AI process automation
We build AI automation for documents, enquiries and data, connecting business applications and systems around a specific process.
We start with where a task arrives, the information it needs and its expected output. AI can help with variable text or documents. Standard rules and integrations may be sufficient for other parts of the process.
From documents to system records
One example is reading selected document fields and preparing a record for further work. We first check formats, material quality, required fields and the destination system. Complex documents and missing information can need additional handling.
Organised customer enquiries
Automation can collect requirements, attachments and missing details, then prepare a brief. Drafting a quotation is a separate possibility. Scope and approval requirements depend on the specific process.
Connections to existing tools
We assess API access, documentation and permissions. We agree data mapping and how to handle duplicates, errors and retries. A CRM or system name alone does not confirm that an integration is possible.
Quality and value checks
We compare results with agreed examples and measure the work that can be reduced. We include exception handling, provider usage and maintenance. We do not promise savings without data about the current process.
What to prepare
Describe the current steps, data sources, output and task volume. List common exceptions and access limits. We define the first version, human involvement and delivery channel after learning the requirements.
Build and maintenance costs
Budget depends on data, integrations, usage and quality requirements. Build, care, hosting and AI/API costs are shown separately.
See the cost factorsRelated services
Describe your project
Start with your goal. The consultant can help define scope and an initial budget. You can also send an enquiry without an AI conversation.