LLM Integration
Embed AI into your products and workflows.
Zarsco integrates large language models — GPT-4, Claude 3.5, Gemini, Mistral, and open-source alternatives — directly into your existing products, internal tools, and business processes. We handle fine-tuning, prompt engineering, and production deployment.
Best-in-Class Models
We select the optimal LLM for your cost, latency, quality, and compliance requirements.
Production-Ready
Battle-tested pipelines for high-volume, low-latency LLM inference at scale.
Fine-Tuning
Custom fine-tuning on your proprietary data for domain-specific accuracy.
Cost Optimization
Smart routing, caching, and batching to minimize LLM inference costs.
What we do for you
Product Feature Integration
Add AI writing, summarization, Q&A, or classification features to your SaaS product.
Internal Knowledge Assistant
Build a company-wide AI assistant over your documents, wikis, and knowledge bases.
Code Generation Integration
Embed code autocomplete, documentation generation, or code review into dev tools.
Content Generation Pipeline
Automate blog posts, product descriptions, social copy, and marketing content.
Sentiment & Classification
Analyze customer feedback, support tickets, and reviews at scale.
Language Translation Service
Integrate multilingual AI capabilities for global product expansion.
Everything included in our LLM Integration service
We handle every aspect from strategy to launch so you can focus on outcomes, not execution.
- LLM selection and cost-performance benchmarking
- Prompt engineering and optimization
- Fine-tuning on proprietary datasets
- RAG pipeline development
- Streaming API integration
- Fallback and multi-provider routing
- Rate limit management and cost controls
- Evaluation framework and quality monitoring
Frequently Asked Questions
Which LLMs do you work with?
We work with OpenAI (GPT-4o, GPT-4-turbo), Anthropic (Claude 3.5 Sonnet, Haiku), Google (Gemini 1.5 Pro, Flash), Mistral, Llama 3, and other open-source models.
Should I use a cloud LLM or host my own?
Depends on your data privacy requirements, latency needs, and cost budget. We help you evaluate all options and can set up private deployments using Ollama, vLLM, or AWS Bedrock.
How do you handle LLM hallucinations?
We implement structured outputs, validation layers, confidence scoring, RAG-based grounding, and human-in-the-loop checks where accuracy is critical.
Can you fine-tune a model on our company data?
Yes. We support fine-tuning for OpenAI models, and supervised fine-tuning of open-source models (Llama, Mistral) on your proprietary datasets.
Ready to get started with LLM Integration?
Book a free consultation call. Our experts will assess your needs and outline a clear plan.