Your process.Rebuilt with AI.Proven together.

No. Many of our engagements start exactly there. The AI Jumpstart exists so your first move is a measured decision, not an experiment: in 2-3 weeks it identifies the workflows in your operation where AI would pay for itself and what it would take. You do not need an AI team, a data strategy, or a pilot behind you - you need one workflow worth improving and the people who know how it runs today.

No. Architech brings the AI engineering, and the same team carries the work from first scope through to production. Your side contributes the people who know the work: an executive sponsor and one or two operational owners, typically 8 to 12 hours of their time in total across the first 2-3 weeks.

Both statements are true: most AI projects never prove their impact, and AI is already producing measured results in real operations - 35% faster resolution, documents and approvals completed 60% faster, and 3x faster information retrieval in workflows we have taken to production, measured against each organization's own starting point. The difference is not the technology. It is picking a workflow where impact can be measured, and measuring it. That is why every engagement starts there.

No. You do not need a data program before starting - you need the pattern for safe access, and that is designed as part of the work. The AI Foundations Blueprint defines the secure access pattern in 2-3 weeks, proves it against real operational data, and produces the AI Reference Architecture every subsequent workflow reuses. Inside Workflow Transformation, the Blueprint's first week verifies the chosen workflow's system and data requirements before anything is built.

Each stage is time-boxed. The AI Jumpstart runs 2-3 weeks and ends with the process to start on and the number to beat. The Transformation Blueprint runs 3 weeks and ends with the plan, the measurement baseline, and the Build's fixed price. The Build follows: simple processes go live in weeks, more complex ones within 90 days. Most organizations see their first measured result in live operation within 5-7 weeks.

The right entry point depends on where the work has stalled. Approved roadmap with no plan to deploy → Transformation Blueprint. Security, governance, or data access blocking the work → the AI Foundations Blueprint. Workflows shipped but KPIs slipping → Outcome Assurance. Licences bought without measurable ROI → Jumpstart reframes the problem around workflow outcomes, not tools.

Evaluation is tied to your business KPI, not model behaviour. A model can score high on relevance and groundedness while cost-per-resolution drifts back to baseline. Architech builds a Golden Dataset of real queries and verified expected outputs with your SMEs, tests semantic behaviour, structural integrity, and end-to-end correctness independently, runs the dataset on a defined cadence, and adds every regression back so it cannot recur. Drift is caught in engineering before it surfaces in the P&L.

No. The Jumpstart is optional - organizations that already know their workflow start directly at the Transformation Blueprint. The AI Foundations Blueprint stands outside the stages entirely and runs before or in parallel. Within Workflow Transformation, the Blueprint and the Build are two gated phases of one engagement: the plan stands on its own, and the Build is committed only after you accept it. Outcome Assurance runs continuously after deployment - it is a discipline, not a stage.

The entry points are fixed-scope: AI Jumpstart starts at $24,100, the Transformation Blueprint at $28,300, and the standalone AI Foundations Blueprint at $9,900. The Transformation Blueprint is success-based: acceptance criteria are confirmed in Week 1, and if outcomes are not accepted at the end, no fee is charged. Production builds and ongoing work are priced to scope once the plan is set - the Blueprint produces the Build's fixed number. All prices are in Canadian dollars and exclude applicable HST. Full details are on the Pricing page.

They are one engagement in two gated phases, committed separately. The Blueprint produces a decision-ready plan and the Build's fixed price, and it stands on its own. The Build follows only when you accept the Blueprint, using the same architecture, baselines, and acceptance criteria. There is no upfront commitment to the full arc.

Most enterprise AI projects miss their KPIs by month six. Outcome Assurance is the discipline that prevents it: continuous evaluation tied to your KPI, a Golden Dataset that grows across the engagement lifecycle, regression sets that prevent recurrence, and a dedicated team accountable for the outcome metric month-over-month. The number on the P&L holds for as long as you own the workflow.

The AI Foundations Blueprint addresses these directly. Two to three weeks, senior-led, ending in a documented security posture, an access pattern proven against real operational data, the AI Reference Architecture, an executive go/no-go decision, and a priced implementation plan for any gaps. Identity, role-based access, audit traceability, and data residency are scoped explicitly. Capital is committed against evidence, not architecture diagrams.

Architech builds. The blueprints produce decision-ready plans; Architech delivers the production builds that follow, with one team carrying through from scoping to scale. No handoffs, no rotating consultants, no lost context.