How we structure serious GenAI delivery.
A clear commercial path from readiness to operated platform: assessment, discovery, then production build with acceptance gates. Scope and commercial terms are confirmed after a short brief — not published as rate cards.
Production Readiness Assessment
Clarify readiness, risk, architecture options, and the first production path before you scale spend.
- Use-case prioritization
- Risk and constraint map
- Architecture options
- Go / no-go recommendation
- Suggested first production path
Discovery sprint
A structured discovery that produces a platform map, acceptance backlog, and commercial delivery plan.
- Platform map
- Acceptance criteria backlog
- Technical approach
- Risk notes
- Commercial delivery plan
Platform build
Build production systems against explicit quality and release gates — progress tied to accepted outcomes, not open-ended hours.
- Measurable accepted stories
- Evaluation gates
- Ops handoff package
- Vendor-neutral architecture
- Scoped after discovery
Pricing is scoped to your use case, constraints, and acceptance criteria. Request an assessment or discovery to receive a concrete commercial plan.
A buying model that reduces AI delivery ambiguity.
Enterprise AI work fails when scope is vague and quality is subjective. The Thest model makes both visible before scale.
Clarity before scale
Assessment and discovery reduce ambiguity so leadership funds a path with known risks, acceptance criteria, and ownership — not another open-ended pilot.
Accepted delivery
Build work maps to stories that meet explicit acceptance criteria. Commercial progress stays tied to measurable outcomes, not vague effort.
Ownership transfer
Engagements are designed so your team can operate and extend the system after handoff — runbooks, monitoring, and enablement included in the delivery model.
Not sure which engagement fits?
Most teams start with a Production Readiness Assessment. We recommend discovery or platform build only when the path is clear.