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AI integration

AI features and agents built into the systems you already run.

From an assistant inside your product to agents that take over repetitive workflows: EDS Labs connects language models to your data, tools and processes, and builds them like any other production software.

Useful AI is an integration problem, not a prompt.

A chatbot demo is quick to build. The hard part is connecting a model to the right data, the right permissions and the systems where work actually happens, and keeping results reliable once real users depend on them.

EDS Labs treats AI features as part of the product: with clear scope, defined data access, review points for people, logging and a release path. Model and hosting are chosen per project to fit the data and the requirements.

Scope

What can be included

01

AI features in products

Assistants, summaries, classification and drafting features inside web platforms, portals, dashboards and apps.

02

Knowledge assistants (RAG)

Search and answers over your own documents and data, with sources, access rules and a clear scope.

03

Agents and workflow automation

Agents that prepare emails, documents and CRM updates, with approval steps wherever a person should decide.

04

MCP and system integrations

Model Context Protocol servers and API connectors that give AI controlled access to internal tools and data.

Process

How the work usually runs

Start small, prove the value with real data, then move the working pilot into daily operation.

01

Assess the potential

Identify the workflows where AI saves real time, check data and systems, and agree on what a pilot must prove.

02

Build a pilot

Implement one focused use case with real data, review points for people and measurable acceptance criteria.

03

Operate and improve

Integrate the pilot into existing systems, add monitoring and extend it step by step once it holds up.