Frequently Asked Questions

It depends on the scope. A functional MVP can be ready in 2-4 weeks. Complete enterprise systems require 2-3 months.

Yes. We offer Fractional CTO for startups and SMEs that need on-demand strategic advice without the cost of a full-time executive.

We don't sell hype. We have our own products in production (Naktor ARGOS, Naktor Knowledge, Remor) that demonstrate our real technical capability.

Yes. Our Partnership model includes continuous support, monitoring, and evolution of deployed systems.

We work with private AI architectures that can be deployed on-premise or in private clouds. We comply with GDPR and can adapt to specific compliance requirements.

Mainly Python, TypeScript, LLM frameworks (LangChain, LlamaIndex), vector databases (Pinecone, Weaviate), and cloud-native architectures.

We start with a diagnostic session to understand your context. Then we define scope, deliverables and timeline. Once approved, we kick off sprint 0 for architecture and within 1-2 weeks there's code in review.

We offer three models: Partnership (ongoing collaboration with monthly dedication), Projects (fixed scope with fixed price), and Fractional CTO (on-demand advisory). Each client chooses what best fits their situation.

Our standard SLA is 99.9% availability with response in less than 4 hours for critical incidents. We can adapt SLAs for specific enterprise requirements.

Yes. We design with integration in mind. REST/GraphQL APIs, webhooks, connectors to ERPs, CRMs and data platforms. We don't create silos, we connect ecosystems.

We have proven experience across insurance, finance, food, digital health, and public sector/energy, and our methodology adapts to any sector.

Yes. We design with privacy-by-design and can implement architectures that comply with GDPR, European AI Act, and sector-specific requirements like PCI-DSS or HIPAA.

We work with incremental deliveries and frequent validations. If something isn't working, we detect it quickly and pivot. We don't charge for code that doesn't add value.

Yes, through Naktor Academy. From AI adoption workshops for executives to advanced technical courses in agentic development for engineers.

Dedicated Slack channel, weekly follow-up meetings, and direct access to assigned architects. No account manager intermediaries.

An agentic system is an AI architecture where autonomous agents can make decisions, execute tasks, and use tools without constant human intervention. Unlike a simple chatbot, an agent can: 1) Plan sequences of actions, 2) Use external tools (APIs, databases), 3) Maintain context memory, 4) Self-correct when it detects errors. Examples: commercial prospecting agents, technical support automation, or autonomous inventory management.

The cost depends on scope and the impact you're after: a one-off diagnosis is not the same as an enterprise system in production. As a boutique, we scope each budget to your case in a first conversation, no strings attached. Tell us your situation and we'll give you concrete guidance.

RAG (Retrieval-Augmented Generation) and fine-tuning are two different approaches to customizing AI models. RAG connects the model to an external knowledge base, allowing updated responses without retraining the model. Fine-tuning modifies the model weights to specialize it for a task. RAG is better for: frequently changing knowledge, strict compliance, lower cost. Fine-tuning is better for: very specific tasks, style/tone changes, when you don't need to cite sources.

Developing in-house makes sense if: 1) AI is core to your business, 2) You have senior technical team available, 3) You have 6-12 months runway to experiment. Hiring a specialized consultancy is better when: 1) You need results in weeks, not months, 2) You don't have internal AI expertise, 3) You want to minimize technical risk with proven professionals. Naktor offers both options: we can build the complete system or train your team to maintain it.

ROI varies by project type. Process automation: 40-70% reduction in time for repetitive tasks. Sales/prospecting agents: 20-35% increase in qualified leads. Corporate RAG: 60% reduction in information search time. Support chatbots: 50-80% automation of level 1 tickets. Typical payback is 3-9 months depending on operations volume.