Managed AI Services for Manufacturers

What Managed AI is

Ongoing leadership for how your organization chooses, uses, and improves AI.

Managed AI is an ongoing management function for AI—not a software product and not a replacement for the people who already own your business, systems, and decisions. It gives leaders and employees a consistent place to bring AI questions, evaluate tools and workflows, review how approved uses are performing, and decide what should change or stop.

It is similar to managed IT because it provides recurring expertise, support, records, and operating discipline. The focus is different: managed IT keeps infrastructure, identities, devices, networks, security controls, backups, and general support operating; Managed AI helps decide where AI belongs, how people use it, how outputs are evaluated, and how AI-specific risks, costs, vendors, and changes are managed.

Responsibility charter for Managed AI, managed IT, and your organization
Area	Magnetta's Managed AI	Managed IT or MSP	Your organization
Direction and priorities	Facilitates priorities, recommendations, roadmap updates, and AI-specific decisions.	Advises on technical fit, supportability, and the existing environment.	Approves objectives, funding, vendors, policies, and risk decisions.
Tools and access	Evaluates AI use, workflow fit, output behavior, and operating requirements.	Owns assigned identity, access, tenant configuration, devices, networks, and security controls.	Approves tools, information use, and business ownership.
Information and systems of record	Reviews only agreed evidence and samples, records unresolved source issues, and recommends AI-specific corrections or limits.	Owns assigned permissions, retention, connections, availability, backup, and technical administration for the underlying systems.	Data, process, and specialist owners identify the governing source, approve information use, and authorize corrections to systems of record.
Employee support	Helps people use approved AI, verify outputs, raise questions, and follow escalation rules.	Handles assigned account, device, connectivity, platform, and general help-desk issues.	Managers set expectations and retain responsibility for employee conduct and decisions.
Workflow performance	Reviews agreed samples, evaluations, issues, costs, changes, and improvement opportunities.	Maintains assigned infrastructure, integrations, reliability, backup, and technical support.	Process and specialist owners decide whether work is acceptable and may continue.
Issues and change	Coordinates AI-specific issue review, vendor changes, workflow corrections, and roadmap decisions.	Leads assigned cybersecurity, availability, infrastructure, and technical incident response.	Leadership and authorized specialists retain policy, quality, legal, HR, security, and production authority.

Magnetta's Managed AI

A defined recurring service for small and midsize manufacturers.

Magnetta's Managed AI is designed for a manufacturer that needs recurring AI leadership but does not need to build an internal AI department. It works alongside management, employees, process owners, quality, and the existing IT team or MSP.

The six-month initial term creates enough time to establish the register and cadence, observe operating questions and agreed workflow samples, and make evidence-based continue, change, or stop decisions.

This is fractional AI leadership within the contracted users, tools, workflows, records, cadence, and response targets. It is not an interim executive role, a broad CIO or CTO mandate, unlimited advisory access, or authority to approve company decisions.

Magnetta’s Managed AI at a glance

For: Manufacturers that need recurring AI leadership without an internal AI function
Duration: Six-month initial term
Scope: Up to 25 active AI users, three reviewed AI tools, and two actively managed workflows
Pricing: Monthly managed engagement; scoped proposal after baseline confirmation

What's included

Know the records, reviews, support rhythm, and response target.

Included in Magnetta's Managed AI

Initial AI tool and workflow register
Monthly leadership operating review and monthly management summary
Two one-hour group office-hours sessions per month
Asynchronous questions with a two-business-day initial-response target
Review of one proposed AI vendor or tool per month
Monthly review of agreed samples from managed workflows
AI issue, risk, change, and decision log
Employee onboarding and reinforcement guidance
IT/MSP coordination and a quarterly AI roadmap update

Operating cadence

Use recurring reviews without implying 24/7 coverage.

Magnetta's Managed AI cadence and service boundaries
Cadence	Included work	Boundary
Asynchronous	Questions about the agreed AI scope, with a two-business-day initial-response target.	An initial response is not a resolution promise, emergency channel, or 24/7 coverage.
Twice monthly	Two one-hour group office-hours sessions.	AI-specific guidance for the agreed users and scope—not a general IT help desk.
Monthly	Leadership operating review, management summary, agreed workflow sample review, and one proposed vendor or tool review.	Sampling and access are agreed; Magnetta does not observe every employee action.
Quarterly	Roadmap update across current evidence, operating changes, and next priorities.	New implementation remains separately scoped.

Workflow health and success measures

Measure whether the workflow remains useful—not whether the model looks impressive.

Each managed workflow needs an agreed outcome, baseline or baseline plan, evidence source, review method, owner, target or acceptable range, and threshold for escalation, pause, change, or retirement. Measures are selected with the manufacturer for the actual workflow; generic model scores or a promised ROI do not substitute for operating evidence.

A monthly sample can reveal direction, exceptions, and questions, but it is not proof about every transaction. The process owner and authorized specialists decide whether the evidence is sufficient and whether the workflow may continue.

Illustrative manufacturing AI workflow-health measures
Measure family	Evidence reviewed	Decision it supports
Business flow	Agreed baseline and current cycle time, backlog, handoffs, rework, missing inputs, or another workflow-specific measure.	Continue, investigate a change, repair the process, or retire the workflow.
Evidence and output quality	Agreed samples for correctness, completeness, source support, unknown preservation, reviewer corrections, and consequential failure modes.	Keep the boundary, narrow it, change the evaluation, pause, or stop.
Adoption and operability	Approved aggregate usage, completed assisted work, recurring questions, fallback use, and support demand within the contracted scope.	Reinforce the method, change the workflow, adjust licenses, or determine that the use is not sustainable.
Risk and control	Reported exceptions, escalations, out-of-scope requests, permission issues, vendor changes, and unresolved specialist decisions.	Correct, restrict access, escalate, pause, roll back, or retire.
Cost and operating burden	Agreed software or usage costs, license utilization, review effort, support effort, and maintenance or vendor dependencies.	Continue, resize, replace, redesign, or stop without claiming guaranteed savings or ROI.

What monitoring means

Monitor the agreed AI operating system—not employees by default.

Monitoring is limited to the registered tools, approved workflows, evidence, questions, costs, and changes named in the engagement. Output sampling and access are agreed in advance and must follow the manufacturer’s privacy, HR, quality, security, and information-handling requirements.

Managed AI does not conduct undisclosed employee surveillance. Aggregate usage may help identify adoption or license questions, but it is not a hidden employee-performance system.

Registered tools and approved workflows
Customer- or platform-supplied aggregate usage
Agreed samples of AI-assisted outputs and evaluation results
Issues, escalations, recurring employee questions, costs, credits, and license utilization
Material product or policy changes

Manufacturing AI change management

Pause, review, and route every material change.

Magnetta coordinates AI-specific change records, evidence review, user reinforcement, and recommendations within the contracted scope. It does not become the emergency-response owner, investigate outside its access and expertise, or make the customer's security, employment, quality, legal, engineering, release, or risk-acceptance decision.

Managed AI change and escalation path
Trigger	Immediate handling	Authorized decision
Material output failure or missing evidence	Pause the affected use when the operating rule requires it, preserve the example and governing source, and record the issue without silently correcting the record.	The process owner and qualified specialist decide correction, retest, rollback, restricted use, or retirement.
Suspected security, privacy, access, or information-handling issue	Stop the affected exposure or access when authorized, preserve facts, and route the issue through the customer's established incident and escalation process.	IT, security, privacy, legal, data, or another authorized owner directs response and restoration.
Vendor, model, feature, policy, source, or integration change	Record the change, affected users and workflows, permission impact, evaluation need, fallback, and unresolved questions before wider use.	The assigned business, IT/MSP, data, security, quality, legal, or vendor owner approves, pilots, restricts, rolls back, or rejects the change.
Workflow-health measure crosses an agreed threshold	Review the baseline, sample, exceptions, user feedback, cost, and known environmental changes; do not treat one metric as the whole decision.	The process owner decides continue, reinforce, modify, pause, resize, or retire with required specialist input.
Employee question, misuse, or conduct concern	Provide agreed AI-use guidance, preserve privacy, and route conduct or employment matters to the customer's management or HR process.	Managers and HR retain employee, performance, discipline, training, and policy authority.

Use the manufacturing AI acceptable-use guide Review the human-authority model

Prerequisite and onboarding

Start from a current operating baseline.

A recent AI Direction Sprint or equivalent current operating baseline satisfies the prerequisite.

Without that baseline, a separately scoped onboarding assessment covers tools, workflows and owners, information and permission boundaries, policies, risks, unresolved decisions, and first operating priorities.

The onboarding assessment is scoped and priced separately so the work reflects the tools, workflows, users, information boundaries, and controls already in place.

A bounded implementation can transition into Managed AI after stabilization only when the customer accepts the workflow, named owners, operating rules, evaluation evidence, unresolved risks, fallback, access, support responsibilities, and first review measures. The transition is a separate commercial decision—not an automatic extension of implementation.

Customer contribution

What your company contributes

Recurring management works only when the internal owners participate and supply agreed access and decisions.

Executive owner: attend the monthly operating review and quarterly roadmap review; make funding, priority, vendor, policy, and risk decisions
Process owners and qualified reviewers: supply agreed samples, baseline context, factual corrections, dispositions, and timely workflow decisions
IT/MSP and data or system owners: participate in onboarding and material access, vendor, source, integration, security, and incident changes
Quality, security, HR, legal, engineering, customer, or regulatory owners: review matters within their actual authority when required
Managers and approved users: follow operating rules, raise issues, use the defined fallback, and participate in agreed reinforcement

Handoff gate from bounded implementation to Managed AI
Handoff item	Required operating baseline
Workflow and authority	Named business owner, users, qualified reviewers, prohibited decisions, escalation path, and accepted workflow boundary.
Evaluation and acceptance	Representative normal, difficult, incomplete, conflicting, and misuse cases; known failures and unresolved risks; customer acceptance or a documented limitation.
Information and technical ownership	Approved sources and information classes, systems of record, access, integration, fallback, IT/MSP owner, and specialist dependencies.
Operating measures and records	Baseline or baseline plan, review sample and cadence, target or acceptable range, issue/change record, and threshold for pause, rollback, or retirement.

Larger teams and complex environments

Larger or more complex needs receive a custom scope.

Teams larger than the standard scope shown here, or with unusually regulated, safety-relevant, or complex requirements, receive a custom scope based on the users, tools, workflows, controls, specialists, and support involved.

The proposal defines the meeting cadence, response targets, evaluation approach, access, specialist dependencies, and support responsibilities before work begins.

Managed AI and managed IT

Managed AI does not replace managed IT or decision owners.

Who owns what

Know who is responsible for each decision.

Monitoring covers only the agreed AI operating system and never transfers customer, IT/MSP, or specialist authority by implication.

Magnetta

Operate the contracted AI management cadence and maintain agreed AI-specific records.

Manufacturer

Own objectives, policy, employee conduct, vendor approval, risk acceptance, and business decisions.

IT or MSP

Own assigned identity, device, network, backup, tenant, and general support responsibilities.

Specialist authorities

Retain delegated quality, legal, HR, security, engineering, and regulatory authority.

Included

Magnetta manages the contracted AI scope

The agreed AI operating cadence, AI-specific records, evaluations, tool reviews, employee reinforcement, and IT/MSP coordination
Only the named user, tool, workflow, access, and support bands

Not included

Managed AI does not include

24/7 monitoring or emergency response
General IT help desk or device, network, identity, backup, endpoint, or tenant administration
Undisclosed employee surveillance
Cybersecurity certification or legal, regulatory, export-control, or compliance determinations
Guaranteed AI accuracy or fitness
Unlimited implementation, integration, or software development
Third-party software, model, API, cloud, or usage charges
Production infrastructure or MLOps unless separately contracted
Authority to approve a tool, policy, disposition, release, commitment, or business decision
Standalone workforce training, employee certification or proficiency determination, or employee-performance assessment

Discuss Managed AI Compare Magnetta services Review bounded implementation Review the Technology Stack and permission model Review AI Direction

Operate approved AI responsibly.

Ongoing leadership for how your organization chooses, uses, and improves AI.

A defined recurring service for small and midsize manufacturers.

Magnetta’s Managed AI at a glance

Know the records, reviews, support rhythm, and response target.

Included in Magnetta's Managed AI

Use recurring reviews without implying 24/7 coverage.

Measure whether the workflow remains useful—not whether the model looks impressive.

Monitor the agreed AI operating system—not employees by default.

Pause, review, and route every material change.

Start from a current operating baseline.

Larger or more complex needs receive a custom scope.

Managed AI does not replace managed IT or decision owners.

Know who is responsible for each decision.

Magnetta

Manufacturer

IT or MSP

Specialist authorities

Magnetta manages the contracted AI scope

Managed AI does not include

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