Baciu.com service area

Post-launch adoption plan

An adoption plan for moving AI services from launch to measurable usage, feedback, training, and continuous improvement.

How we approach it

We start with the business process, the users, and the failure modes. Then we choose the smallest architecture that can be measured, reviewed, and operated safely.

What good looks like

A good AI system leaves traces: source evidence, evaluation history, cost and latency telemetry, and clear escalation rules for the cases that should not be automated.

Readiness before autonomy

Score business value, data readiness, action safety, evaluation coverage, and operational ownership.
Separate assistant workflows from agentic workflows before authority expands.
Turn weak scores into specific remediation work instead of vague risk notes.

Subject expansion

Pages that drill deeper into this delivery surface

AI readiness scorecard

A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.

Governance control matrix

A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.

Retrieval evaluation set

A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.

Model operations runbook

A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.

Executive AI roadmap brief

A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.

AI incident tabletop

A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.

Agent operating model

A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.

Workflow intake template

A structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.

Delivery artifact

Post-launch adoption plan

Use this document as the starting point for a workshop, operating review, or delivery handoff.

Format: Adoption planPhase: Scale

Download outline

Resource library

Delivery artifacts that make the site operational, not just informational.

Use these outlines as starting points for assessments, runbooks, governance reviews, and executive planning.

30artifacts

10phases

29formats

WorksheetAssess

AI readiness scorecard

A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.

Open page Download outline

MatrixGovern

Governance control matrix

A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.

Open page Download outline

Eval setValidate

Retrieval evaluation set

A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.

Open page Download outline

Delivery atlas

Advanced navigator for capabilities, programs, and systems.

Filter, compare, and jump into detailed pages for AI architecture, execution, and governance.

Implementation library

learnOperate

Agent cost allocation model

A finance model for attributing AI runtime cost by workflow, department, customer segment, provider, and outcome.

learnHarden

Agent incident communications plan

A communications plan for AI incidents covering internal escalation, customer updates, regulatory notice, and postmortems.

learnGovern

Agent operating model

A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.

learnSecure

AI data processing addendum

A review outline for documenting AI data handling, retention, subprocessors, residency, and customer control requirements.

learnHarden

AI incident tabletop

A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.

learnAssess

AI readiness scorecard

A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.

learnOperate

AI service SLO template

A service-level objective template for AI latency, quality, cost, availability, escalation, and degraded-mode behavior.

learnGovern

Autonomy risk register

A risk register for tracking AI authority, reversibility, sensitive data exposure, failure modes, mitigations, and owners.

learnOperate

Cost and latency dashboard

A dashboard outline for monitoring provider mix, cost drift, latency budgets, fallback rates, and quality regressions.

learnPrepare

Data source inventory

A source inventory for mapping owners, freshness, permissions, quality issues, retention rules, and ingestion priority.

learnValidate

Evaluation release gate

A release-gate template that connects evaluation results, known regressions, approval decisions, rollback, and launch notes.

learnPlan

Executive AI roadmap brief

A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.

learnPlan

Executive steering pack

A steering-committee packet for connecting AI portfolio decisions to milestones, risks, spend, and operating outcomes.

learnGovern

Governance control matrix

A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.

learnGovern

Human approval policy

A policy template for defining which AI decisions require approval, who approves them, and what evidence is required.

learnOperate

Model fallback decision tree

A decision tree for routing between models, cached answers, degraded mode, escalation, and temporary shutdown.

learnOperate

Model operations runbook

A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.

learnSecure

Permission model workbook

A workbook for translating organizational roles into retrieval, tool-use, approval, logging, and audit permissions.

learnHarden

Production handoff checklist

A handoff checklist for moving AI systems from delivery into operated services with owners, runbooks, controls, and evidence.

learnValidate

Prompt change review

A release review checklist for prompt, policy, model, and tool changes before they reach production users.

learnHarden

Red-team scenario library

A scenario catalog for testing prompt injection, unsafe tool use, data leakage, policy bypass, and recovery behavior.

learnValidate

Retrieval citation audit

An audit worksheet for checking cited answers against source text, permissions, freshness, and reviewer corrections.

learnValidate

Retrieval evaluation set

A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.

learnPrepare

Retrieval source owner map

An ownership map for knowledge sources, refresh cadence, permission rules, source quality, and escalation contacts.

learnConnect

Tool integration spec

A technical specification for AI-callable tools covering schema, permissions, idempotency, retries, and audit trails.

learnSecure

Tool permission review

A review worksheet for validating AI-callable tool scopes, sensitive actions, audit trails, and approval thresholds.

learnValidate

Vendor model evaluation scorecard

A scorecard for comparing model and platform vendors across quality, latency, cost, security, support, and lock-in risk.

learnAssess

Workflow automation ROI calculator

A calculator outline for estimating automation value from cycle time, error rate, labor mix, risk reduction, and adoption.

learnAssess

Workflow intake template

A structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.

learnLearn

Resource library

Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.

StudioCompany

About Baciu.com

A services practice for organizations that need AI systems designed, evaluated, shipped, and operated with accountability.

CapabilitiesUse case

Access-management AI solutions

Use-case patterns for access requests, entitlement review, policy checks, approval packets, and identity-workflow support.

CapabilitiesStudio

Agent permission-scoping solutions

Permission models for deciding what agents may read, draft, recommend, approve, execute, and escalate.

CapabilitiesStudio

Agent production-deployment solutions

Release patterns for moving agents from prototype to monitored, supported, measurable production services.

ProofAssess

Agent readiness assessment

A structured assessment for deciding whether a workflow is ready for autonomous or semi-autonomous execution.

Capabilities

Agent studio

A controlled environment for designing, testing, and managing reusable agents before they reach production.

Execution lab

Interactive planner for AI implementation roadmaps.

Tune delivery tempo, autonomy, and risk profile to inspect recommended phases, dependencies, and control gates.

Primary objective

Risk profile

Delivery tempo

Autonomy level: 58%

Recommended phases

W1+2

Data readiness

No retrieval without source discipline

W3+3

AI product design

Trust is a product feature

W6+4

Tool orchestration

Action with accountability

W10+3

AI evaluation lab

Every release earns trust

W13+2

AI governance

Control where the work happens

W15+2

Enablement and handoff

Client teams can operate independently

Capability radar

Interactive map of AI implementation priorities.

Select an operating perspective and horizon to inspect relevant tracks, signals, and linked decision pages.

Reference page

Perspective

Horizon

Priority tracks

Agent cost allocation model

AI spend tied to operating value

Executive AI roadmap

Strategy with an implementation path

Delivery governance

Governance in the delivery loop

Studio delivery model

Delivery designed for durable ownership

AI governance

Control where the work happens

Execution blueprint

How this capability expands into production service.

Each area is delivered through explicit definition, measurable validation, and operating governance that client teams can inherit.

Natural-language agent definition

Define explicit goals, boundaries, and stop conditions before implementation.

Loop and verify execution

Run iterative plan-execute-verify loops before delivering outcomes.

Human-in-the-loop controls

Keep human approval for sensitive or irreversible actions.

Operating checklist

What gets delivered with this work.

Architecture

A clear system map covering models, tools, data, workflows, users, and failure modes.

Evaluations

Task sets, regression checks, and release criteria for measurable AI behavior.

Controls

Human approval, access, logging, data-boundary, and incident-response rules.

Handoff

Documentation and ownership so the client can operate the system after launch.

Operating risks to control

Expanding autonomous authority without calibrated approval policies.
Stale or conflicting sources that silently degrade decision quality.
Insufficient traceability for automated actions and human interventions.
Release processes that skip relevant regression scenarios.

AI governance AI incident response Model risk management AI evaluation lab

Frequent questions

How do we choose where automation starts?

Start with repetitive, reversible workflows where outcomes and failure boundaries can be measured.

How do we prove quality before launch?

Use eval sets, adversarial scenarios, and explicit go/no-go criteria tied to business impact.

How does the team stay in control?

With authority boundaries, confidence thresholds, escalation packets, and complete execution traces.

What happens when model behavior changes?

Treat model and prompt changes as releases: test, review, approve, and roll out with rollback paths.

Coverage map

Companion pages for this delivery area

AI readiness scorecard

A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.

Governance control matrix

A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.

Retrieval evaluation set

A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.

Model operations runbook

A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.

Relevant pages

Representative AI deployments, rewritten as reusable patterns.

Resource library

Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.

AI readiness scorecard

A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.

Governance control matrix

A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.