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Switch to Local LLMs.

Cut your AI costs by 60% while keeping data in India. We help small and mid-sized Indian businesses deploy powerful local LLMs—no token bills, no latency, no compliance worries.

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The Local First Advantage

Optimized for Indian SMEs. We utilize modern toolchains that prioritize efficiency and data sovereignty.

llama.cpp / vLLM

Flexible serving engines. llama.cpp for edge/consumer GPUs; vLLM for high-throughput cloud deployments.

Sarvam OpenHathi

Indic language support. Fine-tuned for Indian contexts, ensuring your AI understands local nuances.

Data Sovereignty

Deploy on-prem or via Indian GPU clouds (E2E/Neysa). Comply with India's DPDP Act effortlessly.

RAG Pipeline

Cost-effective alternative to fine-tuning. Connect Qdrant/Milvus + LangChain to your private docs.

ROI Case Study: Resorze

Client: IT Services | Team Size: 18 Employees | Location: Gandhinagar

The Challenge: API Costs in INR

TechStart was bleeding cash paying for GPT-4o-mini for customer support, internal docs, and code assistance.

Use Case	Monthly Tokens	Cost (INR)
Customer Support	2.5M	₹10,000
Internal Knowledge	3M	₹7,400
Dev Copilot	4.5M	₹9,300
Meeting Summaries	0.1M	₹1,500
TOTAL MONTHLY	~10M	₹28,200

The Solution: Starter Tier Deployment

We deployed Llama 3.1 8B (Q4 quantized) via llama.cpp on the client's existing RTX 4090 workstation — no new hardware required.

₹7.63L 3-Year Net Savings

9.5 Months to Break Even

90ms Local Inference Latency

✅ Data never left India (DPDP Compliant) ✅ No token anxiety for dev teams ✅ Works during internet outages

Transparent Pricing

Choose the engagement model that fits your stage.

Free LLM Cost Audit

₹0

Token usage analysis
Break-even estimate
Hardware recommendation

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Pilot Project

₹18,000

2-week proof-of-concept
Single use case focus
Performance benchmarking

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POPULAR

Starter Deployment

₹55,000

End-to-end Setup (llama.cpp)
3 Months Support
Staff Training
Latency Optimization

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Growth Upgrade

+₹35,000

A100 Cloud Slice Setup
Hybrid Routing Logic
Advanced Fine-tuning (LoRA)