Generative AI Solutions
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Generative AI Solutions

From prototype to production-ready generative AI faster than you think.

Deploy production-ready generative AI into your products and workflows chatbots, copilots, content pipelines, and more.

Veritaz Generative AI Solutions helps Swedish businesses integrate the power of large language models, image generation, and multimodal AI into their products, internal tools, and customer-facing experiences. We have hands-on experience building RAG systems, AI copilots, automated content pipelines, and conversational interfaces using both OpenAI, Anthropic, Google Gemini, and open-source alternatives. We focus on measurable outcomes: reduced manual effort, faster responses, better customer experiences.

Key Benefits

  • Reduce manual work by 40–70% in document-heavy processes
  • Build AI copilots that actually understand your domain
  • RAG systems that answer from your own knowledge base
  • Multimodal: process text, images, PDFs, and voice
  • Hallucination mitigation and factual accuracy controls
  • Cost-efficient: we help you choose the right model for the job

What's Included

AI chatbot & copilot development
Prompt engineering & evaluation
Multimodal AI (text, image, voice)
AI governance & safety

Our Process

A clear, structured approach from first conversation to delivery.

1

Use Case Discovery

We identify the highest-value generative AI use cases for your business based on effort saved, quality improved, and feasibility with your existing data.

2

Rapid Prototyping

We build a working prototype in 1–2 weeks to validate the approach and get real user feedback before committing to a full build.

3

Prompt & Pipeline Engineering

We engineer the prompts, retrieval pipelines, context management, and output validation logic that make the difference between a demo and a reliable production system.

4

Evaluation & Safety

We set up automated evaluation frameworks, red-teaming, and safety guardrails to ensure the system behaves as intended across edge cases.

5

Production Deployment

We deploy with full observability latency tracking, cost monitoring, quality metrics, and feedback loops for continuous improvement.

Technologies & Tools

OpenAI GPT-4oAnthropic ClaudeGoogle GeminiMistralLangChainLlamaIndexHaystackPineconepgvectorWhisperDALL·EStable DiffusionFastAPIStreamlit

Frequently Asked Questions

What is RAG and when should we use it?
RAG (Retrieval-Augmented Generation) combines a language model with a search system over your own documents. Use it when you need the AI to answer questions based on your specific knowledge base, policies, or product documentation rather than general world knowledge.
How do you prevent hallucinations?
We combine retrieval grounding, output validation, confidence scoring, and human-in-the-loop workflows for high-stakes use cases. There is no single solution we design the right set of controls for your risk tolerance.
Can you build this into our existing product?
Yes. We integrate via APIs into your existing tech stack. We have experience adding AI capabilities to SaaS products, internal tools, customer portals, and mobile applications.
What are the typical costs of running a generative AI system?
It varies significantly. A simple internal chatbot might cost €200–500/month in API fees. A high-volume customer-facing system could be €5,000+/month. We help you model costs before building and architect for efficiency.

Ready to get started?

Talk to our team about how Generative AI Solutions can help your business.

Start a Generative AI Project