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BitleApps

VAT 03859100830
Cap. Sociale €10.000

Milazzo, (ME) 98057
Italia
info@bitleapps.com
+39 3513671283

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AI engineering, built by a team that runs its own AI
in production
into Code

RAG, agents, LLM apps — designed to survive production, not demo. You own the source, the stack, the model choices. No lock-in.

Show me what to buildSee it live
Deployment
Success

What we build

Six AI capabilities — each one we have already shipped and run ourselves.

AI agents & agentic systems

Autonomous, tool-using AI that does real work and stays up. Proof: airtime runs autonomous AI agents producing live audio 24/7.

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RAG — retrieval-augmented generation

AI that answers from your data — grounded, cited, current (vector search + embeddings), not hallucination. Proof: DeepMEMA, our own retrieval engine, and the MELI assistant.

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LLM application development

Chatbots, voicebots, copilots and content generation built into your product. Proof: MEDIAJAM (production GenAI content) and MELI (AI assistant).

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LLM systems engineering

The hard part: evals, prompt versioning, guardrails, monitoring and drift control — because we operate our whole portfolio at our own risk.

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Predictive & real-time AI

Data + ML decisioning under pressure. Proof: AITradato (real-time trading AI) and hotiday (pricing AI).

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AI integration

Wire AI into your existing stack via clean APIs — you keep the keys. Mainstream/open stack, documented, no lock-in.

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AI — straight answers

Questions buyers actually ask

RAG or fine-tuning — which do I need?

Most of the time: RAG. If you need answers grounded in YOUR current data (docs, tickets, catalogues), retrieval-augmented generation is cheaper, faster to ship and easier to keep current than fine-tuning. Fine-tuning is for changing the model's behaviour/style, not for feeding it facts. We'll tell you which fits — or that you need neither.

How do you stop the AI from making things up?

Grounding + evals + guardrails. We retrieve from your trusted sources and cite them, constrain outputs, and run evals so we measure hallucination instead of hoping. In production we monitor it and catch drift early.

Is my data safe — who sees it?

Your data stays in your infrastructure / your keys wherever possible. We're EU-built and GDPR-native, and we scope data access to the task. No silent training on your data.

Build vs buy an off-the-shelf AI tool?

If an off-the-shelf tool solves it, buy it — we'll say so. We build when you need it wired into your own systems, your data, or a workflow no product covers. Honest build-vs-buy is part of the first conversation.

What does an AI build cost and how fast?

It depends on scope, so we start with a short scoping conversation rather than a guessed number. You get a concrete plan — what to build first, the stack, and the trade-offs — before you commit.

Do I own the model and the code?

Yes. You own the source and the stack is mainstream/open — no lock-in. You keep the keys and can take it in-house or to another team.