Pilots succeed in friendly corners; scale exposes data, support, and behaviour gaps. We define explicit exit criteria for pilots, what must be true before the next wave, and how support and governance scale with user growth. The aim is to avoid the common trap: a celebrated POC followed by a stalled enterprise mandate.
How we typically help
- ·Pilot review and scale criteria definition
- ·Sequenced rollout design with realistic dependencies
- ·Readiness gates before expanding audience or use cases
Outcomes we work toward
- ·A documented path from pilot to wave-based rollout
- ·Readiness checks that prevent premature scale
- ·Confidence from sponsors that the next tranche is fundable and defensible
How engagements typically run
Often triggered at pilot mid-point or end — intensive working sessions with delivery, risk, and business owners to lock scale criteria and sequencing.
Example engagements
Representative situations where organisations apply this service — patterns we see across sectors and geographies.
- ·Checklist: SSO, logging, DLP, helpdesk tier-1 scripts, manager training completion rates.
- ·Kill / pivot criteria if adoption or error rates breach thresholds.
- ·Financial model for scale including inference cost and support FTE.
Indonesia and ASEAN context
Indonesian marketplace / tech company post-pilot
A gen-AI assistant for merchants worked in Jakarta beta; support load and Bahasa informal-language edge cases spiked when the pilot widened. We define scale gates on latency, human handoff rates, and content safety, sequence expansion by merchant tier and region, and align product marketing with realistic capability claims — protecting trust with sellers and consumers.