AI & AUTOMATION

Custom AI integration and business automation

Generative AI moved from buzz to a measurable business lever in under two years. But 80% of enterprise AI projects never go past the POC: unversioned prompts, uncontrolled hallucinations, exploding API costs, no integration with the existing IS. At CodingArt, we build productive AI solutions, wired to your data (secure RAG), monitored (LangSmith, Helicone), and with business guardrails. OpenAI, Anthropic Claude, Mistral, self-hosted open source models: we pick the stack that fits your use case, budget and sovereignty constraints.

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Estimate my budget

6-12 wk.

From brief to production deployment

-40%

Typical customer support time after RAG

RAG

Answers sourced on your documents

OpenAI · Claude · Mistral

Multi-model based on need

Industry challenges

POC that never reaches production

ChatGPT plugged in for a demo, everyone clapped, then nothing. No stable version, no monitoring, no eval. The project dies in 3 months.

Hallucinations & made-up answers

An LLM alone invents. Without RAG and guardrails, it confidently states false things about your catalogue, your law, your procedures. Legal and reputation risk.

API costs that silently explode

A poorly designed agent sends 50× more tokens than needed. OpenAI bill x10 the next month, no alert. No attribution per feature.

Sensitive data sent to US clouds

GDPR, medical secrecy, European customers: sending all conversations to OpenAI US without DPA, without EU region, without anonymisation — not acceptable.

Our solutions

Chatbots & RAG on your data

Indexing your documents (PDF, Confluence, Notion, SQL base), embeddings (OpenAI, Cohere, BGE), vector store (pgvector, Pinecone, Qdrant), sourced answers with verifiable citations. +40% accuracy vs LLM alone.

AI agents & business automation

Agents connected to your tools (CRM, ERP, Slack, Gmail, ticketing) via MCP, function calling or n8n / Make / Zapier. Email triage, ticket summary, quote generation, lead qualification workflows.

Governance, monitoring & cost control

Prompt versioning (PromptLayer, LangSmith), automated evals (Ragas, DeepEval), token / latency / cost monitoring (Helicone, Langfuse), guardrails (NeMo Guardrails), per-feature budget alerting.

Sovereignty & GDPR compliance

EU-hosted models (Mistral La Plateforme, Azure OpenAI EU, AWS Bedrock EU), self-hosting Llama / Mixtral on your infra, signed DPAs, upstream PII anonymisation, AI Act 2026 compliance audit.

Frequently asked questions

What our prospects ask us

Which AI models do you use?

We choose based on use case: OpenAI (GPT-4o, GPT-4.1) for versatility, Anthropic Claude (Sonnet, Opus) for long reasoning and agents, Mistral / Mixtral for EU and sovereign self-hosting, Llama 3 / Qwen for on-premise. We avoid lock-in: LangChain / LlamaIndex abstraction, switch model in 1 config line.

How much does a RAG AI chatbot cost?

Simple RAG POC (1 data source, 1 language): €8,000-15,000. Production solution with evals, monitoring, multi-source and deployment: €25,000-60,000. Recurring API cost: €200-2,000 / month depending on volume. Typical ROI: -30 to -50% customer support time in 3 months.

Is my data sent to OpenAI or Anthropic?

By default we use EU regions (Azure OpenAI EU, AWS Bedrock EU) with training opt-out and signed DPAs — your data does not train the models. For very sensitive cases (health, defense, sovereign data), we self-host Mistral / Llama on your infra or a sovereign cloud (OVH AI, Scaleway).

Do you also do automation without AI?

Yes. Many quick wins come from n8n / Make / Zapier workflows without LLM (CRM sync, Slack alerts, PDF generation, monitoring scraping). We often combine pure automation + targeted AI blocks: more profitable and more reliable than a monolithic agent.

Move from AI POC to real business value

Free audit of your AI use cases, working RAG prototype or agent within 3 weeks.

Request a quote

Estimate my budget

Custom AI integration and business automation