A sequential pipeline, from readiness to production
Four tightly integrated products mapping to the natural progression of enterprise AI adoption.
Enter at any stage. Validated work carries forward through to production — on your chosen platform, with security and responsible AI built in.
AI Readiness Assessment
2 days · Fixed fee
A structured advisory engagement that evaluates your data infrastructure and technical readiness for AI investment — independent of any cloud provider. Two structured interviews (executive and technical) feed an internal analysis, delivered as a readout with a clear go / proceed with conditions / not yet recommendation. It deliberately does not generate use cases — that is the focus of the Ideation Workshop.
Executive AI investment recommendation: go / proceed with conditions / not yet
Data & infrastructure readiness gap analysis with prioritized remediation
Build-vs-buy recommendation aligned with your existing or preferred platform
Ideation & Use Case Workshop
3 days · Fixed fee
An intensive, design-thinking-driven facilitated engagement that brings cross-functional stakeholders together to generate, score and prioritize AI use cases — human needs first, not another strategy slide deck. You leave with a scored, investment-ready backlog and a post-workshop technical analysis from Templefield.
Scored, stakeholder-aligned use case backlog: business impact × technical feasibility
Business value and ROI framing with an executive-ready prioritization roadmap
Technical analysis covering architecture, effort, data readiness and GDPR & EU AI Act considerations
Proof of Concept & MVP Delivery
Up to 8 weeks · Milestone-based
A focused, production-oriented implementation sprint that validates a high-priority use case with real data against defined KPIs — a functional system in your target environment, not a demo. Scope and KPIs are fixed in Week 1 and held throughout: no scope creep, no time-and-material surprises.
Scope-fixed working solution built with real data in your target environment
KPI evaluation report measured against predefined business outcomes
Handover package with architecture documentation, code repository and scaling roadmap
Productionization & MLOps Engineering
8 weeks – 12 months
Most AI projects fail not at the PoC stage but in the transition to production. This service re-engineers validated prototypes into robust, scalable, compliant production systems: ML pipelines, model serving, CI/CD and operational monitoring — on a cloud-agnostic stack, with GDPR, EU AI Act and enterprise security embedded by design, not retrofitted.
Batch and streaming data pipelines with automated training and retraining workflows
Scalable model serving, CI/CD and monitoring for drift, data quality and system health
Audit-ready security, GDPR & EU AI Act compliance, documentation and operational handover
Not sure where you are in the journey?
Start with a 2-day Readiness Assessment. Each product accepts prior-stage outputs — or your own artifacts — as its starting point.