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AI systems audit packet

AI Systems Audit Packet

The AI Systems Audit is the controlled entry point for companies that want useful AI but need clarity first. Folium inspects processes, tools, data, staff impact, cost, risk, integrations, governance, and first-build candidates before recommending a path.

Audience Executives, IT, operations, compliance-aware teams, and first-build sponsors

Purpose Define what a buyer should expect from a Folium audit and what records it should produce

Updated May 2026

The audit turns AI pressure into a ranked set of safe, useful, reviewable next steps.

The first output is clarity: process map, source map, risk map, tool inventory, and first-build recommendation.

The audit protects the buyer from overbuying tools, exposing data, or launching without owners.

AI systems audit

The audit finds the first safe lane before the buyer overbuilds.

The audit packet maps processes, systems, data, tools, subscriptions, staff impact, risk, runtime fit, and first-build candidates.

Audit path

01Turns the audit into an operating product.

02Shows the buyer what records they receive.

03Connects discovery to a first build instead of a static report.

Navigation map

Choose the review route before reading cover to cover.

This packet is meant to support a real decision meeting. Different reviewers should enter through different routes, then come back together around the same controlled next step.

Decision route Operating route Trust route

Executive route

Decision first

Start with the cover, visual summary, executive read, controls, first ninety days, and handoff. This route helps leaders decide whether the next move is education, audit, first build, pilot, or operations.

Outcome
Risk
Owner
Next gate

Operations route

How the work will run

Read the workflow map, procedures, operating roles, metrics, first sprint, and buyer worksheet. This route shows whether staff can actually use, review, and improve the future process.

Workflow
Staff
Support
Improve

Technical and trust route

Where the boundaries live

Focus on records and work products, controls, risk assumptions, reference work products, source truth, runtime placement, and launch conditions before any private access expands.

Source
Access
Runtime
Rollback

Buyer session route

Turn reading into a working session

Use the discovery questions, role review route, buyer worksheet, and engagement fit ladder to prepare one process, one owner, one source map, and one next decision.

Process
Examples
Questions
Decision

Best use: bring one workflow, the people who own it, the systems it touches, the data classes involved, and the decision this packet should help leadership make.

Folium Systems Navigation map foliumsystems.com

Executive read

AI systems audit packet in plain language.

RecordBoundaryAction

Inventory

Find what already exists

List AI tools, automations, subscriptions, documents, databases, websites, stores, CRMs, and staff workarounds.

Tools
Sources
Owners

Risk

Name what can go wrong

Map data exposure, wrong-answer risk, vendor sprawl, unsupported workflows, compliance concerns, and staff resistance.

Data
Access
Support

Value

Rank the first safe lane

Choose the first workflow by value, feasibility, risk, and reviewability.

Time
Cost
Quality

Plan

Create the next build path

Produce a scoped first-build, governance, launch, and operations recommendation.

Scope
Build
Operate

This packet is public-facing. It is written for serious review without exposing private infrastructure, customer data, credentials, live provider wiring, or internal project labels.

Folium Systems Public-facing PDF foliumsystems.com

Workflow map

The operating path should be visible before anyone trusts the outcome.

Folium uses workflow maps to turn broad AI ambition into inspectable work. Each phase names the procedure, the visible output, and the decision gate that prevents excitement from outrunning control.

Decision gridReview lensNext step

Phase	Procedure	Visible output	Decision gate
Kickoff	Name sponsor, audit goal, business pressure, constraints, and review audience.	Audit charter.	The audit has a business owner.
Tool inventory	List AI subscriptions, automations, agents, APIs, databases, documents, and shadow workflows.	AI estate inventory.	Unknown tools are surfaced.
Workflow scan	Identify repeated tasks, customer moments, staff bottlenecks, support issues, and document-heavy work.	Workflow candidate list.	At least one useful lane is visible.
Data boundary review	Classify sources by public, internal, private, regulated, confidential, and blocked.	Data boundary map.	Sensitive data is not guessed.
Risk and readiness	Score risk, quality, staff adoption, source readiness, integration difficulty, and support burden.	Readiness matrix.	Launch blockers are clear.
First-build selection	Choose a narrow build with visible value and controlled risk.	First-build recommendation.	The buyer knows what to test first.
Launch posture	Define owner, governance, support, rollback, training, and improvement needs.	Launch readiness outline.	Pilot path is credible.
Audit handoff	Package findings, decisions, diagrams, and recommended next step.	Audit packet.	Leadership can decide from records.

Folium Systems Public-facing PDF foliumsystems.com

Records and work products

The work should leave behind material a buyer can inspect.

A serious engagement should produce more than conversation. Folium packages records, diagrams, checklists, routes, system surfaces, launch gates, and handoff material so the buyer can keep control after the first win.

Decision gridReview lensNext step

Work product	What it contains	How the reviewer uses it
AI estate inventory	Tools, accounts, automations, prompts, agents, APIs, data stores, and owners.	Shows sprawl, overlap, cost waste, and hidden dependencies.
Workflow candidate matrix	Potential AI use cases ranked by value, feasibility, risk, and reviewability.	Selects the first safe build.
Data boundary map	Source classes, allowed use, blocked data, retention, custody, and provider exposure.	Protects sensitive information.
Risk heatmap	Wrong-answer risk, privacy risk, operational risk, staff risk, customer risk, vendor risk.	Prioritizes controls.
First-build scope	Process, users, systems, data, acceptance criteria, and excluded actions.	Moves from audit to action.
Launch readiness checklist	Owners, support, rollback, training, monitoring, evaluation, and approvals.	Prevents unsupported pilots.

Folium Systems Public-facing PDF foliumsystems.com

Procedures

The procedure is the product as much as the technology.

The goal is not to make AI look impressive for one meeting. The goal is to make the operating path repeatable, explainable, reviewable, and safe enough to improve.

ChecklistOwner pathRelease signal

Start with one executive sponsor and one operations owner.
Collect existing tool, system, source, and process information before recommending new software.
Name duplicated AI subscriptions and unsupported automations.
Use staff interviews to find hidden workarounds and fear points.
Classify data before discussing model/provider placement.
Separate easy productivity gains from high-risk operational dependency.
Rank workflows by value and readiness, not hype.
Document what should stop, what should continue, and what should be built next.
Produce one first-build recommendation that leadership can understand.
End with a decision meeting, not a vague report.

Folium Systems Public-facing PDF foliumsystems.com

Controls

Governance, quality, and launch gates keep speed honest.

Folium keeps the buyer's next decision tied to observable gates: source truth, authority, access, testing, ownership, support, rollback, and improvement cadence.

Decision gridReview lensNext step

Gate	What must be true	Stop or refine signal
Access gate	The audit only uses approved public/internal materials and agreed interviews.	Private or regulated data is being shared casually.
Inventory gate	AI tools and business systems are sufficiently mapped.	Unknown shadow systems remain central to the process.
Readiness gate	A first workflow has owner, sources, value, and risk controls.	Candidate workflows are not ready.
Scope gate	The first build has acceptance criteria and excluded actions.	The build is too broad or unbounded.
Leadership gate	The audit packet supports stop/refine/build/pilot decision.	Decision makers lack records.

Folium Systems Public-facing PDF foliumsystems.com

Discovery questions

The right questions expose the real project.

These prompts help a buyer and Folium decide whether the next step should be education, audit, first build, security review, pilot, or an operating support path.

ChecklistOwner pathRelease signal

Which AI tools are already being paid for?
Which workflows rely on staff memory or spreadsheet patches?
Where are customers waiting too long?
Which document or knowledge process is repeated every week?
Which current AI output is trusted without enough review?
Which integration would save the most manual handoff?
Which data should never enter a public AI service?
Which process would prove value fastest without production risk?

Folium Systems Public-facing PDF foliumsystems.com

Visual digestion

Diagrams, charts, and overlays make the work easier to review.

Dense AI work should not only be explained in paragraphs. The reviewer should be able to inspect maps, scorecards, matrices, lanes, and before-after views that reveal where the value and risk live.

RecordBoundaryAction

AI estate map

A system map of tools, subscriptions, automations, documents, stores, owners, and gaps.

Tool
Source
Owner
Gap

Workflow candidate matrix

A scoring grid for value, risk, data readiness, staff adoption, and build difficulty.

Value
Risk
Readiness
Effort

Data boundary overlay

A color-coded map for public, internal, private, regulated, confidential, and blocked sources.

Public
Internal
Private
Blocked

First-build funnel

A funnel from many ideas to one process with the strongest safe first outcome.

Ideas
Rank
Scope
Build

Folium Systems Public-facing PDF foliumsystems.com

Operating roles

Every serious AI path needs named owners before it becomes dependency.

The same technology can be safe or unsafe depending on who owns the workflow, data, quality, launch authority, support, and improvement loop. Folium makes those responsibilities explicit so no buyer inherits an orphaned system.

Decision gridReview lensNext step

Role	Owns	Record to inspect
Executive sponsor	Priority, budget, risk tolerance, stop/continue decision, and expansion timing.	Decision note, value hypothesis, and approval boundary.
Business process owner	The day-to-day work, acceptance criteria, staff impact, and operational usefulness.	Workflow map, user feedback, and adoption notes.
Technical owner	Systems, APIs, databases, runtime placement, deployment, monitoring, and fallback.	Architecture map, integration log, and support route.
Knowledge owner	Source truth, document freshness, policies, retrieval scope, and correction workflow.	Source inventory, freshness cadence, and review exceptions.
Security or risk reviewer	Data classes, credentials, access, logs, retention, blocked actions, and incident path.	Boundary map, permission table, and rollback trigger.
Folium delivery lead	Build coordination, review file, known limits, quality checks, and handoff completeness.	Launch room, eval record, and improvement backlog.

Folium Systems Public-facing PDF foliumsystems.com

Quality scorecard

A max-detail packet should tell reviewers how to judge the work.

Folium uses scorecards to make a subjective AI conversation more inspectable. The score is not a substitute for judgment; it helps leadership see whether the next step is education, repair, sandbox, pilot, or operations.

Decision gridReview lensNext step

Score area	Strong signal	Weak signal
Business fit	The workflow is specific, painful, owned, and tied to measurable operational improvement.	The project is framed as adding AI generally.
Source truth	Approved sources are known, fresh, classified, and connected to the answer path.	The system mixes stale, unknown, or unapproved sources.
Behavior quality	Representative tasks pass, wrong-answer behavior is known, and edge cases are recorded.	The review build only shows a polished happy path.
Authority control	AI actions are separated into draft, retrieve, recommend, route, execute, block, and escalate.	The system can act without visible permission.
Staff readiness	Users can explain the tool, correct it, escalate, and understand their role.	Staff feel replaced, confused, or unsupported.
Operations readiness	Support, monitoring, rollback, release rhythm, and source refresh are owned.	No one knows who maintains the system after launch.

Folium Systems Public-facing PDF foliumsystems.com

Thirty / sixty / ninety

The work should have a believable first ninety days.

A controlled first ninety days keeps ambition high without turning uncertainty into production risk. Folium uses the period to move from understanding into a narrow working example, then into reviewable operating rhythm.

Decision gridReview lensNext step

Window	Focus	Expected output
First 30 days	Discovery, source inventory, first-lane selection, staff interviews, data boundary, and build plan.	Process map, owner map, first-build scope, source list, and launch blockers.
Days 31-60	Working surface, RAG or agent behavior, integration stub, evaluation cases, browser checks, and staff review.	Sandbox, evaluation file, screenshots, known limits, and repair list.
Days 61-90	Architecture review, pilot conditions, governance layer, training guide, support path, and improvement cadence.	Launch room, go/no-go record, operations guide, and next-stage recommendation.

Folium Systems Public-facing PDF foliumsystems.com

Risk and assumption register

The hidden assumptions should be visible before they become expensive.

Every AI engagement contains assumptions about data, people, systems, cost, behavior, and authority. Folium treats those assumptions as review material, not background noise.

Decision gridReview lensNext step

Assumption	Why it matters	How Folium reviews it
The source is authoritative	AI can only be as reliable as the sources and business rules it is allowed to use.	Source inventory, owner confirmation, retrieval tests, freshness cadence.
The process is ready	A broken process can become a faster broken process when AI is added too early.	Workflow mapping, bottleneck review, owner interview, first-lane narrowing.
The runtime fits the data	Cloud, private, local, and hybrid routes carry different privacy, cost, latency, and support tradeoffs.	Runtime matrix, data classification, provider review, fallback plan.
Staff will adopt the tool	Adoption fails when users do not understand, trust, correct, or benefit from the system.	Training notes, staff review, feedback loop, manager visibility.
Authority is clear	The system can create harm if it sends, updates, approves, or routes without permission.	Permission table, blocked actions, human review, audit trail.
The system can be supported	A useful first build becomes fragile if nobody owns incidents, source updates, or cost review.	Support guide, owner map, release rhythm, rollback trigger.

Folium Systems Public-facing PDF foliumsystems.com

First sprint procedure

The first sprint should produce something real and reviewable.

Folium prefers a narrow first sprint that creates a working surface or review file the buyer can challenge. The first sprint is not the final system; it is the safest way to make the future visible.

ChecklistOwner pathRelease signal

Confirm the single process and the decision the sprint must support.
Collect approved example material, redacted review records, public references, screenshots, workflow notes, and source rules.
Define what will be built: portal, dashboard, RAG assistant, agent route, integration adapter, audit file, or launch room.
Create the visual workflow: intake, source, model or agent route, human review, output, record, and next gate.
Run representative tasks, edge cases, bad input, missing data, and blocked-action tests.
Prepare browser screenshots, known limits, support questions, and next-stage blockers.
Review with staff and leadership before expanding data, access, authority, or dependency.
End with a decision: stop, refine, rebuild, pilot, or prepare an operating plan.

Folium Systems Public-facing PDF foliumsystems.com

Reference work products

The packet should make the invisible work tangible.

AI work often fails because the important pieces are invisible until something breaks. Folium turns those pieces into work products the buyer can open, print, challenge, and improve.

RecordBoundaryAction

Process map

A before-and-after workflow showing people, systems, data, decision points, blockers, and expected output.

Before
After
Owner
Gate

Data boundary map

A map of source classes, approved use, blocked use, retention, provider exposure, and custody.

Public
Internal
Private
Blocked

Model and agent route

A path showing which model, tool, retrieval source, or agent lane is used and where humans approve.

Route
Tool
Review
Escalate

Evaluation file

A record of tasks, expected outcomes, failures, repairs, known limits, and acceptance criteria.

Cases
Failures
Repairs
Limits

Launch room

A board for owners, support, training, rollback, incidents, go/no-go, and improvement backlog.

Owner
Support
Rollback
Backlog

Handoff guide

A plain-language guide staff can use to understand what the system does, cannot do, and how to report problems.

Use
Limit
Correct
Report

Folium Systems Public-facing PDF foliumsystems.com

Metrics and review rhythm

The business should know how improvement will be measured.

Folium keeps measurement practical. The first goal is not a perfect dashboard; it is a clear set of signals that shows whether the process is saving time, reducing risk, strengthening staff, or improving customer outcomes.

Decision gridReview lensNext step

Signal	What to watch	Decision it supports
Time recovered	Manual steps removed, average handling time, repeated work reduced, faster routing.	Should this workflow expand to more users or adjacent processes?
Quality improved	Wrong answers, missing sources, correction rate, review exceptions, customer rework.	Is behavior strong enough for pilot or does it need repair?
Risk reduced	Blocked unsafe actions, escalations, data-boundary violations avoided, rollback readiness.	Can authority expand or should controls remain tight?
Staff confidence	Training completion, feedback volume, adoption friction, override rate, manager notes.	Does the workforce need more support before launch?
Cost and runtime	Provider cost, local infrastructure cost, latency, uptime, fallback use, subscription sprawl.	Should runtime placement change?
Customer impact	Response speed, consistency, issue resolution, conversion support, satisfaction signals.	Is the capability improving the business outcome?

Folium Systems Public-facing PDF foliumsystems.com

Role review route

Each reviewer should know what to inspect first.

A max-detail packet is only useful when different reviewers can find their lane quickly. Folium separates executive, operations, technical, security, finance, and staff questions so the buyer can bring the right people into the right part of the review.

Decision gridReview lensNext step

Reviewer	Start with	Decision they support
Executive sponsor	Value hypothesis, launch gate, first ninety days, and stop/refine/continue choices.	Whether the process deserves a controlled engagement.
Operations lead	Workflow map, operating roles, support rhythm, and staff feedback loop.	Whether the future process can be run by the team.
Technical lead	Runtime placement, data path, integration surface, monitoring, and fallback.	Whether the architecture can be supported safely.
Security or risk reviewer	Data classes, permissions, blocked actions, logs, retention, and rollback.	Whether access can expand beyond public review.
Finance or owner	Cost signals, subscription overlap, runtime tradeoffs, labor impact, and support burden.	Whether the first build has a practical business case.
Staff user	Plain-language use, limits, escalation, correction path, and training expectations.	Whether the tool strengthens the job instead of confusing it.

Folium Systems Public-facing PDF foliumsystems.com

Buyer worksheet

The packet should turn into a working session, not only reading material.

Before a call, Folium wants the buyer to gather the real operating pieces that make the review useful. The worksheet keeps the conversation grounded in one process, one owner, one source map, and one next decision.

ChecklistOwner pathRelease signal

Bring one workflow that is slow, risky, expensive, repetitive, customer-visible, or staff-heavy.
Name the systems touched by the workflow: store, CRM, ERP, inbox, spreadsheet, database, portal, document folder, or legacy application.
Separate approved public material from internal, customer, regulated, confidential, credential, and blocked material.
Write down who owns the work today, who reviews exceptions, and who will own the AI-assisted version.
List the decisions AI may draft, retrieve, recommend, route, block, or escalate, and the decisions that stay human-owned.
Bring examples of good output, bad output, common exceptions, missing data, and customer-facing risk.
Name the first useful working surface: dashboard, portal, assistant, queue, control room, commerce lane, integration, or review file.
Decide what record would make leadership comfortable with the next stage.

Folium Systems Public-facing PDF foliumsystems.com

Engagement fit ladder

The next step should match the maturity of the record.

Folium does not need every buyer to start at the same altitude. The right offer depends on how much process clarity, source truth, owner alignment, and launch readiness already exists.

Decision gridReview lensNext step

If the buyer has	Best next Folium move	Output to expect
AI interest but no clear process	AI systems audit or first workflow finder.	Pressure map, source inventory, first-lane recommendation, and risk view.
A clear process but no working surface	Forward engineering first sprint.	Clickable surface, route map, known limits, and next-stage blockers.
A tool that works in parts but not in operations	Architecture and launch readiness review.	Permission map, runtime decision, support model, and go/no-go record.
A failed or frightening rollout	AI recovery and staff enablement path.	Issue register, staff training plan, repair roadmap, and confidence loop.
Sensitive data or cost pressure	Local, private, or hybrid AI placement review.	Runtime matrix, data custody plan, fallback route, and vendor-exit view.
A useful pilot that needs care	AI operations support.	Monitoring rhythm, source refresh, release notes, incident path, and improvement backlog.

Folium Systems Public-facing PDF foliumsystems.com

Handoff

The last page of a packet should create the next controlled move.

Folium's handoff view separates what can be done now, what needs customer records, what needs approval, and what should wait until the review file is stronger.

Decision gridReview lensNext step

Handoff lane	Owner	Next record
Audit sponsor	Executive owner	Audit charter and final decision.
Process owner	Operations lead	Workflow map and first-build scope.
Technical reviewer	IT or systems owner	System/source boundary and integration notes.
Folium delivery	Forward engineering lead	Recommendation packet and next-stage plan.

The strongest next step is narrow: one process, one owner, one source map, one working surface, one review file, and one decision gate.

Folium Systems Public-facing PDF foliumsystems.com

Next step

A good audit makes the first build obvious and the bad ideas visible.

Use this packet to prepare for a Folium Systems AI audit and decide what records your team should gather first.

Bring the process

Name the business process, the systems involved, the people affected, and the decision this PDF should support.

Separate review from production

Keep public examples, sandbox review, pilot access, and production dependency in separate stages with clear owners.

Ask for the record

Request screenshots, browser checks, known limits, launch blockers, support plans, and the next approval path.

Folium Systems Public-facing PDF foliumsystems.com