A curated set of reusable templates—checklists, interview scripts, ROI models, and planning worksheets—to speed AI audits, pilots, vendor evaluations, and roadmaps.
A curated, downloadable library of practical templates — interviews, ROI models, project plans, dashboards, and checklists — designed to accelerate AI initiatives and reduce duplicated effort across teams.
A practical, organized starter pack of reusable templates, checklists, calculators, and worksheets teams can copy and adapt to plan, pilot, and scale AI initiatives — with guidance on how to use each artifact and suggested next steps for onboarding a team to an AI project.
A practical, ready-to-adapt toolkit of templates for scoping, estimating, piloting, and handing off AI work: stakeholder interview script, ROI calculator, pilot project plan, engineering handoff checklist, and user onboarding checklist.
A ready-to-run, guided interview form with differentiated question sets for executives, domain experts, frontline staff, and customers plus structured note capture, an outcome-framing section, and a quick scoring rubric. Submissions are saved for later affinity mapping and use-case hypothesis generation.
A practical, copyable collection of reference architectures for common AI use cases (chat assistants, retrieval-augmented generation, classification pipelines, forecasting, and edge inference). Each pattern includes a concise architecture diagram (placeholder), component responsibilities, example tech stacks, runnable implementation notes, test cases, and a production-readiness checklist designed to shorten time-to-production.
Concrete, runnable reference architectures and recommended components for four common AI patterns: chat assistants, retrieval‑augmented generation (RAG), classification pipelines, and forecasting pipelines. Each pattern includes architecture components, low-friction implementation recipe, recommended technologies, monitoring and validation checkpoints, security considerations, and quick adaptation guidance so teams can copy, run, and tailor a working solution.
Interactive checklist and scorecard for evaluating AI vendors and third-party models. Includes structured fields for technical fit, model provenance, security, data handling, SLAs, liability/indemnity, exit/portability, sandbox testing, weighted scoring, and a final recommendation.