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.
AI Strategy$8K – $15K
AI Product Strategy
Your AI roadmap. Build-ready in weeks.
2–4w
Typical delivery
100%
Fixed-price scope
3×
Faster engineering kickoff
$0
Rework cost on clear roadmaps
THE CHALLENGE
Sound familiar?
- You have an AI idea but can't define what to build first
- You're unsure which AI capabilities are feasible for your data and budget
- Your roadmap keeps shifting because core assumptions haven't been validated
- You're burning runway on discovery with nothing concrete to show investors
- You don't have a technical co-founder to own architecture decisions
OUR APPROACH
How we solve it
We run a structured 2–4 week AI product strategy sprint. We validate your concept, assess your data readiness, define the highest-value AI features, and deliver a decision-ready roadmap and architecture blueprint — so engineering can start with confidence, not guesswork.
What you receive
- Product Requirements Document (PRD) with AI feature specifications
- Technical architecture blueprint with model selection rationale
- 90-day development roadmap with milestones and dependencies
- Data readiness assessment and gap analysis
- Build vs. buy analysis for AI components
- Investor-ready technical narrative
OUTCOMES
What you walk away with
01
Clarity on what to build in Phase 1 — and what to skip
02
Reduced risk of building the wrong AI feature before launch
03
Technical confidence in investor and co-founder conversations
04
Faster engineering kickoff — weeks of ambiguous discovery eliminated
05
Fixed scope means accurate cost and timeline estimates from day one
OUR DIFFERENCE
Why AI Strategy from Virinchi
Production-first thinking
Every roadmap we deliver is grounded in what is technically feasible to ship — not what sounds good in a deck.
Independent perspective
We have no incentive to sell you more work than you need. Our strategy sprint stands alone, and we say so upfront.
Domain-specific expertise
We've built AI for FinTech, HealthTech, eCommerce, and Industrial clients across four markets. We know your sector's constraints.
USE CASES
Real-world applications
Strategic AI Audit
Evaluate existing workflows to surface high-value AI integration points with measurable impact.
Product-Market Fit for AI Features
Define and validate AI feature bets before engineering investment begins.
Technical Due Diligence
Independent review of AI architecture for product teams preparing for fundraise or acquisition.
HOW IT WORKS
Our delivery process
01
Discovery
Understand your vision, constraints, data availability, and target users in a structured 2-day workshop.
02
Feasibility Audit
Validate technical assumptions, assess data maturity, and identify the highest-value AI features.
03
Architecture Design
Define system architecture, model selection, and key build-vs-buy decisions.
04
Roadmap Delivery
Deliver PRD, phased roadmap, milestone plan, and investor technical narrative.
Is this right for you?
Best suited for
- Pre-seed or seed founders with an AI concept and no engineering team yet
- Technical co-founders who want an independent architecture review before hiring
- Startups that received investor feedback to 'clarify your AI approach'
- Founders who've tried to scope AI features and keep hitting walls
Not the right fit for
- Companies with a defined roadmap that only need execution
- Teams expecting a pitch deck, not an engineering blueprint
- Companies with no domain data or access to relevant data sources
Engineering Stack
Built with the tools that matter
38 production-grade technologies — every one battle-tested in shipped products.
INVESTMENT
Engagement & pricing
$8K – $15K
2–4 weeks
- Fixed-scope, fixed-price — no hourly surprises
- Includes two revision cycles on the roadmap
- Most clients continue to Full-Cycle Dev or Custom AI Solutions after strategy
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.
A typical engagement includes a discovery workshop, technical feasibility study, data readiness assessment, prioritized feature roadmap, and a phased build plan with estimated effort and timelines.
Most strategy engagements run 2–4 weeks depending on complexity. We aim for a working roadmap in your hands within the first month.
Both. We work with seed-stage startups defining their first AI feature and enterprises adding AI capabilities to existing platforms.
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
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READY TO START?