AI Integration Services
Connect AI capabilities into the apps and systems you already run. Reliable connectors, structured outputs, provider routing and cost controls, so AI becomes part of your stack.
What AI integration means for your business
A capable model is only useful when it is wired into the systems where work happens: the CRM, the ERP, the internal tools. AI integration is that connective work, done reliably.
We build the connectors, enforce structured outputs so downstream systems can trust the data, route across providers, and control cost, so an AI feature behaves like a dependable part of your stack.
- Reliable connectors into your CRM, ERP and internal tools.
- Structured outputs downstream systems can rely on.
- Provider routing and cost controls built in.
Systems we integrate AI with
Most of the value from AI comes from putting it inside the systems your teams already use, not from launching another app nobody opens. We connect language models and machine learning to:
- ERP: SAP S/4HANA and ECC, Microsoft Dynamics 365, for example to read incoming orders, match invoices or flag unusual postings.
- CRM: Salesforce, HubSpot and Dynamics CRM, for lead qualification, account summaries and drafted follow-ups.
- Help desk: Zendesk, Freshdesk, ServiceNow and Jira Service Management, for ticket triage and suggested replies.
- Document stores: SharePoint, Google Drive, Confluence and DMS platforms, as the knowledge source for search and assistants.
- Data warehouse: Snowflake, BigQuery, Databricks or PostgreSQL, so AI features work on governed, current data.
For SAP AI integration we work through standard APIs, OData services and middleware, so core processes and upgrades stay untouched.
AI integration consulting
Before we write code, we check whether the integration will hold up in production. AI integration consulting covers four questions: does the architecture support the call volumes and latency you need, how is data accessed and secured, which provider and model fit your data protection requirements, and what will each AI call cost at full volume.
You get a short written assessment with the recommended architecture, the risks we see and a plan for a first integration. If an AI feature does not make sense for a process, we say so.
Generative AI integration
Generative AI integration connects large language models to your business data through APIs. Three building blocks make it reliable:
- Retrieval on your data: RAG over your documents and records, so answers come from your sources and cite them.
- Structured outputs: responses validated against a schema, so results flow into your systems as clean data.
- Guardrails: input and output checks, permissions per user and logging of every call for review and audit.
How we deliver an integration project
- Discovery: we map the process, the systems involved and the success metric.
- Prototype: a working integration on real data, tested against agreed cases.
- Production build: security review, error handling, monitoring and cost limits.
- Rollout: gradual release to users, with training and documentation for your team.
After go-live we monitor quality, latency and cost per feature, and adjust prompts, models or routing as usage grows.
What we connect
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System connectors
Reliable connections between AI capabilities and your CRM, ERP, help desk and internal systems.
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Structured outputs
Schema-validated outputs so AI results flow into your systems as clean, predictable data.
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Routing and cost control
Multi-provider routing, caching and monitoring so quality stays high and cost stays predictable.
Frequently asked questions
What are AI integration services?
Connecting AI models, including LLMs, to the systems your teams already use, so AI works inside existing workflows rather than in a separate tool.
Can you integrate AI with SAP?
Yes. We connect to SAP through its APIs and middleware to add document extraction, forecasting or assistant features without changing core SAP processes.
Is our data sent to external AI providers?
Only if you choose that. We can run models in your cloud tenant or use EU-hosted providers with data processing agreements.
How do you control AI costs after integration?
We add usage limits, caching and cost dashboards per feature, so you see the cost of every AI call.
Make AI part of your systems
Tell us where AI needs to plug in. We will scope reliable integration with structured outputs and cost control.