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.
GTM Execution$12K – $30K
Product-to-Market Execution
From working product to paying customers, faster.
5–8w
Typical timeline
30-day
Post-launch support included
100%
Analytics instrumentation
2-week
Post-launch window included
THE CHALLENGE
Sound familiar?
- You have a working product but no launch infrastructure or analytics in place
- You're flying blind — no visibility into where users drop off or why
- Your onboarding has high drop-off but you can't pinpoint where it breaks
- You're not running any product experiments, so you can't improve conversion
- Your AI features are in the product but users don't discover or use them
OUR APPROACH
How we solve it
We build the technical infrastructure for product-led growth — analytics instrumentation, A/B testing, onboarding optimization, and launch tooling. We make your working product measurable and your AI features visible to the users who need them.
What you receive
- Analytics instrumentation — Mixpanel, Amplitude, PostHog, or custom
- Funnel analysis: acquisition → activation → retention → revenue
- A/B testing framework with feature flags and experiment tracking
- Onboarding flow redesign and implementation
- AI feature surfacing: contextual prompts, smart defaults, in-product recommendations
- Launch readiness checklist: monitoring, alerting, rollback procedures
- Performance monitoring dashboard — uptime, latency, error rate
OUTCOMES
What you walk away with
01
Clear visibility into where users drop off — and why
02
AI features users actually discover and engage with
03
Onboarding completion improved through data-driven iteration
04
Product team can run experiments without an engineering ticket for every change
05
Launch week handled without surprises — infrastructure is ready
OUR DIFFERENCE
Why GTM Execution from Virinchi
Launch-ready infrastructure
We set up analytics, A/B testing, monitoring, and rollback procedures before you flip the switch — not after the first incident.
AI feature discoverability
We instrument your AI features to be discovered by users — not buried in menus. Adoption is engineered, not hoped for.
Domain-specific expertise
We've launched AI products for FinTech, HealthTech, eCommerce, and Industrial clients across four markets.
USE CASES
Real-world applications
AI Product Launch Programs
End-to-end launch execution for AI features — from internal readiness review to public release.
Onboarding Optimization
Data-driven redesign of user onboarding flows to improve activation and reduce time-to-value.
Growth Instrumentation
Comprehensive analytics stack setup that gives product teams accurate signals for iteration.
HOW IT WORKS
Our delivery process
01
Current State Audit
Review existing analytics gaps, conversion funnel health, and AI feature discoverability.
02
Instrumentation Plan
Define events, funnels, experiment hypotheses, and success metrics before touching code.
03
Implementation
Analytics setup, A/B framework, feature flags, and onboarding build.
04
AI Feature Surfacing
In-product AI integrations, contextual prompts, and smart defaults users will actually encounter.
05
Launch Prep
Load testing, monitoring setup, runbook creation, and staged rollout execution.
Is this right for you?
Best suited for
- Startups 6–12 weeks from launch who need to be market-ready
- Teams that shipped a product but have no analytics to guide decisions
- Founders whose AI features aren't being used because they're hard to discover
- Companies preparing for a funding round who need to demonstrate traction metrics
Not the right fit for
- Products that haven't been built yet — this service optimizes, not builds
- Companies with zero existing users looking for acquisition services
- Teams expecting marketing or growth campaign execution
Engineering Stack
Built with the tools that matter
38 production-grade technologies — every one battle-tested in shipped products.
INVESTMENT
Engagement & pricing
$12K – $30K
5–8 weeks
- Engages best when product is feature-complete or near-complete
- Analytics instrumentation can run in parallel with final development sprints
- 2-week post-launch support window included as standard
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.
No. This is technical and product execution — launch infrastructure, analytics, onboarding, and iteration. We do not run campaigns or manage paid channels.
Ideally 4–6 weeks before planned launch. We can also engage earlier to design the launch strategy in parallel with development.
We work with Mixpanel, Amplitude, PostHog, Segment, and custom event pipelines. Tool selection is driven by your budget, scale, and technical requirements.
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?