Questions about automation?Let's make it simpler.

YesAutomate builds custom automation and technology solutions that help businesses reduce repetitive work, improve accuracy, connect systems and make better use of their data. We combine accounting and business process expertise with Robotics, AI/ML, OCR & Document AI, analytics, ERP implementation and custom software.

We bring business and accounting experience into the automation process. Our focus is not simply on deploying technology; it is on understanding the underlying process and determining what should be automated, which technology fits best and where human judgement should remain involved.

Finance and Accounting is a core area of our expertise, but our automation capabilities can be applied across functions and industries where repetitive workflows, document processing, data movement, reconciliation, reporting or decision support are involved.

Typically, we need to understand the current workflow, systems and tools involved, data or documents being processed, volume and frequency, business rules, exceptions, current team effort and the desired outcome. We don't need a perfectly documented process to start the conversation.

Start with a conversation about the process or business challenge. We'll understand how the work is currently being done, explore the automation opportunity and discuss the appropriate next step — whether that is an assessment, POC or implementation.

Processes involving repetitive data entry, reconciliation, reporting, document processing, system updates, email workflows and rule-based decisions are common candidates. Examples include invoice processing, bank and vendor reconciliations, MIS preparation, ERP data entry, report generation, document extraction and workflow automation.

We look at factors such as repetition, volume, process stability, rules, digital inputs, exception rates and the amount of human judgement required. Not every process needs automation, and not every process needs the same type of automation.

No. Some processes are best handled with rule-based RPA. Others may require OCR, AI/ML, analytics or a combination of technologies. We determine the appropriate technology based on the process rather than starting with a particular technology.

RPA is generally suited to structured, repetitive tasks that follow defined rules. AI can help when the process requires understanding documents, interpreting information, identifying patterns, making predictions or handling less-structured situations. Many real-world workflows can combine both.

Yes. OCR & Document AI can extract and structure information from invoices, contracts, forms, financial statements, scanned documents and other document types. AI can then be used for classification, validation, interpretation or downstream workflow actions.

Yes. We can build AI-powered conversational solutions that work with defined knowledge sources and business context, including document-based Q&A, assistants and voice or chat workflows.

Where appropriate, yes. The solution may involve an existing AI model, custom rules, retrieval-based approaches, machine learning, document AI or a combination. The architecture depends on the business requirement rather than assuming that a custom model is always necessary.

Yes. Solutions can work with existing applications, including cloud systems, desktop applications, ERPs, accounting platforms, portals, Excel and other business tools.

Generally, no. We design automation around the systems and workflows you already use wherever practical. The objective is usually to connect, extend or automate the existing environment rather than force a wholesale system replacement.

Our automation engagements are generally customized around the client's process, systems and business rules. We don't expect every organisation to change its process simply to fit a standard automation.

We start by understanding the current process, systems, rules, exceptions and business objectives. We then assess the automation opportunity, determine the appropriate technology, define the solution and, where appropriate, build a POC before moving toward implementation.

Yes. A POC can be useful when there is uncertainty around feasibility, process complexity, expected outcomes or technology. It allows the business to validate the concept before committing to a broader implementation.

It depends on the complexity of the process, number of systems involved, integrations, business rules, exceptions and testing requirements. A small automation or POC may move quickly, while larger multi-system workflows require more time.

Our objective is generally the opposite: to build around the existing workflow wherever practical. We understand the current process first and then design the automation around the way the business operates, rather than forcing teams to completely redesign their processes to accommodate the technology.

Data handling depends on the solution architecture and deployment model. Where possible, discovery and POC activities can use sample or redacted data. For production solutions, access, data handling, security and governance requirements are considered as part of the implementation.

Access requirements depend on the workflow. Where access to production information is required, permissions and access controls should be defined according to the process and system requirements. We aim to limit access to what the automation actually needs.

Yes. Automation can be designed with human-in-the-loop controls, particularly where exceptions, uncertainty, approvals or business judgement are involved.

Where required by the process, workflows can be designed to record relevant activities, validations, exceptions and outcomes to support traceability and review.

Depending on the engagement, we can provide monitoring, maintenance, support and refinements as processes and systems evolve.

The automation can be reviewed and updated as business rules, systems or workflows change. The extent of modification depends on how the change affects the underlying automation.

Yes. Solutions can be designed to handle increased transaction volumes, additional users, entities, systems or workflows where the underlying architecture supports it.

We look at the outcome of the process rather than simply whether a bot has been deployed. Depending on the use case, this may include time saved, accuracy, cost, process volume, exceptions and turnaround time.