Artificial Intelligence & Automation
Many working hours go into searching for information, entering data and repetitive compilation. The aim is to reduce manual work so your team has more time for valuable tasks. Metatek helps select suitable use cases, pilot and verify them, then integrate them into workflows with human oversight.
Metatek starts from specific tasks, defining inputs, outputs and evaluation criteria so you have a sound basis for choosing a solution.
Examples are reference scenarios, not completed client projects.
01
Helps search and summarise information from documents the organisation has approved for use. Answers should cite sources and respect each user's access rights.
Example uses
Looking up internal procedures, operating guides, product documentation and FAQs.
Design considerations
Document permissions, update mechanism, source citation and how to respond when information is insufficient.
02
Combines optical character recognition and document-processing techniques to classify, extract and standardise information from paper or electronic files.
Example uses
Intake of HR records, vouchers, contracts and forms within an agreed scope.
Design considerations
Data field set, exception checks and a confirmation step before updating systems.
03
Helps consolidate information from plans, reports and meeting minutes to track progress, tasks and open issues.
Example uses
Preparing meeting summaries, task lists, reminders and progress reports.
Design considerations
Data sources, update responsibilities and approval before sending or changing important information.
04
Connects work steps across forms, email and business systems. Identifies what can be automated, which steps need approval and how exceptions are handled.
Example uses
Request intake, assignment, notifications, approval routing and status updates.
Design considerations
Trigger conditions, operating permissions, logs and handling when a step fails.
05
Standardises data sources and builds reporting around management needs. AI can help interpret, suggest or flag points needing attention.
Example uses
Consolidating KPIs, detecting variances and preparing explanations of results.
Design considerations
Data quality, KPI definitions and who is responsible for checking before use.
Define who uses it, which work needs improving and how results are evaluated.
Clarify data sources, usage rights, access rights and conditions for sharing data with the chosen platform.
Define review steps, approvals and accountability for outputs.
Assess correctness, processing time, exceptions and running costs before scaling.
01
Clarify the work, data, users and expected outcomes.
02
Use representative data to assess results, limitations and the human review effort required.
03
Design permissions, inputs, outputs, approvals and exception handling.
04
Record usage quality, cost and feedback to define the next scope of development.
The level of automation depends on the nature of the work and the impact of decisions. Metatek proposes review or approval steps suited to each case.
Share the work that takes up time, the data you have and the results you want. Metatek will assess a suitable approach with you.
These applications can improve operations and user experiences. But when images are used to identify individuals, track behavior, or connect with customer profiles, the scope extends well beyond installing cameras. Your business is mana…
Read article
Being selected by AEON Vietnam to provide personal data protection consulting marks a meaningful milestone for Metatek, reflecting the confidence of a major retailer within Japan’s AEON Group.
Read article
Faster customer responses, less manual work, and more proactive cash-flow management. AI agents create value when they help departments work together to complete tasks—with measurable results.
Read article