AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Baciu.com servicegebied
A technical specification for AI-callable tools covering schema, permissions, idempotency, retries, and audit trails.
We starten met proces, gebruikers en faalmodi voordat we de kleinste meetbare architectuur kiezen.
Bekijk paginaEen goed AI-systeem bewaart bronnen, evaluaties, telemetrie en escalatieregels.
Bekijk paginaOnderwerpsuitbreiding
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Bekijk paginaA control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Bekijk paginaA starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Bekijk paginaA production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Bekijk paginaA board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
Bekijk paginaA tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
Bekijk paginaA practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
Bekijk paginaA structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.
Bekijk paginaUse this document as the starting point for a workshop, operating review, or delivery handoff.
Resource library
Use these outlines as starting points for assessments, runbooks, governance reviews, and executive planning.
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Leveringsatlas
Filter, vergelijk en open detailpagina’s voor AI-architectuur, uitvoering en governance.
Implementatiebibliotheek
A finance model for attributing AI runtime cost by workflow, department, customer segment, provider, and outcome.
A communications plan for AI incidents covering internal escalation, customer updates, regulatory notice, and postmortems.
A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
A review outline for documenting AI data handling, retention, subprocessors, residency, and customer control requirements.
A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
A service-level objective template for AI latency, quality, cost, availability, escalation, and degraded-mode behavior.
A risk register for tracking AI authority, reversibility, sensitive data exposure, failure modes, mitigations, and owners.
A dashboard outline for monitoring provider mix, cost drift, latency budgets, fallback rates, and quality regressions.
A source inventory for mapping owners, freshness, permissions, quality issues, retention rules, and ingestion priority.
A release-gate template that connects evaluation results, known regressions, approval decisions, rollback, and launch notes.
A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
A steering-committee packet for connecting AI portfolio decisions to milestones, risks, spend, and operating outcomes.
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
A policy template for defining which AI decisions require approval, who approves them, and what evidence is required.
A decision tree for routing between models, cached answers, degraded mode, escalation, and temporary shutdown.
A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
A workbook for translating organizational roles into retrieval, tool-use, approval, logging, and audit permissions.
An adoption plan for moving AI services from launch to measurable usage, feedback, training, and continuous improvement.
A handoff checklist for moving AI systems from delivery into operated services with owners, runbooks, controls, and evidence.
A release review checklist for prompt, policy, model, and tool changes before they reach production users.
A scenario catalog for testing prompt injection, unsafe tool use, data leakage, policy bypass, and recovery behavior.
An audit worksheet for checking cited answers against source text, permissions, freshness, and reviewer corrections.
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
An ownership map for knowledge sources, refresh cadence, permission rules, source quality, and escalation contacts.
A review worksheet for validating AI-callable tool scopes, sensitive actions, audit trails, and approval thresholds.
A scorecard for comparing model and platform vendors across quality, latency, cost, security, support, and lock-in risk.
A calculator outline for estimating automation value from cycle time, error rate, labor mix, risk reduction, and adoption.
A structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.
Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.
A services practice for organizations that need AI systems designed, evaluated, shipped, and operated with accountability.
Use-case patterns for access requests, entitlement review, policy checks, approval packets, and identity-workflow support.
Permission models for deciding what agents may read, draft, recommend, approve, execute, and escalate.
Release patterns for moving agents from prototype to monitored, supported, measurable production services.
Een gecontroleerde omgeving voor het ontwerpen, testen en beheren van herbruikbare middelen voordat ze in productie gaan.
Design and enablement solutions for defining agent behavior, permissions, tests, release controls, and handoff workflows.
Uitvoeringslab
Stel tempo, autonomie en risicoprofiel in om aanbevolen fasen, afhankelijkheden en controles te bekijken.
Aanbevolen fasen
Geen terugvinding zonder brondiscipline
Vertrouwen is een productkenmerk
Actie met verantwoordelijkheid
Elke release verdient vertrouwen
Controle waar het werk gebeurt
Klantteams kunnen zelfstandig opereren
Capaciteitenradar
Kies perspectief en horizon om relevante trajecten, signalen en beslissingspagina's te bekijken.
Prioritaire trajecten
AI spend tied to operating value
Pagina openenStrategie met een implementatietraject
Pagina openenGovernance in de leveringslus
Pagina openenLevering ontworpen voor duurzaam eigendom
Pagina openenControle waar het werk gebeurt
Pagina openenUitvoeringsplan
Elk gebied wordt geleverd met expliciete definitie, meetbare validatie en operationele governance die klantteams kunnen overnemen.
Operationele checklist
A clear system map covering models, tools, data, workflows, users, and failure modes.
Bekijk paginaTask sets, regression checks, and release criteria for measurable AI behavior.
Bekijk paginaHuman approval, access, logging, data-boundary, and incident-response rules.
Bekijk paginaDocumentation and ownership so the client can operate the system after launch.
Bekijk paginaBegin met repetitieve, omkeerbare workflows waarin resultaten en faalgrenzen kunnen worden gemeten.
Gebruik evaluatiesets, vijandige scenario's en expliciete go/no-go-criteria die verband houden met de zakelijke impact.
Met autoriteitsgrenzen, vertrouwensdrempels, escalatiepakketten en volledige uitvoeringssporen.
Behandel model- en promptwijzigingen als releases: test, beoordeel, keur goed en implementeer met rollback-paden.
Dekkingskaart
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Bekijk paginaA control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Bekijk paginaA starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Bekijk paginaA production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Bekijk paginaRelevante pagina's
Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.
Bekijk paginaA scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Bekijk paginaA control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Bekijk pagina