appforge
AI development and integration

Artificial intelligence that fits your operations.

AI agents, RAG knowledge bases, LLM integrations, predictive models. Live AI systems that automate real workflows and produce a measurable edge. Not demos.

Kérek árajánlatot
Mit kínálunk
  • GDPR + EU AI Act compliant
  • On-prem or cloud-hosted LLMs
  • Auditable, transparent decisions
  • Measurable ROI in 3–12 months
Probléma → Megoldás

From LLM hype to a live, measurable product

Most teams use ChatGPT in a browser tab. We build AI systems that plug into your workflows, run on your data, and produce auditable output.

Manual ChatGPT copy-paste

  • hallucinations
  • no sources
  • no audit trail

RAG over your own data

  • source citations
  • measurable time and cost savings
Amit kínálunk

What you should expect from a serious AI partner

We don't hand out prompt-engineering tips. We build, deploy, and monitor live systems. Data sovereignty, transparency, and tooling your team can actually maintain.

AI agents

Autonomous AI agents that execute multi-step workflows without human intervention. Built on LangGraph, CrewAI, and AutoGen — for quote generation, customer handling, and data processing. Every step is auditable and transparent.

RAG knowledge bases

Your accumulated knowledge — documents, emails, contracts, internal wikis — becomes instantly searchable and queryable. LlamaIndex and LangChain architecture with ChromaDB or Pinecone for vector storage. 90%+ accuracy on your own knowledge base.

On-prem LLM hosting

Sensitive data never leaves your servers. We deploy large language models on your own infrastructure (Ollama, vLLM) that match cloud-hosted performance — with full data sovereignty. The right fit for finance, healthcare, and legal teams.

GDPR-compliant AI

Privacy isn't an afterthought. Every system is designed against GDPR and local regulation: data minimization, lawful basis handling, access controls, automatic deletion, full logging. We deliver DPIA assessments too.

Mire használják

Where AI pays back the fastest

Where we've consistently seen 3–6 month payback for SMBs and mid-market companies.

01 · RAG
Internal knowledge chatbot

HR policies, product info, process docs — one colleague who knows everything and answers in Slack or Teams. RAG, grounded only in your own documents.

01
02 · Support
Customer support AI

Tier-1 support 24/7, in your language, with up-to-date knowledge. Complex cases escalate to a human agent — with full context attached.

02
03 · OCR
Document processing

Automated extraction from invoices, contracts, and proposals. OCR + LLM + validation — accounting hours drop to a fraction of what they were.

03
04 · ML
Predictive analytics

Demand, churn, and revenue forecasts. Classical ML models paired with LLM-generated executive summaries.

04
Folyamat

AI projects in 5 steps

We don't open with a giant LLM platform. A focused pilot proves the concept first, then we scale.

01

01

AI audit

We identify 3–5 repetitive, document-heavy, or decision-bound processes where AI pays back the fastest. Concrete ROI math, no vapor.

02

02

Pilot in 4–8 weeks

A live, measurable solution for one chosen use case. Not proof-of-concept theater: your team uses it, and we count the savings.

03

03

Measurement

Hard numbers: hours saved, errors reduced, revenue captured. We use those numbers to plan the next step.

04

04

Scale-up

From a working pilot we expand into more processes, integrations, and tuning. Each step builds on what the last one already proved.

05

05

AI culture

Team training, AI champions, and ethical guidelines. The long-term value of AI lives in your people, not in the code.

Technológiák

AI stack

Model-agnostic by default. The use case decides whether OpenAI API, Claude, Gemini, or self-hosted Ollama / vLLM is the right call.

Python
OpenAI
Claude
LangChain
LangGraph
LlamaIndex
Pinecone
ChromaDB
FastAPI
Ollama
Hugging Face
PyTorch
Csomagok

What does an AI project cost?

Price depends on data volume, integration count, and whether fine-tuning is needed. Typical ranges:

AI integration
EUR 2.6k – EUR 7.9k

Existing LLMs wired into your current systems

  • OpenAI / Claude / Gemini API
  • 1 use case (e.g. chatbot, RAG)
  • Integrated into existing systems
  • Logging, monitoring
  • 1–3 month implementation
Let's start →
Legnépszerűbb
Custom RAG / agent
EUR 7.9k – EUR 21k

Your own knowledge base or autonomous agent

  • Knowledge base ingestion, embeddings
  • Vector DB (Pinecone / Chroma)
  • Source citations, audit log
  • Admin UI, monitoring
  • GDPR-compliant design
  • 3–6 months, in sprints
Let's talk →
On-prem LLM / fine-tuning
From EUR 21k

Your infrastructure, your model, full data sovereignty

  • On-prem Ollama / vLLM deployment
  • Industry-specific fine-tuning
  • Custom pipeline and integrations
  • Hardware advisory (GPU)
  • SLA, dedicated support
Book a call →

Detailed price comparison on the full pricing page: Részletes árazás →

GYIK

Frequently asked questions

Cost depends on the project type and complexity. A simpler chatbot or automation typically starts around EUR 2,600. A custom AI system (RAG knowledge base, predictive model, AI agents) runs EUR 7,900 to EUR 39,000. Data volume, integration count, infrastructure, and fine-tuning all move the number. Every project starts with a free consultation and feasibility review.
Kapcsolódó megoldások

Related services

AI rarely ships on its own. These services pair naturally with an AI project.

Web development

Plug AI features into your existing website or web app.

App development

Mobile apps with intelligent features: recommendations, OCR, speech recognition.

Webshop development

AI-driven product recommendations, cart recovery, customer segmentation.

Monthly website subscription

Continuous AI development and maintenance on a fixed monthly fee.

Ready for your first AI project?

Start with a free AI audit.

In 30 minutes we find where AI pays back fastest in your operation. Concrete use cases with projected ROI.

Book an AI audit
Free SEO audit
Start a project