Enterprise integration
An AI system is only as useful as the systems it can read from and act on. Most of our work happens at that boundary, across ERP, CRM, finance and data platforms.
What it covers
- 01
ERP
SAP integration through APIs and existing middleware, including posting, validation and SAP-integrated dashboards. NetSuite for finance and procurement flows.
- 02
CRM and service
Salesforce integration for case routing, escalation and resolution workflows.
- 03
Cloud and platform engineering
Workloads on AWS, Azure and GCP, chosen for each use case after evaluation rather than by default.
- 04
Identity and access
AI actions carry the identity of the person and client behind them, so downstream systems can enforce their own authorization.
- 05
Data intake
Ingestion from email, EDI, file uploads and multiple providers, normalized for the systems and reports that consume it.
Where this sits
Every engagement follows Strategy, Build, Govern and Operate. This capability does most of its work in the highlighted stage.
- 01 · Strategy
Find where AI pays
We map processes, volumes and systems, then rank use cases by value and feasibility.
A funded roadmap and an AI CoE operating model
- 02 · Build
Embed engineers, ship systems
Forward deployed engineers work inside your teams and connect models to SAP, CRM, identity and data.
Production software in your environment, not a demo
- 03 · Govern
Control every AI action
Identity, policy, approvals, data controls and audit apply before anything executes.
A system your security and audit teams can sign off on
- 04 · Operate
Stay accountable after launch
Monitoring, evaluation, cost management and steady improvement against the original target.
Named owners, runbooks and measured outcomes