Not chatbots. Agents that get work done in your systems.
Autonomous agents on Azure OpenAI that pull live data from AFAS, Exact and Dynamics, prepare decisions according to your rules, and execute actions in your existing software. All inside your Azure tenant, all audit-logged.
Four processes where it almost always pays back.
Not fashionable use cases. These are the four where volume is high enough, rules are clear enough, and ROI is visible within 6 months.
Quote & lead automation
Inbound quote request via email or form. Agent enriches customer via KvK, fetches current component prices from AFAS or Exact, generates a Dutch-language quote in your house style, and logs everything in CRM. Account manager approves or adjusts.
at 20 quotes/month: ~€4,700/mo in capacity
Invoice & document processing
Supplier invoices from email or upload. Agent reads with Azure Document Intelligence, extracts header and line fields, matches against purchase orders, routes to approver and pushes to your accounting after approval. Audit trail per decision.
at 500 invoices/mo: ~40 hours in capacity
Customer service agent (WhatsApp / email)
Incoming queries via WhatsApp Business, email or web form. Agent recognises intent (order status, return, appointment, complaint), pulls current data from your systems, replies in NL/EN or escalates to the right person with full context.
response time: minutes instead of hours
Internal knowledge agent (SharePoint)
Auditable answers from your own documents — SharePoint, Teams or network drive. Employees ask in plain language, agent answers with source citations. Replaces endless hunting for the right manual, the latest contract or specs from a previous project.
faster onboarding for new hires
Four steps, every decision logged.
An IITS agent is not a black box. Every iteration of the loop is captured in Application Insights — input, reasoning, tool call, output. Your auditor and compliance officer get what they need.
Agent receives an event: email, form, WhatsApp message, scheduled trigger. Full context stored for reproducibility.
LLM determines which tools are needed for this specific query. Plan is logged before execution — no action without traceable reasoning.
Agent invokes tools: KvK API, AFAS, Exact, Dynamics, Document Intelligence, AI Search. Each call and response is logged in your Application Insights.
Output passes through guardrails: business rules, decision threshold, human-in-loop for high-stakes actions. No action leaves the loop unchecked.
The Dutch stack, built in.
We maintain stable connectors for the software your business runs on. No weeks of brittle scraping — tested, OAuth-safe tools that agents call directly.
Four committed choices. Set upfront, not along the way.
How IITS agents work is not a project-specific debate. These are the defaults every implementation is built on — compliance is built in, not bolted on.
All workloads in EU data centres
Azure OpenAI in West Europe or Sweden. Logging, retrieval indexes and function calls stay in EU region. No data leaves the region without your explicit choice.
Your Azure subscription, your keys
Where possible we deploy in your own Azure tenant. You own the Key Vault, the infrastructure, the logs and the data. If we stop, you still own everything.
Every decision traceable
Application Insights logs input, model reasoning, tool calls and outputs per request. EU AI Act, GDPR audit and NIS2 requirements get what they need without ad-hoc data extraction.
Data minimisation by design
Tools receive only the fields they need for their task. A quote agent sees no HR data. An invoice agent sees no CRM notes. Per-tool scoping is a design principle.
Three scale tiers. Setup + monthly.
One-off setup covers scoping, build and delivery. Monthly covers monitoring, support and infrastructure-as-code maintenance. Azure consumption (OpenAI tokens, storage, compute) runs in your subscription — you pay Microsoft directly.
One task, one source
For one bounded task with one source. A FAQ bot, a simple knowledge agent or a status-query responder.
- 1 use case, 1 integration
- Baseline monitoring & support
- 2 weeks delivery
Multi-step process
For processes combining multiple steps, sources and decisions. Document processing, quote flow, customer service with CRM integration.
- 2 – 4 integrations (AFAS, Exact, Dynamics, etc.)
- Human-in-the-loop approval flow
- Full audit trail in Application Insights
- 2-week pilot before production
- 3 months hypercare post go-live
Multi-agent orchestration
For system-wide automation with multiple cooperating agents, planning and complex integration layers. For organisations structurally automating part of their operation.
- Multi-agent with orchestrator
- 5+ integrations, custom connectors
- Production-grade observability
- Hand-over to internal team possible
What we almost always get asked.
Isn't this just ChatGPT with extra steps?
No, and the difference matters. ChatGPT is a general-purpose language model that generates responses. An IITS agent uses Azure OpenAI as one component within a controlled loop: it calls verified tools, reads live from your systems, applies business rules and logs every step. A chatbot can tell you what an invoice usually contains — an agent processes the invoice and pushes it to Exact.
What does Azure OpenAI consumption cost?
For a typical Medium agent, OpenAI consumption is between €40 – €200 per month at normal volumes (1,000 – 5,000 requests/month). That runs in your own Azure subscription, so you pay Microsoft directly. We use smaller models where possible (gpt-4o-mini for classification, gpt-4o for reasoning) to keep costs low without sacrificing quality.
What if the agent makes a mistake?
Good agents are designed to make predictable, not surprising, mistakes. For every high-stakes action (sending a quote, posting an invoice, calling a customer back), there's a human-in-the-loop. The agent prepares, a person approves. For low-impact actions (FAQ reply, ticket routing) you accept a known error rate — which we measure during the pilot and agree upfront.
My data — does it go to OpenAI in the US?
No. We use Azure OpenAI (not OpenAI directly). Azure OpenAI in EU region keeps prompts and responses inside EU data centres, doesn't use your data to train models, and falls under Microsoft's EU Data Boundary. Same models, different legal reality. For a notary firm or healthcare organisation, this is the difference between being able to use it or not.
Does this work in Dutch?
Yes. GPT-4 class models are strong in Dutch, including jargon, formal address forms and u/jij distinction. For specific house style we tune prompts; for sector-specific terms (construction, legal, financial) we use a terminology database.
Can we maintain the agent ourselves later?
Yes. Code in Git, infrastructure-as-code in Bicep/Terraform, deployment via DevOps pipelines. At the Complex tier, hand-over to your team is included by default; at Medium it's optional. We also don't build agents that depend on our hosting — everything runs in your Azure subscription.
Which process costs you the most time today? We scope it in 30 minutes.
In one call we determine whether the process suits an agent, what the pilot would cost and what ROI is realistic. No sales pitch — just the numbers.
Book a scoping call