ShiftCurve Lab
Active R&DHonest positioning. Everything here is categorised by actual readiness - not marketing optimism. In Production means real users and real output. In Build means active development with weekly iterations. In Research means we understand the problem deeply and have working prototypes.
Live systems with real users, real data, and real output.
AI-powered Assessment of Environmental Effects reports for resource consent applications. Compiles intelligence from GIS databases, District Plan rules, and property data into polished council-ready documents. Not templates - each report is generated from compiled intelligence specific to the site and application.
End-to-end website, SEO, and content delivery for professional services firms. AI reinforcement loop optimises Google Ads daily - auto-pruning wasted spend, blocking bad clicks, and learning what converts. Live clients generating leads from day one.
Actively under development with real users testing iteratively.
Purpose-built town planning workspace. Contact management, council status tracking with RMA milestones, GIS property mapping across 5 councils with Esri satellite imagery, LINZ parcel boundaries, zone overlays, flood zones, and 3 Waters infrastructure. Fee proposals with PDF generation and cadence engine for follow-ups. Phase 3 of 5 complete - real users, real data, iterating weekly.
Working prototypes and deep domain understanding. Production-grade delivery is the engagement itself.
Performance attribution for fund managers. Demo exists with working calculation engine. The real challenge is the data trust layer - reconciliation across custodian, PMS, and risk systems, pipeline reliability, and fund manager adoption. We understand this problem deeply because we have sat in that chair.
Signal aggregation and synthesis across market data sources. Functional internally for our own operations - needs significant work on the data layer for enterprise reliability and scale.
Enterprise buyers detect vapourware instantly. Calling something "In Build" when the hard problems are not solved erodes trust the moment someone asks a technical question. Calling it "In Research" with a working prototype and deep domain understanding is stronger - it says we know exactly how hard this is, and we will not pretend otherwise.
The CRM is the proof point. Phase 3 complete, real users, real data, iterating weekly. That is what delivery looks like.