RAG vs Fine-Tuning: Choosing the Right LLM Approach for Your Product
Both RAG and fine-tuning improve LLM performance on your specific use case — but they solve different problems. Here's how to choose.
Custom AI$15K – $45K
Custom AI Solutions
AI that fits your business exactly.
50+
AI systems delivered
100%
IP ownership transferred
$0
Vendor lock-in
6–12w
Typical timeline
THE CHALLENGE
Sound familiar?
- Off-the-shelf AI APIs produce inconsistent results on your domain data
- You've built a prototype but it's unreliable under production conditions
- Your data is unique — generic models don't understand it well enough
- You're worried about cost and vendor lock-in with large AI providers at scale
- You need AI that integrates with your existing systems, not a standalone tool
OUR APPROACH
How we solve it
We design, train, and deploy AI systems built specifically for your problem. Whether it's a fine-tuned LLM, a custom classification model, or an AI-powered workflow engine — engineered to perform reliably in your production environment, on your data.
What you receive
- Custom model or fine-tuned foundation model trained on your domain data
- Documented training and inference data pipeline
- REST API or embedded inference endpoint
- Model evaluation framework with accuracy benchmarks
- Integration with your existing product or backend
- Drift monitoring and retraining pipeline
OUTCOMES
What you walk away with
01
AI that understands your domain — not just the internet
02
Consistent inference performance under real production load
03
Lower inference cost vs. generic API calls at scale
04
Full IP ownership — no dependency on a third-party model provider
05
Traceable model decisions for regulated industry requirements
OUR DIFFERENCE
Why Custom AI from Virinchi
Production-first engineering
Every system is built to production standards from day one — no notebook demos, no prototypes handed off as products.
Full IP ownership
All code, model weights, pipelines, and documentation are transferred to you. No licensing, no lock-in, no vendor dependency.
Domain-specific expertise
We've shipped AI for FinTech, HealthTech, eCommerce, and Industrial clients across four markets. We know your sector's constraints.
USE CASES
Real-world applications
Intelligent Document Processing
Extract structured data from unstructured documents with high accuracy using fine-tuned models.
Personalization Engines
Real-time AI that adapts product recommendations and content to each user's behavior.
Predictive Risk Models
Custom ML models that score risk, detect anomalies, or forecast outcomes for your domain.
HOW IT WORKS
Our delivery process
01
Problem Scoping
Map requirements, data sources, and success metrics. Define 'good' before writing a line of code.
02
Data Preparation
Clean, structure, and validate data quality. Confirm the data can support target model performance.
03
Model Development
Train, fine-tune, and evaluate against agreed benchmarks. Iterate until performance targets are met.
04
Integration
Deploy into your product, connect APIs, and test under production-like conditions.
05
Handover
Load testing, monitoring setup, documentation, and team knowledge transfer.
Is this right for you?
Best suited for
- Startups where generic AI APIs produce inconsistent or inaccurate results
- Companies with proprietary data that would benefit from domain-specific training
- Teams that need AI as a core product feature, not a bolt-on tool
- Founders who've hit the limits of no-code AI tools
Not the right fit for
- Projects solvable with a standard API call and a well-crafted prompt
- Startups with no labeled or structured training data
- Teams looking for a quick demo rather than a production system
Engineering Stack
Built with the tools that matter
38 production-grade technologies — every one battle-tested in shipped products.
INVESTMENT
Engagement & pricing
$15K – $45K
6–12 weeks
- Milestone-based delivery — checkpoints at each phase
- Full source code and model weights delivered — you own everything
- Retraining pipeline available as an optional addition
Ready to start?
Get a detailed proposal within 48 hours. No commitment required.
Frequently Asked Questions
Didn't find what you were searching for? Reach out to us at [email protected] and we'll assist you promptly.
When your use case requires domain specificity, proprietary data advantages, latency constraints, or cost efficiency at scale that off-the-shelf APIs cannot provide.
Yes. We assess your data during discovery and design training pipelines around your existing data infrastructure — whether on-premise, cloud, or hybrid.
We agree on accuracy targets during scoping — before any model work begins. Delivery is measured against those benchmarks, not against our internal estimation.
FROM OUR CLIENTS
Built with teams who ship
The team took our AI concept from whiteboard to production in 10 weeks. The architecture they designed handles 10x our expected load with no issues.
Insights
From our engineering blog
A collection of detailed case studies showcasing our design process, problem-solving approach,and the impact of our user-focused solutions.
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READY TO START?