WorksheetAssess
AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Baciu.com service area
Evaluation release gate
A release-gate template that connects evaluation results, known regressions, approval decisions, rollback, and launch notes.
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.
Explore pageWhat 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.
Explore pageReadiness 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.
Explore pageGovernance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Explore pageRetrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Explore pageModel operations runbook
A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Explore pageExecutive AI roadmap brief
A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
Explore pageAI incident tabletop
A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
Explore pageAgent operating model
A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
Explore pageWorkflow intake template
A structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.
Explore pageResource 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.
18artifacts
9phases
17formats
MatrixGovern
Governance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Eval setValidate
Retrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Delivery atlas
Advanced navigator for capabilities, programs, and systems.
Filter, compare, and jump into detailed pages for AI architecture, execution, and governance.
Implementation library
Agent operating model
A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
AI incident tabletop
A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
AI service SLO template
A service-level objective template for AI latency, quality, cost, availability, escalation, and degraded-mode behavior.
Autonomy risk register
A risk register for tracking AI authority, reversibility, sensitive data exposure, failure modes, mitigations, and owners.
Cost and latency dashboard
A dashboard outline for monitoring provider mix, cost drift, latency budgets, fallback rates, and quality regressions.
Data source inventory
A source inventory for mapping owners, freshness, permissions, quality issues, retention rules, and ingestion priority.
Executive AI roadmap brief
A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
Governance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Model operations runbook
A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Permission model workbook
A workbook for translating organizational roles into retrieval, tool-use, approval, logging, and audit permissions.
Production handoff checklist
A handoff checklist for moving AI systems from delivery into operated services with owners, runbooks, controls, and evidence.
Prompt change review
A release review checklist for prompt, policy, model, and tool changes before they reach production users.
Retrieval citation audit
An audit worksheet for checking cited answers against source text, permissions, freshness, and reviewer corrections.
Retrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Tool integration spec
A technical specification for AI-callable tools covering schema, permissions, idempotency, retries, and audit trails.
Workflow intake template
A structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.
Resource library
Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.
About Baciu.com
A services practice for organizations that need AI systems designed, evaluated, shipped, and operated with accountability.
Access-management AI solutions
Use-case patterns for access requests, entitlement review, policy checks, approval packets, and identity-workflow support.
Agent permission-scoping solutions
Permission models for deciding what agents may read, draft, recommend, approve, execute, and escalate.
Agent production-deployment solutions
Release patterns for moving agents from prototype to monitored, supported, measurable production services.
Agent readiness assessment
A structured assessment for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Agent studio
A controlled environment for designing, testing, and managing reusable agents before they reach production.
Agent studio solutions
Design and enablement solutions for defining agent behavior, permissions, tests, release controls, and handoff workflows.
Agent test-sandbox solutions
Sandbox environments for validating agent behavior against realistic data, tools, edge cases, and failure modes.
Agent-to-agent orchestration solutions
Interoperability patterns for coordinating specialized agents that need to share context, delegate tasks, and report status.
Agentic RAG pipeline solutions
Reasoning pipelines that retrieve, inspect, compare, cite, and act on enterprise knowledge with structured validation.
Agentic RAG pipelines
Retrieval-augmented reasoning pipelines that combine source grounding with multi-step decision logic.
Agentic systems
Digital workers that plan, call tools, check their own output, and hand off cleanly when confidence drops.
AI architecture solutions
Architecture solutions for central orchestration, memory, security, operating protocols, data sovereignty, and compliance-ready deployment.
AI capability map
A practical overview of the systems we design, build, evaluate, and operate for organizations adopting AI.
AI evaluation lab
Model and workflow evaluation for teams that need measurable quality before they expose AI to customers or staff.
AI for finance operations
AI-assisted reconciliation, vendor workflows, management reporting, and forecast support.
AI for financial services
Agentic and retrieval systems for regulated teams that need auditability, evidence, and careful approval boundaries.
AI for healthcare operations
Administrative AI systems for care operations where privacy, escalation, and human judgment are non-negotiable.
Execution lab
Interactive planner for AI implementation roadmaps.
Tune delivery tempo, autonomy, and risk profile to inspect recommended phases, dependencies, and control gates.
Risk profile
Delivery tempo
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.
Priority tracks
Agent operating model
Ownership before autonomy
Open pageExecutive AI roadmap
Strategy with an implementation path
Open pageDelivery governance
Governance in the delivery loop
Open pageStudio delivery model
Delivery designed for durable ownership
Open pageAI governance
Control where the work happens
Open pageExecution 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.
Operating checklist
What gets delivered with this work.
01
Architecture
A clear system map covering models, tools, data, workflows, users, and failure modes.
Explore page02
Evaluations
Task sets, regression checks, and release criteria for measurable AI behavior.
Explore page03
Controls
Human approval, access, logging, data-boundary, and incident-response rules.
Explore page04
Handoff
Documentation and ownership so the client can operate the system after launch.
Explore pageOperating 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.
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.
Explore pageGovernance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Explore pageRetrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Explore pageModel operations runbook
A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Explore pageRelevant pages
Representative AI deployments, rewritten as reusable patterns.
Resource library
Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.
Explore pageAI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Explore pageGovernance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Explore page