Document extraction
Turn consistent information from invoices, forms, surveys or supporting documents into structured data for review and onward processing.
Practical AI implementation
Apply AI where it creates measurable business value
Use AI inside well-defined workflows to process information, assist decisions and improve response speed—without pretending every task should become autonomous.
Useful, controlled, accountable
AI is valuable when the task, evidence and fallback route are clear.
The strongest opportunities usually involve high-volume information: reading documents, classifying messages, preparing drafts, retrieving knowledge or identifying what deserves attention. The AI component must still sit inside a reliable operating process.
Classification and routing
Identify the likely subject, urgency or next workflow while sending uncertain cases to the correct person.
Drafting and summarisation
Prepare customer responses, case summaries or internal updates from approved context, with review before sensitive communication.
Qualification and knowledge retrieval
Collect relevant information, surface suitable guidance and help teams respond consistently without exposing unrestricted actions.
Controls by design
Confidence is not the same as certainty.
Megabite designs the surrounding controls with the AI step: permitted data, confidence thresholds, human review, restricted actions, logs, exception handling and a clear route when the model cannot produce a responsible answer.
Human review
Place approval at the point where an incorrect output could affect a customer, payment or important decision.
Restricted actions
Give the workflow only the access it requires rather than allowing a model to act broadly across the operation.
Visible exceptions
Record uncertain, failed and unusual cases so people can intervene and the workflow can improve.
Where AI should not be used
Do not add uncertainty to a task that deterministic automation can solve.
Standard rules are usually better for exact calculations, fixed validation, permissions and repeatable transfers. AI should not make unsupported regulatory, engineering, financial or high-consequence decisions, and it should not receive sensitive data without an appropriate privacy and security design.
Choose the right mechanism
A useful workflow may combine conventional automation, an AI-assisted step and human judgement. Megabite first asks whether to configure, integrate or automate with rules before introducing a model.
Relevant work
Automation designed around an accountable operational outcome.
Recoups demonstrates the wider principle: prioritise the right work, make communications consistent, preserve human escalation and keep the operation visible.
Recoups
A controlled invoice-recovery workflow designed to improve follow-up consistency, finance visibility and the speed at which outstanding cash is pursued.
Read the case studyInvestment and questions
Prove one valuable use case before expanding.
Focused Fixes typically range from £1,000–£5,000. Custom Systems start from £3,000. Scope depends on data access, model/provider choice, controls, integrations and monitoring. Prices exclude VAT or IVA where applicable.
Can AI run the workflow without people?
Sometimes a low-risk step can run automatically, but full autonomy is not the default. The consequence of error determines review, confidence and escalation controls.
Can you use our existing documents or knowledge?
Potentially, subject to access, quality, permission and privacy. The project must define which sources are authoritative and what happens when evidence is missing.
How do you protect customer data?
Data minimisation, provider terms, retention, access and permitted processing must be assessed for the use case. Sensitive data is not sent to a model merely because it is technically possible.
How do we know whether AI is justified?
Start with volume, time, error consequence and the value of faster or more consistent handling. If rules can solve the task reliably, conventional automation may be better.
Find the AI use case worth implementing properly.
Bring the repetitive information work, current decisions and risk of error. We’ll establish whether AI, rules or a combined workflow is the credible route.