AI Development & Integration
Enterprise AI integration is the work of connecting AI models to company data, applications and workflows so AI is actually used in operations. As an AI integrator, MBT builds the applications, data pipelines and access controls around existing AI models. We do not develop our own foundation models.
AI Engineering & Integration, Enterprise AI Integration
Business problems
SOPs, policies and manuals are hard to search, so the same questions keep reaching the same people.
Data from invoices, purchase orders and forms is retyped into systems and prone to errors.
Summarizing reports, classifying requests and drafting replies are done by hand every day.
What we build
Four capability groups, each of which can start from a single use case.
Example applications
Employees ask about SOPs, HR policies or IT procedures and get answers with document references.
Invoice, purchase order or import document data is extracted automatically and validated before entering the ERP.
Meeting recordings are transcribed, summarized and action items are sent to the task system.
New tickets are categorized and routed to the right team based on the request content.
An assistant that drafts replies, reports or summaries from system data.
Product, vendor or next-action recommendations based on company historical data.
Architecture & approach
AI is treated as a system component: its quality is measured, its access restricted and its cost monitored.
Select a use case with clear value and check data availability and quality.
Build a proof of concept with real data to measure answer quality.
Test accuracy, latency, cost and risk before wider rollout.
Connect AI to existing applications, access rights and workflows.
Track quality and cost, and improve the system regularly.
Technology & integration
The components we use to build AI applications on top of available models.
Deployment
The deployment choice depends on data sensitivity, required quality and cost.
| Option | Description | Best for |
|---|---|---|
| Model via API (cloud) | The application calls commercial AI models through an API, with control over the data sent. |
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| Private / on-premise | Open-source models run on internal servers so data never leaves the company network. |
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| Hybrid | Sensitive data is processed internally while general tasks use models via API. |
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Specializations
AI copilots, summarization and document Q&A that work with company data and systems.
Explore Generative AIEnterprise knowledge chatbots that answer from internal documents with source references and per-user access control.
Explore RAG DevelopmentOCR, document classification and data extraction from invoices, purchase orders and import documents, validated before entering systems.
Explore Document AITranscribe voice recordings and meetings into text that can be searched, summarized and passed to work systems.
Explore Speech-to-TextClassification, recommendations and AI steps embedded in workflows you already run.
Explore AI AutomationAI agents that run multi-step work with restricted tools, clear logs and human approval.
Explore AI Agent & Agentic WorkflowFAQ
Tell us which process you want AI to support. We will help assess feasibility, the data required and the proof of concept steps.
