Artificial Intelligence
AI shipped to production. Not just demos.
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.
What we build for you
- Self-hosted private LLMs
- Llama, Mistral, Qwen, hosted on your infrastructure or a sovereign cloud. No data leaves your perimeter.
- Multilingual conversational agents
- French, English, Modern Arabic and Darija. Support chatbots, internal assistants, voice bots with dialect recognition.
- RAG on your documents
- Turn PDFs, wikis, Confluence and emails into a knowledge base queryable in natural language.
- Computer vision
- Arabic and French OCR, anomaly detection, quality control, face/document recognition for KYC.
- Fine-tuning on your data
- Specialise an open-source model on your business terminology, brand tone and real use cases.
- Evaluation & guardrails
- Automated test suites (RAGAS, LLM-as-judge), hallucination detection, full audit logs.
Real-world use cases
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Bank · Casablanca
Hybrid AI + rules credit scoring
A private LLM reads KYC docs while a tabular scorer rates solvency. Analysts keep control of edge cases.
-62% analysis time
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National e-commerce
FR / AR / EN / Darija chatbot
24/7 handles returns, order tracking, product questions. Escalates to human when confidence drops below 85%.
85% tickets auto-resolved
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Law firm
RAG over 120,000 case precedents
Multilingual contextual search across Moroccan legal databases. Traceable citations back to source.
4× faster research
How we work
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01
Scoping workshop (1 week)
We identify 2-3 priority use cases, map your data and quantify expected ROI.
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02
Scoped PoC (3-4 weeks)
A working prototype hooked to a sample of your data, deployed in a test environment.
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03
Production (4-10 weeks)
Industrialisation, dedicated infra, monitoring, guardrails, technical and business team training.
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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.
Frequently asked questions
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.
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.
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.
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.
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.
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.
Related services
See all servicesGot 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.