Generative AI integration into your existing systems
Generative AI delivers where it fits the systems you already run: the ERP, the CRM, the document management system. We integrate GPT-5.6, Claude Opus 5, Gemini 3.6, and custom fine-tuned models into your processes — without ripping and replacing. Pilot in 2-3 weeks, implementation in 6-12 weeks; delivered by a Budapest-based team.
The next step is the AI opportunity assessment: from HUF 500,000 + VAT.
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The first question in an adoption project is which process carries the most manual work: quote preparation, answering customer inquiries, reading through documents, searching across documents. Generative AI fits onto those, integrated into your existing ERP, CRM, and document management systems — without ripping and replacing. We build the integration over secure APIs with robust authentication.
Across our 46+ completed projects, automated processes reach a 40-45% efficiency gain; typical ROI is 6-12 months. At an insurance company, 78% of staff used the assistant fine-tuned on 12,000 documents within the first month — every answer links back to the original document.
We pick the model for the task: GPT-5.6, Claude Opus 5, and Gemini 3.6 over API, or open-source models on your own infrastructure where data cannot leave the environment. A full team carries the work: a project manager, senior developers, and an AI DevOps engineer; we run the EU AI Act risk classification at the start of every project.
What generative AI is used for inside a company
An assistant on your own knowledge base
Policies, product documentation, and past projects in one searchable place. Your team gets accurate answers without searching through documents, and every answer arrives with its source — you can see which document it is based on. We offer the internal AI knowledge base as a separate service; this page covers fitting it into your existing systems.
Content generation and decision support
The system drafts, summarizes, and pulls the data a decision needs — for emails, quotes, internal documents. Your colleague reviews and sends instead of writing from scratch.
Added to the systems you already run
We add AI capabilities to your existing ERP, CRM, and enterprise systems — without ripping and replacing. The AI appears where your team already works; the integration is built over secure APIs with robust authentication.
Agentic workflows
Where the process allows it, we build self-directing AI agents: they handle exceptions and escalate only when needed. We agree the escalation rules together during implementation. Custom AI agent development is described on its own service page.
How does the implementation work?
- 1
AI opportunity assessment — from HUF 500,000 + VAT
We review your processes and your existing systems: where the manual work happens, where the documents live, which ERP and CRM to connect to. The output is a written plan with cost and payback estimates that you can work from even if you continue without us.
- 2
Model selection and knowledge base
We pick the model for the task and assemble the retrieval layer from your own documents, so answers arrive with source citations. Where accuracy needs domain knowledge, we fine-tune the model on your data.
- 3
Pilot — 2-3 weeks
We test the system on one process in production conditions and measure the results. A small proof of concept is ready in 2-3 weeks and sets the baseline we measure back to after implementation.
- 4
Implementation and operations — 6-12 weeks
Integration with your existing systems, training for your team. Most projects go from kickoff to production in 6-12 weeks; an AI assistant or integration project is usually €15-40K. Source code, models, and data remain yours; monitoring and support are part of how we work.
Why Leventech
A complete team from one source
A project manager, senior developers, and an AI DevOps engineer take the project from assessment to production.
Our team has built production systems since 2013
46+ completed projects, 96% client satisfaction. What we build, we also operate and maintain.
EU AI Act and GDPR built into development
Risk classification at project start, data protection in the design, a go-live checklist before launch. We have experience implementing high-risk AI systems as well.
We tell you when you don't need AI
Sometimes a simple script, a better database query, or fixing the data quality is the right answer. If there is no viable use case, we say so — we don't sell AI for the sake of AI.
Common questions
We pick the model for the task. In enterprise settings we work with GPT-5.6, Claude Opus 5, and Gemini 3.6; where data cannot leave your environment, or the volume justifies it, we deploy open-source models on your own infrastructure (Meta Muse, Qwen3.8, DeepSeek V4, Mistral Large 3). For domain accuracy we fine-tune the model on your data. The assessment documents the choice and the reasoning behind it.
When needed, we deploy on-premise or on your private cloud, with open-source models running on your servers — your data never leaves your environment. Data protection is part of the design, and we run the EU AI Act risk classification at project start. Source code, models, and data remain yours.
We handle this with two things. Answers are built from your own documents through a retrieval layer and arrive with source citations: each answer links back to the original document, so it can be verified. Wherever the output leaves the company or carries a financial consequence, a human review point stays in the process — your colleague checks it and sends it. Anything the system cannot answer reliably is escalated to a person.
A small pilot is ready in 2-3 weeks. Most projects go from kickoff to production in 6-12 weeks. The assessment gives you the exact schedule: it depends on the number of systems to connect and the state of your documents.
The entry point is the AI opportunity assessment: from HUF 500,000 + VAT. An AI assistant or integration project is usually €15-40K; a document processing system €30-80K. After the assessment you get an exact quote — no surprises. Typical ROI is 6-12 months.
We integrate with existing ERP, CRM, and enterprise systems, as well as document management and email systems — without ripping and replacing. We build the integration over secure APIs with robust authentication. The assessment describes what each connection requires.
In most cases the retrieval layer is enough: the model answers from your own documents, with source citations. Fine-tuning is warranted when accuracy depends on domain language — industry terminology, legal or manufacturing-specific naming. At an insurance company we built an assistant fine-tuned on 12,000 documents; the assessment tells you which one you need.
The documents and a description of the process, in an accessible format: policies, product documentation, past replies, and the systems to connect to. During the assessment we review what exists and what is missing. No in-house IT team is required: we handle implementation, operations, and maintenance, and we train your team.
Still have questions?
Related resources
Start with a conversation
Tell us where the manual work goes and which systems your team works in; we tell you where generative AI fits. For monthly operations of an existing system, see our Managed AI Operations page; for the shared foundation under several AI workloads, our Enterprise AI Platforms page.
What would you automate in your business?
Tell us briefly about the task. We will reply by email to arrange an initial conversation.
The next step is the AI opportunity assessment: from HUF 500,000 + VAT.
What happens after you send?
In the first conversation we review the task, your existing systems and the outcome you need. Then we discuss whether a detailed assessment would help. We provide a proposal before any paid work.
Or reach us directly:
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