Korvanta AIService · Generative AI
Generative AI That's Grounded, Not Guessing
Custom pipelines for text, image, video and code — retrieval-augmented generation, fine-tuning and secure private deployments built for brand-safe, accurate output at scale.
Beyond the "ChatGPT Wrapper"
Generic prompting breaks down fast in production — inconsistent tone, hallucinated facts, no way to audit output. We build generative systems grounded in your own data via RAG, with evaluation pipelines that catch drift before your customers do.
When prompting isn't precise enough, we fine-tune open or proprietary models to lock in tone, structure and domain accuracy — with private deployment options for regulated industries.
What We Build
- → RAG systems grounded in your own data
- → Fine-tuned domain-specific models
- → Generative content & creative pipelines
- → AI code generation & developer tools
- → Secure, private model deployments
Where Generative AI Creates the Most Value
Content at Scale
On-brand copy, product descriptions and marketing assets generated and reviewed in a fraction of the time.
Knowledge Retrieval
Internal and customer-facing Q&A grounded in your actual documentation, accurate and current.
Creative & Media
Image, video and code generation pipelines tailored to your brand and product requirements.
FAQ
What is retrieval-augmented generation (RAG)?
RAG grounds a model's answers in your own documents and data at query time, reducing hallucination and keeping responses current without retraining.
Do you fine-tune models or only use prompting?
Both — prompting and RAG for most cases, fine-tuning when you need consistent tone, format or domain behavior prompting can't reliably deliver.
Can generative AI be deployed privately for compliance?
Yes — private cloud deployments using open-source models or enterprise agreements for regulated industries.
Ready to Build a Generative AI System That Holds Up?
Book a free strategy call — we'll show you exactly where RAG or fine-tuning fits your use case.