Illustration of AI document processing

KANTEEK / Services

Artificial Intelligence

AI shipped to production. Not just demos.

KANTEEK
Artificial Intelligence

AI has left the lab. Today, companies that actually use it gain a tangible edge, provided they bridge the gap between demos and production.

Kanteek builds industrial-grade AI: private LLMs, multilingual conversational agents, computer vision, RAG on your documents. Everything is designed to run 24/7, be auditable and respect your data sovereignty.

01 /

What we build for you

01
Self-hosted private LLMs
Llama, Mistral, Qwen, hosted on your infrastructure or a sovereign cloud. No data leaves your perimeter.
02
Multilingual conversational agents
French, English, Modern Arabic and Darija. Support chatbots, internal assistants, voice bots with dialect recognition.
03
RAG on your documents
Turn PDFs, wikis, Confluence and emails into a knowledge base queryable in natural language.
04
Computer vision
Arabic and French OCR, anomaly detection, quality control, face/document recognition for KYC.
05
Fine-tuning on your data
Specialise an open-source model on your business terminology, brand tone and real use cases.
06
Evaluation & guardrails
Automated test suites (RAGAS, LLM-as-judge), hallucination detection, full audit logs.
02 /

Illustrative AI applications

Illustrative examples, not client references or guaranteed gains. Measure scope, period, human time, errors and costs before and after a pilot.

  1. Banking

    Hybrid AI + rules credit scoring

    A private LLM reads KYC docs while a tabular scorer rates solvency. Analysts keep control of edge cases.

    Measure in a pilot

  2. National e-commerce

    FR / AR / EN / Darija chatbot

    24/7 handles returns, order tracking, product questions. Escalates to human according to agreed validation criteria.

    Measure in a pilot

  3. Law firm

    RAG over a legal corpus

    Multilingual contextual search across Moroccan legal databases. Traceable citations back to source.

    Measure in a pilot

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How we work

  1. 01

    Scoping workshop (1 week)

    We identify 2-3 priority use cases, map your data and quantify expected ROI.

  2. 02

    Scoped PoC (3-4 weeks)

    A working prototype hooked to a sample of your data, deployed in a test environment.

  3. 03

    Production (4-10 weeks)

    Industrialisation, dedicated infra, monitoring, guardrails, technical and business team training.

  4. 04

    Run & improve

    SLA support, periodic retraining, continuous improvement based on user feedback.

Our AI stack

  • Llama 3.1
  • Mistral Large
  • Qwen 2.5
  • Claude API
  • OpenAI API
  • LangChain
  • LlamaIndex
  • vLLM
  • Ollama
  • Pinecone
  • FAISS
  • Weaviate
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Frequently asked questions

Contact us
01

How long does a typical AI project take?

A useful PoC runs in 3 to 4 weeks. Full production (integrated into your IS, with monitoring and guardrails) takes 2 to 4 months depending on complexity. We ship in increments, never in tunnels.

02

Do you need GPUs at our side?

Not necessarily. We can host on your cloud, on a Moroccan sovereign cloud (OCP), European (OVH, Scaleway) or American. For small volumes, a single A100 80GB is enough. Very large models can also be called via API (Claude, GPT-4o) through a zero-retention proxy.

03

How do you handle Modern Arabic and Darija?

We use natively multilingual models (Qwen 2.5, Mistral Large) and fine-tune on Darija corpora when relevant. For speech, we combine Whisper with post-processing specific to Moroccan Arabic.

04

Does my data stay confidential?

Yes. With a self-hosted private LLM, no data leaves your infrastructure. Logs are encrypted and audited. We sign NDAs and can host in fully air-gapped environments if required.

05

How do you measure AI quality?

We define metrics at scoping time: precision, recall, hallucination rate, user satisfaction. We use RAGAS, LLM-as-judge, and manually-curated test sets. Everything is reported in a dashboard you can consult at any time.

06

Can you fine-tune a model on our data?

Yes, it's one of our specialities. We use LoRA/QLoRA to keep costs down. For a 10,000-example dataset, fine-tuning takes 12-24h and costs about €300-800 in compute.

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Useful resources

Artificial Intelligence · 27 Oct 2026

AI consulting in Morocco: 9 decisions before launching a pilot

Artificial Intelligence · 22 Oct 2026

AI chatbot in Marrakech: scope a reliable project for a hotel or riad

Artificial Intelligence · 12 Oct 2026

Prompt injection in Morocco: secure business AI assistants

KANTEEK / Contact us

Got an AI project in mind? Let's talk.

Tell us about your use case in 2 minutes. We'll come back within 24h with an estimate and a roadmap.