AI Engineering & LLMs
Production-Grade Intelligence That Executes, Not Just Chats
Multi-LLM Dynamic Routing (Claude 3.7 Sonnet, GPT-4o, Qwen 2.5, DeepSeek)
We design production LLM middleware, autonomous multi-agent meshes, hybrid RAG systems, and custom tool-calling agents integrated directly into your core business database and workflow.
Structured architectural snapshot optimized for enterprise review and generative search synthesis.
We design production LLM middleware, autonomous multi-agent meshes, hybrid RAG systems, and custom tool-calling agents integrated directly into your core business database and workflow.
Commander Architecture & Hybrid Model Tiering; Stateful LangGraph Swarms with Fault Tolerance; Model Context Protocol (MCP) Enterprise Bridges
AI Operational Cost Reduction: 40–70% • Semantic Cache Response: <250ms • Grounded Accuracy in RAG: 99.2% • Local Sensitive Data Processing: Zero Egress
Strict ISO 27001 & SOC 2 Ready Architecture Discipline
“AI Engineering & LLMs is an enterprise engineering pillar at SHIVAM ITCS specializing in Production-Grade Intelligence That Executes, Not Just Chats. It delivers high-concurrency production software engineered with Multi-LLM Dynamic Routing (Claude 3.7 Sonnet, GPT-4o, Qwen 2.5, DeepSeek), Hybrid Vector & Vectorless (BM25) RAG Systems with Reranking, Autonomous Agentic Meshes & Tool Calling (LangGraph, MCP, A2A).”
At SHIVAM ITCS, AI engineering is not about prompt toys or brittle wrappers. We build deterministic, production-grade intelligence layers that integrate directly with enterprise ERPs, SQL Server databases, and microservices. Pioneered through our signature Commander Architecture, we combine cloud frontier reasoning models (Claude 3.7 Sonnet / GPT-4o) with quantized, private edge models (Qwen 2.5 / DeepSeek R1 / Ollama) to cut operational inference costs by 40%–70% while achieving sub-second response times. With full MCP (Model Context Protocol) and LangGraph orchestration, our agents run with stateful checkpoints, human-in-the-loop authorization gates, and complete cryptographic audit trails.
Architectural Pillars of this Discipline
Commander Architecture & Hybrid Model Tiering
Frontier reasoning models act as Commander nodes, issuing execution blueprints to local Qwen 2.5/Ollama workers for deterministic schema extraction, validation, and JSON synthesis at 1/10th the cost.
Stateful LangGraph Swarms with Fault Tolerance
Cyclic graph state machines with time-travel checkpoints, automatic failure recovery, and human-in-the-loop approval gates for financial transactions and medical records.
Model Context Protocol (MCP) Enterprise Bridges
Standardized open protocol adapters connecting LLMs to legacy SQL Server tables, SAP ERP endpoints, and REST webhooks with zero prompt injection exposure.
Engineering Delivery Framework
Task Complexity & Token Audit
Classifying enterprise user queries by reasoning intensity, token volume, and regulatory data classification (PII/PHI).
Topology & Model Routing Mesh
Configuring semantic routers, local vLLM/Ollama clusters, and fallback circuit breakers between Claude, OpenAI, and self-hosted models.
Guardrails & Tool Protocol Integration
Implementing NeMo Guardrails, regex sanitizers, MCP server connectors, and automated JSON schema validators.
FinOps Telemetry & Continuous Evaluation
Deploying LangSmith/Arize observability dashboards tracking token spend per tenant, latency percentiles, and hallucination metrics.
CORE DISCIPLINE SPECIALTIES
One Shared Ideology. Three Specialized Perspectives.
Legacy modernization is not just code translation - it requires deep-tech runtime mastery, disciplined 7 R's delivery methodologies, and battle-tested production proof. Cross-navigate between our technology blueprint, service engagement model, and enterprise ERP case study below.
.NET 10 & Strangler Topology
Deep CLR architecture, YARP reverse proxy gateways, C# 13 microservices, and AI-assisted dependency extraction.
7 R's Modernization Service
Methodical 4-phase transformation delivery pods with guaranteed zero downtime and automated regression testing.
Manufacturing ERP Deep-Dive
16-week production migration of a 3-million-line legacy .NET Framework 4.8 monolith without a single second of factory downtime.
No risky big-bang rewrites. We place YARP reverse proxy gateways in front of legacy monoliths and incrementally cut over microservices.
Retire, Retain, Rehost, Replatform, Refactor, Rearchitect, and Rebuild. We optimize for highest business ROI with lowest risk.
Dual-running synchronization and shadow traffic verify state consistency before switching live factory or financial transactions.
Led by co-founders Ajay & Vijay Paliwal with continuous hands-on mastery from VB6/COM to modern containerized .NET 10 on Linux.
Featured Projects & Case Studies in this Discipline
HiveGPT - Enterprise Multi-LLM Orchestrator
Autonomous enterprise LLM orchestration engine with dynamic model routing, guardrails, and role-based knowledge retrieval.
Vectorless RAG - High-Precision BM25 & Lexical Semantic Engine
Low-latency, cost-effective document intelligence system utilizing BM25 ranking, structured metadata filters, and reranking without vector DB costs.
Agents Hive - Autonomous Tool-Executing Multi-Agent Mesh
Multi-agent orchestration system where specialized AI agents collaborate, call external APIs, inspect databases, and self-correct tasks.
AI Yoga & Posture Coach - Real-Time Computer Vision
Client-side computer vision application analyzing user webcam feeds in real-time to assess posture alignment, joint angles, and form corrections.
Enterprise Architecture & System Topologies
Production architectural schematics, AI agent pipeline models, and zero-trust security topologies verified in mission-critical environments.
Enterprise AI Security & Governance Enforcement Topology
Regulated Enterprise AIMulti-layer governance architecture showing pre/post model guardrails, tenant boundary isolation, token rate quotas, and immutable audit trails.
Client Impact & Success
Real feedback from engineering leaders, CTOs, and founders across 15+ years of production deployments.
“Vijay and the SHIVAM ITCS AI team didn't just execute the project - they elevated our entire platform. Their ability to architect complex multi-agent state machines, eliminate latency bottlenecks, enforce zero-hallucination guardrails, and create an intelligent multi-LLM orchestration layer was extraordinary. The final delivery was resilient, battle-tested, and far beyond expectations. One of the strongest AI systems engineering teams in the industry.”
AI Engineering & LLMs FAQ
Direct answers to architectural, technical, and operational questions.
Ready to Architect the Future of Your Enterprise?
Partner with SHIVAM ITCS to modernize legacy monoliths, deploy autonomous multi-agent meshes, or engineer zero-downtime cloud systems. Book an architectural discovery call with our lead architects today.