal AI engineering capacity (most teams overestimate by 40-60%).

Talk through the decision

Sometimes the answer changes once we map your actual systems, team, and timeline. 30-min Discovery call to validate the result.

Book a Discovery call →