KALKI-1.5

KALKI AI — Business Model, Cost Estimation & Scalability Plan

1. Cloud Infrastructure Cost Estimation (Monthly Projections)

Component Resource Specification Unit Cost Projected Monthly Cost (100k Users)
GPU Inference Cluster 8x NVIDIA H100 SXM (vLLM Engine) $3.50 / GPU-hr $20,160
Vector Storage (Qdrant) 3-Node Cluster (128GB RAM, SSD) Managed Cloud $1,200
Relational Database AWS Aurora PostgreSQL (Multi-AZ) db.r6g.2xlarge $1,450
Caching & Pub/Sub Redis Enterprise Cluster 32 GB RAM $450
Object Storage AWS S3 (Document storage & backups) 10 TB $230
Total Estimated Infrastructure Cost     ~$23,490 / month

2. Horizontal Scalability Roadmap

graph LR
    Tier1["Phase 1: Single Cluster<br/>10k DAU<br/>Monolithic Gateway + Qdrant"] --> Tier2["Phase 2: Microservices<br/>500k DAU<br/>Ray LLM Cluster + Distributed Redis"]
    Tier2 --> Tier3["Phase 3: Multi-Region Global Mesh<br/>10M+ DAU<br/>Anycast Edge SLMs + Cloud MoE Fallback"]

3. Risk Assessment & Mitigation Matrix

Risk Factor Severity Probability Mitigation Strategy
Prompt Injection Attack High Medium Dual-pass Security Agent verification using Llama-Guard 3 + static input sanitization.
Hallucination in RAG Outputs High Medium Validator Agent verification threshold ($>0.85$ grounded confidence rating) before sending output.
GPU Capacity Exhaustion Medium High Automatic graceful degradation to quantized local Edge SLMs or speculative decoding.
Privacy Data Leakage High Low Dynamic PII anonymization regex layer on all document ingestion pipelines.