The Enterprise AI & Architecture GlossaryArchitecture Glossary
A peer-reviewed, battle-tested reference for CTOs, VPs of Engineering, and software architects navigating the paradigm shift from fragile single-turn chatbots to autonomous multi-agent execution swarms.
Zero Hallucination Benchmarks•Production Code Blueprints•Direct Case Study Proof
23 Standards
Curated Specifications
5 Core Pillars
Architectural Domains
100% Deployed
Production Battle-Tested
AEO & LLMO
Graph Citation Ready
Popular Architecture Specs:
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Depth:
Index:
Matching: 23 TermsSelect term to inspect
Agentic AIAG-AI
2 min read
Agentic AI
AI systems capable of autonomous multi-step reasoning, goal formulation, tool execution, and self-correction without step-by-step human prompts.
Autonomous AgentsReasoning LoopsLangGraph
Agentic AILG-SM
3 min read
LangGraph State Machine
A cyclical graph-based framework for orchestrating stateful, multi-agent workflows with durable persistence and human-in-the-loop checkpoints.
State GraphsCheckpointsPostgreSQL
Agentic AIReAct
2 min read
ReAct Reasoning Loop
A cognitive pattern combining Reason (thought formulation), Act (external tool invocation), and Observe (analyzing execution feedback) in a tight feedback cycle.
ReasoningAction ObservationSelf-Healing
Agentic AISK
3 min read
Microsoft Semantic Kernel
Microsoft enterprise open-source SDK that integrates LLMs with conventional programming languages (C#, Python, Java) via native function calling and memory plugins.
.NET 10C#Enterprise AI
Agentic AISAI-Node
3 min read
Sovereign AI Node
An isolated, on-premises or private VPC inference cluster running open-weight models with zero telemetry egress and full regulatory compliance.
Data SovereigntyAir-GappedPrivate Compute
Agentic AIHITL
2 min read
Human-in-the-Loop (HITL) Gateways
Asynchronous architectural pause points that require verified human authority approval before high-stakes agent actions are committed.
SafetyApproval GatesAuditing
Protocols & ArchitectureCA-Pillar
3 min read
Commander Architecture
A hybrid multi-tier orchestration pattern that pairs a high-reasoning frontier cloud model (Commander) with local lightweight models (Specialists) to slash costs by 40%–70%.
Hybrid AICost OptimizationRouting
Protocols & ArchitectureMCP
3 min read
Model Context Protocol (MCP)
An open protocol standard created by Anthropic that standardizes how AI models discover and connect to external enterprise data sources, tools, and environments.
AnthropicOpen StandardTool Discovery
Protocols & ArchitectureA2A
3 min read
Agent-to-Agent Protocol (A2A)
Standardized communication and contract specifications enabling independent AI agents to negotiate tasks, delegate workloads, and exchange state across organizational boundaries.
Inter-Agent CommState ExchangeSwarms
Protocols & ArchitectureSFM
3 min read
Strangler Fig Modernization
An architectural migration pattern that incrementally replaces legacy monolithic subsystems with modern cloud-native microservices with zero downtime.
Legacy ModernizationZero Downtime.NET 10
Protocols & ArchitectureYARP
3 min read
YARP Reverse Proxy Modernization
Yet Another Reverse Proxy: a toolkit for building high-performance, programmable HTTP reverse proxy servers in ASP.NET Core.
Reverse ProxyTraffic SlicingZero Downtime
Protocols & ArchitectureCQRS
3 min read
CQRS & MediatR Pattern in .NET 10
Command Query Responsibility Segregation: separating read and write data models into distinct paths to maximize scalability, auditability, and throughput.
Clean ArchitectureMediatRHigh Throughput
FinOps & OptimizationFinOps
2 min read
LLM FinOps (AI Financial Operations)
The practice of tracking, attributing, optimizing, and governing AI model compute and token expenditures across multi-tenant applications.
Cost ControlUnit EconomicsToken Telemetry
FinOps & OptimizationSemCache
2 min read
Semantic Caching
Storing and retrieving AI generation results based on meaning similarity rather than exact string matching.
RedisVector SearchLatency Reduction
FinOps & OptimizationLLMLingua
3 min read
Prompt Compression & Context Pruning
Algorithmic compression of system prompts and retrieval context to strip redundant tokens while preserving key semantic entities and instruction fidelity.
Token SqueezingInformation DensityCost Savings
FinOps & OptimizationDMC
2 min read
Dynamic Model Cascading
An evaluation pipeline that attempts to satisfy queries using fast, low-cost models first, escalating to frontier models only when verification thresholds fail.
RouterModel TieringCost-Latency Pareto
Data & RetrievalV-RAG
3 min read
Vectorless RAG (Hybrid BM25 + Graph RAG)
A high-precision information retrieval architecture that combines lexical BM25 indexing and relational graph traversal without relying solely on dense vector embeddings.
BM25Lexical SearchHybrid Retrieval
Data & RetrievalGraphRAG
3 min read
GraphRAG & Knowledge Mesh
Retrieval Augmented Generation backed by structured knowledge graphs, connecting disparate concepts across multi-hop organizational hierarchies.
Knowledge GraphRelational ReasoningNeo4j
Governance & SecurityRLS
2 min read
PostgreSQL Row-Level Security (RLS)
Database-level security policies that guarantee tenant isolation by automatically filtering rows according to authenticated tenant session variables.
SecurityMulti-TenancyPostgreSQL
Governance & SecurityGEO
2 min read
Generative Engine Optimization (GEO / LLMO)
The discipline of structuring digital entity graphs and authority content so that AI search engines (ChatGPT, Perplexity, Gemini) cite your brand in answer synthesis.
ChatGPT SearchPerplexityEntity Graph
Governance & SecurityAgentOps
3 min read
AgentOps & Multi-Agent Observability
Full-lifecycle monitoring, trace visualization, latency attribution, and behavioral auditing for non-deterministic multi-agent systems.
TelemetryLangSmithOpenTelemetry
Governance & SecurityRAGAS
3 min read
RAGAS & Continuous Evaluation
Automated evaluation framework assessing RAG pipelines on Faithfulness, Answer Relevancy, Context Precision, and Context Recall.
FaithfulnessAnswer RelevanceCI/CD Evaluation
Governance & SecurityZDE
2 min read
Zero Data Egress Architecture
A strict network and architectural posture ensuring that zero customer data, PII, or PHI leaves the private customer VPC boundary during AI inference.
HIPAAAir-GappedPII Protection
Agentic AILevel: Foundational
Agentic AI(AG-AI)
AI systems capable of autonomous multi-step reasoning, goal formulation, tool execution, and self-correction without step-by-step human prompts.
Technical Anatomy & Implementation Mechanics:
Unlike traditional LLM chat interfaces that merely respond to single-turn prompts, Agentic AI systems maintain persistent state, break down complex business goals into deterministic sub-tasks, invoke external APIs or databases, observe execution outputs, and self-heal when errors occur.
SHIVAM ITCS Battle-Tested Delivery Record:
We build deterministic state-machine agent swarms using LangGraph and Semantic Kernel, enforcing strict guardrails to prevent infinite loops and hallucinations.
The Modernization Ecosystem // 3 Angles of Mastery
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.
Active View // You Are Here
TECHNICAL FOUNDATION
.NET 10 & Strangler Topology
Deep CLR architecture, YARP reverse proxy gateways, C# 13 microservices, and AI-assisted dependency extraction.
.NET 10 JIT Engine4.8x Speedup
YARP reverse proxy traffic strangulation
C# 13 CQRS & MediatR domain logic
Semantic Kernel LLM legacy augmentation
Currently Reading
ENGAGEMENT PODS
7 R's Modernization Service
Methodical 4-phase transformation delivery pods with guaranteed zero downtime and automated regression testing.
Shared Engineering Philosophy Across All 3 Pillars
Strangler Fig Pattern
No risky big-bang rewrites. We place YARP reverse proxy gateways in front of legacy monoliths and incrementally cut over microservices.
The 7 R's Framework
Retire, Retain, Rehost, Replatform, Refactor, Rearchitect, and Rebuild. We optimize for highest business ROI with lowest risk.
Zero Production Downtime
Dual-running synchronization and shadow traffic verify state consistency before switching live factory or financial transactions.
20+ Years Microsoft Heritage
Led by co-founders Ajay & Vijay Paliwal with continuous hands-on mastery from VB6/COM to modern containerized .NET 10 on Linux.
KNOWLEDGE BASE // FAQ
Enterprise AI Terminology & Architecture FAQ
Direct answers to architectural, technical, and operational questions.
7 Questions
Q01What core engineering domains does SHIVAM ITCS specialize in?
We specialize in four interconnected pillars: Autonomous Agentic AI Systems, Monolithic .NET to .NET 9/10 Cloud Modernization, High-Concurrency Multi-Tenant SaaS Architecture, and Hybrid Vectorless Knowledge Retrieval (RAG).
Q02How does your 18-year legacy experience benefit modern AI projects?
Q03How does Vectorless RAG reduce enterprise AI operating costs by up to 85%?
Q04Can SHIVAM ITCS modernize our legacy .NET applications without downtime?
Q05What is the typical engagement model for an enterprise software build?
Q06Where is SHIVAM ITCS located and how do you support global timezones?
Q07How do you ensure data security, HIPAA, and ISO 27001 compliance?
DIRECT FOUNDER ADVISORY
Need Architectural Guidance on These Technologies?
Schedule a 45-minute confidential architecture discovery session with co-founders Vijay & Ajay Paliwal to map your agentic roadmap, token economics, or legacy .NET modernization.
