AI service
Generative AI & LLM App Development
Products powered by large language models — from first prototype to production.
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What is generative AI development?
Generative AI development means building applications on top of large language models (LLMs) that write, summarise, classify, translate and reason over your data. Unicorn Softech builds LLM-powered features and full products, handling prompt design, model selection, fine-tuning, evaluation, cost control and deployment.
See it
What it looks like
Summarise this 40-page report in 3 points
AI
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How it works
Generative AI & LLM App Development in 5 steps
- 01Your data
- 02Prompt + context
- 03LLM
- 04Evaluate
- 05AI feature
What we deliver
What you get with Generative AI & LLM App Development
LLM product engineering
Copilots, content tools, document processing and AI features inside your app.
Prompt & context engineering
Structured prompts, tool schemas and context pipelines that stay reliable at scale.
Model selection
Choosing between hosted and open-source models on quality, speed, cost and privacy.
Fine-tuning
Adapting models to your domain language and output format when prompting is not enough.
Evaluation & testing
Golden datasets and automated scoring so quality is measured, not guessed.
Cost & latency tuning
Caching, routing, streaming and batching to keep bills and response times low.
Common use cases
- AI copilots inside SaaS products
- Document extraction and summarisation
- Content and marketing generation tools
- Code and data assistants for internal teams
- Multilingual translation and localisation
Tools and technology
We choose per project. These are the tools we use most for generative ai & llm app development.
- OpenAI
- Anthropic Claude
- Google Gemini
- Llama
- Mistral
- Hugging Face
- LangChain
- Vercel AI SDK
- LLM product engineering
- Prompt & context engineering
- Model selection
- Fine-tuning
- Evaluation & testing
- Cost & latency tuning
- AI copilots inside SaaS products
- Document extraction and summarisation
- Content and marketing generation tools
- Code and data assistants for internal teams
- Multilingual translation and localisation
FAQ
Generative AI & LLM App Development: common questions
Which LLM should I use for my product?
It depends on the task. We benchmark several models on your real data for quality, latency and cost, and often route simple requests to a small model and hard ones to a larger model.
Can generative AI run on our private data safely?
Yes. We use providers with zero-retention options or deploy open-source models in your own cloud, and we keep access control at the data layer so the model only sees what the user is allowed to see.
Do I need fine-tuning?
Usually not at the start. Good prompts plus retrieval solve most cases. Fine-tuning helps when you need a specific style, strict format or lower cost at high volume.
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Let's talk about Generative AI & LLM App Development
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