AI & Generative AI

Intelligent automation

Combining AI with workflow and process automation to remove manual effort from high-volume operations.

Vue d’ensemble

Many operational processes are still held together by people copying data between systems, reading documents and making routine judgments at volume. Intelligent automation combines workflow tools, integration and AI so that work moves through these processes with far less manual effort.

We start by mapping the process as it actually runs, including exceptions and workarounds. We then identify which steps suit rules-based automation, which need AI to read documents or classify requests, and which should stay with people, and we redesign the flow rather than simply automating the existing one.

Solutions combine workflow and RPA platforms, APIs, document AI and language models, with human-in-the-loop review for low-confidence cases. We build in exception handling, audit trails and dashboards so operations leaders can see throughput, quality and where work is getting stuck. The aim is a process that is faster, more consistent and easier to change when the business does.

Ce que vous obtenez

01Current-state process map with volumes, exceptions and handoffs
02Redesigned future-state process and automation blueprint
03Automated workflows with document AI and human review steps
04Exception handling, audit logging and operational dashboards
05Support model and handover documentation

Technologies que nous maîtrisons

Microsoft Power Automate
UiPath
ServiceNow
Azure AI Document Intelligence
Amazon Textract
n8n
OpenAI, Anthropic and Google model APIs

Nous sommes indépendants des éditeurs : les outils sont choisis en fonction de vos besoins et de vos investissements existants.

Les questions que l’on nous pose souvent

We already use RPA. Does intelligent automation replace it?

Usually not. AI extends what your existing automation can handle, such as unstructured documents, emails and judgment-based classification, while RPA and workflow tools continue to run the deterministic steps.

Which processes make good candidates?

High-volume processes with clear inputs and outputs, a meaningful share of manual handling and measurable cycle times are the best starting points. Examples include invoice processing, claims intake, customer onboarding and service request triage.