Services
AI automation built into your enterprise software
AI applied to specific operational work, such as reading documents, answering internal questions and preparing reports, engineered into the systems your teams already use.
What AI automation means in practice
AI automation uses language and vision models to do work that used to need a person to read, interpret or write something. Typical examples are pulling data out of invoices and contracts, sorting incoming requests, drafting replies, and turning raw figures into a written summary.
It differs from rule-based workflow automation in one way that matters: rules handle work that always looks the same, while AI can handle work that varies, like documents in different layouts or questions phrased in different ways.
OGLAT builds AI automation into the software itself. A standalone chatbot sits beside your work; an AI step inside your ERP, CRM or workflow system does part of the work, uses your own data, and leaves a record. Where a decision carries risk, a person reviews it before anything is final.
The Problem
Where AI automation earns its place
Hours spent retyping documents
Staff copy figures from invoices, purchase orders and forms into the system by hand.
Answers buried in files
Policies, contracts and past records exist, but finding the right paragraph takes longer than asking a colleague.
Reports assembled by hand
Someone spends the first days of every month pulling numbers together and writing the same commentary.
Requests sorted manually
A person reads every incoming email or ticket just to decide who should handle it.
What We Build
What we build with AI
Each of these is built as a feature of your system, with the same access controls and logging as everything else in it.
Document processing
Data extracted from invoices, orders, contracts and forms, checked against your records and posted to the right place.
Internal copilots
An assistant inside your system that answers staff questions from your own documents and data, with sources shown.
Automated reporting
Scheduled reports with written summaries that explain what changed and why it matters.
Classification & routing
Incoming requests read, categorised and sent to the right team, feeding straight into your workflows.
Alerts & anomaly flags
Unusual transactions, stock movements or delays flagged for a person to review.
Human review steps
Approval points built in wherever an AI output should be confirmed before it takes effect.
How We Work
How an AI automation project runs
- 01
Find the right task
We look for work that is repetitive, high in volume and costly in staff time, and rule out tasks where AI adds risk without saving much.
- 02
Test on your real data
Before building anything permanent, we measure how accurately the approach performs on a sample of your own documents or records.
- 03
Build it into the system
The AI step is engineered into the software your team uses, with access controls, logging and review points.
- 04
Monitor and tune
Accuracy is tracked after launch and the system is adjusted as your documents and processes change.
Who It's For
Where this fits best
- Finance and operations teams processing documents in volume
- Companies with large stores of internal knowledge that staff struggle to search
- Management teams that want reports written, not just charted
- Businesses already running an ERP or CRM that want it to do more
FAQ
Questions we hear most
Is this just a chatbot?
No. A chatbot is one possible interface. Most of what we build runs in the background: reading documents, classifying requests and generating reports inside your existing software, without anyone typing a prompt.
Is our data safe?
Data handling is decided during design, before any build. We agree which data the AI may access, where it is processed and who can see the results, and apply the same role-based access and audit trails as the rest of the system.
How accurate is it?
Accuracy depends on the task and the quality of the input, so we measure it on your own data before committing to a build. For high-stakes steps we add human review, so the AI prepares the work and a person approves it.
Do we need to replace our current systems?
No. AI steps can be added to software you already run, as long as it exposes its data through an API or database. When we are also building your ERP or CRM, AI is designed in from the start.
Which AI models do you use?
We choose the model per task based on accuracy, cost and where your data needs to stay. The system is built so the model can be swapped later without rebuilding the feature.
Related Services
Often built alongside
Workflow Automation
Automated workflows connecting sales, operations, and fulfillment — so work moves without manual handoffs.
Learn moreERP Systems
Custom ERP built around your actual operations — inventory, finance, HR, and procurement unified in one system.
Learn moreCloud & System Architecture
Resilient backend systems and cloud infrastructure engineered for enterprise scale and reliability.
Learn moreReady to build with OGLAT?
Tell us what your team needs to run on, and we'll scope the system that gets you there.