A draft labelled final
The classification was wrong and a workflow started.
BoldBellowsSharePoint AI document processing with a named approver
SharePoint AI document processing that classifies files, extracts metadata and flags compliance issues as proposals, while a person approves any change to the library
SharePoint AI document processing lets a model read the documents that qualify and propose what should happen, without ever editing the library itself. A SharePoint webhook says only that a list changed, a file can be protected or unreadable, and the words inside a document may include instructions aimed at the model. BoldBellows saves the item ID, the eTag and the version of the change, separates a new version from a new document, then passes the model only the text and fields you approve as quoted data, validates its structured answer and records a proposal with its evidence for a person to accept, edit or refuse.
View Pricing
From $1,395, billed once.
- Process SharePoint documents with AI under control
- Each proposal carries evidence and confidence
- Nothing is filed or shared without approval
The guarantees behind the SharePoint AI route
- Rules firstonly documents that meet your rule reach the model
- Text is dataa document can never give the model orders
- Evidence keptinputs, confidence and the policy version are saved with each decision
- People filenothing changes in the library without the approval you choose
- Launch reviewThe first weeks are watched against the checkpoint log
- No meter running$1,395 covers design, build, tests and handover; nothing accrues afterwards
01the ungoverned-model problem
A model with write access to your library will sooner or later file the wrong thing in the wrong place
Give a model the keys to a document library and it will label a draft contract as final, copy an employee record into a shared folder, or follow a sentence inside a PDF that was only meant to be read. A forty-page report is summarised without the clause that matters. A file is saved twice in a minute and the model processes both versions. Later, nobody can say which document it read, which prompt it ran or why it was confident.
A record in a shared folder
The model moved it where everyone could read it.
An instruction obeyed
A sentence inside a file steered the model.
The same library, with a model that advises and a person who files
Before: the route guesses
- Events are copied across unjudged
- A model can label, move or share on its own
- Nobody can say what it read or why it chose for SharePoint AI Document Processing
After: the route proves each result
- Create, update or skip is decided by a decision key made of the item's unique ID, its version, the model-run ID and the policy version
- The model only proposes, and a person approves with SharePoint AI Document Processing
- Every proposal keeps its inputs, evidence and policy version with SharePoint AI Document Processing
02how it works
How a SharePoint document becomes an evidence-backed proposal a person can approve
The path is short: admit, match, write, record.
- Confirm the trigger. The route confirms that the SharePoint event is authentic and that the library event is one you asked it to act on.
- Read, qualify, minimise. Changes since the stored token are read, each new version is tested against your rule and its content type, and only approved text and fields are prepared as quoted data.
- Propose, approve, record. The structured answer is validated, held with its evidence, confidence and policy version, and a label, a move or a share follows only the approval you require.
What SharePoint and the model each do, and what we add
- Two kinds of trigger. SharePoint has its own webhooks for lists and libraries and Microsoft Graph has change notifications for the same lists and drive items, so the build picks the one that suits the library and renews it before it lapses.
- Documents can carry instructions. A file is written by someone outside your control, so the route hands its text to the model as quoted data under fixed instructions and checks the answer against a schema, which is the defence when a document tries to steer the model.
- Proof of delivery. Each successful write stores the AI workflow identifier beside a decision key made of the item's unique ID, its version, the model-run ID and the policy version, which later checks rely on.
03What the package includes
The parts of a governed SharePoint AI route, and what each does
Pick the depth you need.
EntryEngineAudit Desk
Rule-based admitter Entry
Matches the incoming event to the admission rule and logs the match for later audit.
Stable identity ledger Entry
Maintains a searchable ledger of SharePoint proposals, with the evidence behind each one beside it.
Value normaliser Entry
Standardises formats, dates and casing from SharePoint so the AI workflow receives clean values.
Document eligibility gate Engine
Tests each file against your rule, its content type and its sensitivity before anything reaches a model.
Document-and-run matcher Engine
Compares the event with what a decision key made of the item's unique ID, its version, the model-run ID and the policy version points to and picks the matching action.
Policy and approval matrix Engine
Decides, by content type and confidence, whether a proposal is shown, auto-applied to metadata or sent to a reviewer.
Decision register Audit Desk
Produces a dated list of differences so they can be cleared in order, for this SharePoint AI Document Processing service.
Prompt and policy drift monitor Audit Desk
Flags a changed prompt, model version or policy before the processing quietly changes.
Incident trail Audit Desk
Keeps the sequence of events around any problem so the cause can be found fast.
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04Who it's for
Helping healthcare administrators filing referrals and consents classify, extract and route documents without letting a model change a library on its own
SharePoint holds the documents.
Records manager
"Classify without losing control."
The model suggests the content type and retention label, and a person approves what is applied.
Compliance officer
"Show me what the model read."
Only the approved text and fields reach the model, and every request is recorded.
Legal operations lead
"Flag the risky clause."
Compliance flags come with the passage they rest on, not just a score.
Security lead
"Stop a file steering the model."
Document text is wrapped as data inside fixed instructions, and a reply off the schema is discarded.
Consultancy partner
"Each client site has rules."
Policies and approvers are set site by site, so nothing crosses clients, in the SharePoint AI Document Processing service.
Information officer
"Permissions must not change by accident."
Sharing and permission changes are always held for a named approver.
05Compare
SharePoint to the AI workflow: the quick way, the usual way and an evidence-gated document route
Each can ask a model.
| How a run starts | An AI summary add-on | A generic AI zap for SharePoint | Our evidence-gated document route |
|---|---|---|---|
| What starts the work | A manual check | Each raw notification | YesA library event that passes eligibility |
| How identity is decided | Name typed, hope it matches | Name match, first result wins | YesA decision key: item, version, model run and policy |
| What reaches the AI workflow | Key fields, sometimes | Loosely formatted text | YesA validated proposal with its evidence, confidence and approval state |
| After an uncertain result | A weekly tidy-up | Stops and loses context | YesReconciles first, writes only the difference |
Yesterday's change, today's record
A SharePoint event older than the state in the AI workflow is logged and closed, so delivery timing never decides which version wins.
A document is saved again while the model is still reading it
The proposal is tied to the version it read, so the new version is queued as its own run and the earlier answer is never applied to it. The proposal is located through a decision key made of the item's unique ID, its version, the model-run ID and the policy version, compared with the intended values and classified.
Decide a decision key made of the item's unique ID, its version, the model-run ID and the policy version early: it is how the route recognises its own work.
PricingProposals, approvals and policies move the estimate for SharePoint AI Document Processing
Price your SharePoint AI route, a decision at a time
Packages open at $1,395.
One setup fee · Range shown first · PDF handover included
View Pricing
Pricing
Build your SharePoint AI Document Processing price
Pick a package, answer three short questions about how SharePoint data should reach AI Document Processing, and your price and turnaround move as you choose.
06The process
Six steps to document AI that stays under control
The plan has six steps and a fixed shape, so timelines stay honest.
Choose the decisions
We agree which documents the model may see, what it may propose, such as a content type, metadata or a flag, and who approves each kind.
Approve access
SharePoint permissions are set to the minimum, the model service is confirmed and the approval chain is written down.
Agree fields, policy and approvers
The text and fields the model sees, the policy for each proposal type and the approver for each are written down and signed off.
Replay the troublemakers
Known problem cases are replayed through a test the AI workflow until each one ends safely, for this SharePoint AI Document Processing service.
Launch with notes
The last step is release: a defined start, a review window and a PDF you can keep.
Confirm it holds
A short review confirms that counts, matches and exceptions behave as they did in testing.
07Turnaround
How long the AI Document Processing packages take
Your delivery range starts on the day SharePoint and the model are both connected.
Entry
6 to 10 business days
Engine
10 to 16 business days
Audit Desk
16 to 24 business days
08Before we start
What we ask of you
Authorisation to reach the SharePoint objects in scope
Consent from a SharePoint admin for the sites in scope, plus the model service you have approved
A named SharePoint contact who can approve access requests
The fields from SharePoint that the AI workflow must receive
Details of any other tools that already write to the AI workflow
Permission to document the route in your handover pack
09Security and ownership
Approved data only, through supported doors only
What the model may see from SharePoint is agreed in writing, and what it may propose is agreed with the same care.
Leaves both tools alone
The build uses supported access on each side and does not alter how SharePoint or the AI workflow behave for anyone else on your team.
Scoped, revocable access
Permissions are written down, minimal and reversible.
Scoped to the route
For SharePoint AI Document Processing, the proposal receives the agreed fields for this route alone, which keeps reports and permissions in the AI workflow simple.
Checked before it is repeated
Each retry is preceded by a read of the AI workflow through a decision key made of the item's unique ID, its version, the model-run ID and the policy version, which keeps a timeout from becoming a duplicate.
Minimal logging
Evidence of a run is kept as references, not as copies of data.
Full handover
The PDF names each rule, credential and owner so your admins are never guessing.
10In their words
What BoldBellows clients say
Verified reviews from operations and finance teams who trust BoldBellows to keep their data moving correctly.
AI Document & Contract Automation
Onboarding was slow because we wrote every contract by hand. BoldBellows automated the lot: contracts, welcome emails and client setup.
What took 48 hours now takes under 10 minutes, and clients regularly tell us how professional it feels.
AI Workflow Automation for Agencies
Running a digital agency with many clients was overwhelming. BoldBellows built one automation dashboard that tracks tasks, sends updates and creates client reports automatically.
Clients love the transparency and we love the time we get back. Productivity is up, and project delays have dropped to almost zero.
AI CRM Automation
Our CRM was barely used because updating it by hand was tedious. BoldBellows automated data entry, tagging, segmentation and follow-ups.
Now the CRM is always up to date and our campaigns are far more accurate. It improved our whole sales pipeline.
AI Voice Assistant
BoldBellows built a custom AI voice assistant for our customer hotline. It answers questions, books appointments and handles simple requests.
Customers love how fast it is, and our call-centre workload dropped dramatically. One of the smartest upgrades we’ve made.
AI Automation Partner
BoldBellows is hands-down the best AI automation partner we’ve worked with. Their systems are fast, reliable and built around how our business actually works.
Every automation they’ve delivered, from customer service to content, runs flawlessly. We’ve saved time, cut costs and grown faster than we expected.
AI Chatbot & Customer Support
BoldBellows built an AI support chatbot for our online boutique, and it has changed how we run the business. We used to have two full-time staff answering the same questions all day. Now the AI handles order tracking, product recommendations and even refund requests on its own.
What surprised me most is how natural it sounds. Customers compliment the ‘agent’ without realizing it’s AI. Our support workload dropped by 75% and customer satisfaction went up dramatically.
AI Content & Social Media Automation
Our marketing agency couldn’t keep up with content. BoldBellows set up an AI content engine that writes blog posts and captions and even designs our social media creatives.
It spots trends and suggests topics for us, so we stay ahead of competitors. We now produce three times the content with the same team, and engagement has soared. They didn’t just automate our workflow, they lifted our whole brand.
AI Lead Qualification & Sales Automation
Our sales team wasted hours chasing cold leads. BoldBellows built an AI lead-scoring system that reads behavior, email engagement and buying signals.
It filters out weak leads and sends personalized follow-ups automatically, so our team only talks to people who are ready to buy. Conversions rose 40% in the first month. It paid for itself straight away.
AI Video & Voice Automation
We publish product videos every week, and BoldBellows introduced us to AI video automation. The system writes the script, voices it and produces the finished video in minutes.
The quality is remarkable: professional voiceovers, clean visuals and smooth editing. Production time went from three days to under 30 minutes, and we scaled our video marketing without adding cost.
AI Email & Smart Inbox Management
Our inbox used to be chaos. BoldBellows built an AI email system that sorts messages, drafts replies and flags anything urgent.
It learns how we write and gets better every week. We reply faster and no longer miss important messages. It feels like having a personal assistant working around the clock.
AI Booking & Scheduling Automation
Our coaching business needed a better way to schedule. BoldBellows automated all of it: bookings, reminders, cancellations and follow-ups.
No-shows fell by 60% and clients enjoy how smooth it is. It feels personal, not robotic. One of the best upgrades we’ve made.
AI Translation & Localisation
When we expanded abroad we needed fast, accurate translations. BoldBellows built an AI translation system that turns our content into several languages instantly.
The translations read naturally and suit each culture. We now serve customers in five new countries without hiring translators. BoldBellows helped us go global.
AI HR & Recruitment Automation
Our HR team was drowning in applications. BoldBellows automated screening, skills-based filtering and interview scheduling.
It saves us hours every week and means we only interview qualified people. Hiring is now faster, better organized and more professional.
AI Accounting & Invoice Automation
BoldBellows automated our whole invoicing process: creating invoices, sending reminders and tracking payments.
Late payments dropped sharply, and our accounting team finally has time for strategy instead of repetitive admin. Worth every penny.
AI Data Entry & Reporting Automation
We used to spend hours collecting data and building weekly reports by hand. BoldBellows automated all of it.
The reports are clean, visual and easy to read, and our managers rely on them for quick decisions. Human error is gone and our numbers are more accurate across the board.
AI E-commerce Listings Automation
BoldBellows automated our product listings. The AI writes descriptions, organizes photos and publishes listings across several marketplaces.
It even answers customer questions instantly. Our store looks more professional and sales have noticeably increased.
AI Customer Journey Automation
We wanted a smoother path from first contact to purchase. BoldBellows built an AI system that guides each customer there automatically.
It sends personalized messages, recommends products and follows up at just the right moment. Customer retention has improved dramatically.
AI Social Comment & DM Automation
We get thousands of comments and messages every week. BoldBellows built an AI system that replies instantly, filters spam and surfaces the important ones.
Engagement is up and our page looks active around the clock. It’s like having a full social media team that never stops.
11FAQ
SharePoint and AI: what records and compliance teams ask before they trust it
We collected the questions that decide most purchases and answered them.
Do I need more than a model prompt on a SharePoint trigger?
Buying a label and a summary on every file from a connector is fine. Expecting it to decide which documents qualify, validate the model's structured answer and leave filing and permissions to a person is where they fall short. That is the difference between moving data and running a route.
Can the AI change my library by itself?
No. The model only returns a proposal. Applying metadata, moving a file or sharing it waits for the approval step you choose, and nothing changes until a person releases it.
Which parts of a document does the model see?
Only the text and fields on an approved list, passed as quoted data. Files above your sensitivity threshold, and anything else you exclude, never reach the model.
Could a document take over the model?
Document text is never treated as instructions.
What if a notification is missed or a file is saved twice?
A missed notice is made up from the list's change log, read from the last stored token, and each proposal is tied to the exact version it read.
Which model do you use?
For SharePoint AI Document Processing, the route works with the model service you approve.
How is access to the sites limited?
The app is granted only the sites you name, with the narrowest permissions that work, and what a provider retains depends on the plan we agree and document with you.
Do you show us each SharePoint field before it is used?
Included: a signed field map that separates reading, suggesting and writing for SharePoint.
Is the AI route configurable per team on the SharePoint AI Document Processing service?
Yes. We design the branching with you, and the SharePoint AI route follows it exactly, from $1,395.
What if the model provider changes its terms on the SharePoint AI Document Processing service?
The handover lists every interface the route uses. If one changes, the affected item stops and is flagged instead of being written from a guess. Repairs after your review window are quoted separately. It is also the answer to automate sharepoint with AI and custom sharepoint AI automation.
Next stepProcess documents faster, and keep the library in human hands
Give your library AI help with a person in charge
Entry price $1,395.
- From $1,395, paid once
- People file
- Text is data
- No monthly fee from us
Unusual volumes or extra systems are quoted on request.