AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Area Baciu.com
A communications plan for AI incidents covering internal escalation, customer updates, regulatory notice, and postmortems.
Partiamo dal processo, dagli utenti e dai rischi prima di scegliere l'architettura misurabile più semplice.
Apri paginaUn buon sistema mantiene fonti, valutazioni, telemetria e regole di escalation.
Apri paginaEspansione del tema
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Apri paginaA control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Apri paginaA starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Apri paginaA production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Apri paginaA board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
Apri paginaA tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
Apri paginaA practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
Apri paginaA structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.
Apri 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.
Atlante di delivery
Filtra, confronta e apri pagine dettagliate su architettura, esecuzione e governance AI.
Libreria di implementazione
A finance model for attributing AI runtime cost by workflow, department, customer segment, provider, and outcome.
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 technical specification for AI-callable tools covering schema, permissions, idempotency, retries, and audit trails.
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.
Modelli di trasferimento per passare con sicurezza dal supporto dell'implementazione alle operazioni di proprietà del cliente.
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.
Design and enablement solutions for defining agent behavior, permissions, tests, release controls, and handoff workflows.
Laboratorio di esecuzione
Regola ritmo, autonomia e profilo di rischio per vedere fasi, dipendenze e controlli consigliati.
Fasi consigliate
Nessun recupero senza disciplina della fonte
La fiducia è una caratteristica del prodotto
Azione con responsabilità
Ogni versione guadagna fiducia
Controlla dove si svolge il lavoro
I team dei clienti possono operare in modo indipendente
Radar capacità
Scegli prospettiva operativa e orizzonte per vedere tracce, segnali e pagine decisionali correlate.
Tracce prioritarie
AI spend tied to operating value
Apri paginaStrategia con un percorso di implementazione
Apri paginaLa governance nel ciclo di consegna
Apri paginaConsegna progettata per una proprietà durevole
Apri paginaControlla dove si svolge il lavoro
Apri paginaPiano di esecuzione
Ogni area viene consegnata con definizione esplicita, validazione misurabile e governance operativa trasferibile al team cliente.
Stabilize quality, cost, and latency before scaling adoption.
Apri paginaRun explicit operating rituals through implementation and handoff.
Apri paginaDesign control surfaces before broad autonomous behavior.
Apri paginaChecklist operativa
A clear system map covering models, tools, data, workflows, users, and failure modes.
Apri paginaTask sets, regression checks, and release criteria for measurable AI behavior.
Apri paginaHuman approval, access, logging, data-boundary, and incident-response rules.
Apri paginaDocumentation and ownership so the client can operate the system after launch.
Apri paginaInizia con flussi di lavoro ripetitivi e reversibili in cui è possibile misurare i risultati e i limiti degli errori.
Utilizza set di valutazione, scenari contraddittori e criteri espliciti go/no-go legati all'impatto aziendale.
Con limiti di autorità, soglie di confidenza, pacchetti di escalation e tracce di esecuzione complete.
Tratta le modifiche al modello e alle richieste come versioni: testa, rivedi, approva e implementa con percorsi di rollback.
Mappa di copertura
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Apri paginaA control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Apri paginaA starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Apri paginaA production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Apri paginaPagine utili
Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.
Apri paginaA scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Apri paginaA control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Apri pagina