AI Services for Charleston Businesses
AI Services for Charleston Businesses
Systems that read your own documents and do your own work, running in cloud accounts your company owns.
What this work is
A model on its own answers general questions. It becomes useful to a business when it is pointed at that business's own material — the contracts, the job files, the price lists, the inbox — and wired into the systems where work already happens.
That wiring is the job. It runs on cloud services your company owns and pays for directly, so the documents stay in accounts under your control and every request is logged against a named user.
None of these systems learn from your files. They read them at the moment a question is asked, which is why the work takes weeks rather than years and needs no data science team.
What you get
What we build
Six things account for most of the work worth doing at a 20 to 200 person company.
An answer desk over your own files
Staff ask a question in Teams and get an answer with the file it came from named. Works over SharePoint, a file share, or a document store nobody has been able to search properly in years.
Document data extraction
One recurring document type — invoices, contracts, closing packets, job sheets — read into fixed fields and checked by a person on one screen instead of retyped.
Workflow automation
The steps between systems that somebody currently does by hand. Read the inbound thing, decide, write it into the CRM or the accounting system, and log what happened.
Assistants inside Microsoft 365
Copilot deployed properly, plus the agents that Copilot alone cannot do — the ones that need to reach a line-of-business system.
A phone that always gets answered
Calls answered, callers routed, appointments booked and messages taken, with a path to a person at any point.
Keeping it running
Model versions move, documents change, and spend drifts. Somebody has to own that after the build.
How it works
How the work runs
Look at what you have
A short review of where the documents live, what the tenant will support, and which job is worth doing first.
Build one thing
The first system goes in narrow and finished rather than broad and half-working. Usually a few weeks.
Put it in front of people
Real users, real questions, measured against what the answers should have been.
Keep it working
Model versions, retrieval quality and spend get reviewed on a set cadence.
In practice
What these look like in practice
Four shapes that account for most of the work worth doing at this size.
The question everyone asks the same person
A firm where one person knows how the pricing works, and everyone interrupts them. An answer desk over the existing policy and pricing documents takes most of those interruptions away, and answers name the document they came from.
The pile of paper that becomes a spreadsheet
Supplier invoices, delivery notes or timesheets that somebody keys in every week. Extraction reads them into fields and a person approves the batch on one screen.
The email that becomes a job
Enquiries arriving as prose that somebody retypes into the CRM. An automation reads the message, pulls out the detail and creates the record, flagging anything it is unsure about.
The report rebuilt every Monday
A recurring extract assembled by hand from two systems. Scheduled, built and distributed automatically, with a note when a source is missing.
What matters
What decides whether it still works in a year
These are the parts that are rarely discussed before a build and always decide how it ages.
Model versions expire
Deployed models carry a published retirement date, and the vendor sets the migration schedule. Anything built against a pinned version has a clock on it from the day it ships.
Retrieval quality is the whole product
Whether an answer is right depends on how documents were split, what was indexed, and how often the index is rebuilt when content changes.
Permissions decide what people see
An assistant returns what the person asking is entitled to see, so permissions get reviewed before anything is switched on.
Non-deterministic output needs a test harness
The same question can return two different answers. Checking one by hand proves nothing, so the work includes a way to test answers repeatedly against known-correct ones.
Spend is metered per request
Cost tracks usage rather than seats, so the build includes reporting on where the requests are coming from.
Documents move
The folder gets restructured, the template changes, someone renames a field. The system needs to survive that.
Who it is for
Who this is for
20 to 200 people
Big enough for the repetitive work to be worth automating, too small to hire an AI engineer.
Professional firms
Accountants, law firms, engineering and design practices — businesses whose product is documents.
Trades and field businesses
Contractors, property services and installers, where the paperwork arrives faster than anybody can type it.
Anyone already on Microsoft 365
The licences and the identity system are usually most of what is needed already.
Questions
Frequently asked questions
Does our data get used to train the model?
No. The model reads the documents at the moment a question is asked and does not learn from them. On Azure, prompts and completions are not used to train foundation models without your instruction.
Where does it actually run?
In a Microsoft or AWS account your company owns. CloudCentric builds and administers it, and the subscription and the data sit under your name.
Do we need Microsoft 365 Copilot?
Sometimes. Copilot is a licence that works across your Microsoft content. Work that has to reach a system outside Microsoft 365 usually needs something built alongside it.
How long does the first system take?
A narrow first build is normally a few weeks. Document extraction and answer-desk projects are the fastest because the scope is set by the document type.
What if we do not know what to automate?
That is what the readiness review is for. It ranks the candidates by what they are worth and how hard they are.
Do you work outside Charleston?
Yes — the Lowcountry, Beaufort, Bluffton and Savannah. The build work is remote; the conversations that matter happen in person.
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