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Deep technical content on agentic AI systems, LLM cost optimization, Commander Architecture, and production SaaS engineering — from 18+ years of building.
Intelligent APIs with AI Assistants
The emergence of Large Language Models (LLMs) and AI assistants has transformed APIs from simple request-response interfaces into intelligent service layers capable of understanding natural language, reasoning over enterprise data, and orchestrating complex workflows. This article explores the architectural patterns, opportunities, and challenges of building AI-powered APIs from the perspective of June 2023.
GraphQL Schema Definition Language: Standardizing APIs with Static Types
The GraphQL Schema Definition Language (SDL) provides a standardized, human-readable approach to defining GraphQL APIs using explicit types, queries, mutations, and relationships. This article examines SDL architecture, schema-first API design, type systems, tooling, and enterprise adoption considerations from the perspective of April 2017.
GraphQL Open Source Release: Replacing REST with Single-Endpoint Queries
Facebook has open sourced GraphQL, introducing a query language and runtime designed to simplify API development by allowing clients to request exactly the data they require through a single endpoint. Rather than exposing numerous REST resources, GraphQL offers a typed schema and client-driven queries that promise greater flexibility for web and mobile applications. This article examines GraphQL from the perspective of April 2015, exploring its architecture, enterprise use cases, performance characteristics, and adoption considerations.
Designing RESTful APIs: Standardizing JSON Status Codes, Hypermedia, and CORS
As RESTful APIs become the foundation of modern web and mobile applications, consistent API design is increasingly important. This article explores REST architecture, JSON response standards, HTTP status codes, hypermedia, and CORS from the perspective of mid-2013, providing practical guidance for enterprise architects and API developers.
Designing Scalable HTTP APIs: Early Architectures with WCF Web API
As HTTP-based services gain momentum beyond traditional SOAP web services, Microsoft's WCF Web API preview introduces a new programming model for building resource-oriented APIs. Learn how enterprise architects can evaluate its architecture, scalability considerations, and adoption strategies in late 2010.
Frequently Asked Questions.
Get all your answers here and if something remains, feel free to contact us directly or book a strategy session.
We design and build agent-native custom software architectures from day one. Instead of simply building bolt-on API wrappers, we deploy multi-agent orchestration systems (like our Commander Architecture), run local secure LLMs to slash token expenses by 40–70%, and modernize legacy Microsoft ecosystem codebases to modern AI-native structures.
It is our proprietary 5-agent pipeline framework. High-tier cloud models (like Claude Opus) act as 'Supreme Commanders' to analyze complexity and structure task files, which are then processed at high concurrency by local models (like Qwen on Ollama) at around $0.001 per task, drastically lowering API costs.
By integrating custom prompt caching strategies and context-aware semantic routing, we achieve a prompt cache hit rate of ~90%. This bypasses redundant processing of duplicate context instructions to dramatically slash monthly token bills.
We specialize in modern high-performance tech stacks: Next.js/React, Drizzle ORM, SQLite/PostgreSQL databases, .NET Core 8 cloud services, React Native/Expo for mobile apps, and cognitive frameworks such as Semantic Kernel, FastAPI, and Neo4j Knowledge Graphs.
We implement secure architectures by deploying local LLMs inside your virtual private cloud (VPC), ensuring sensitive data never leaves your environment. We also establish strict end-to-end data encryption, audit trails, and role-based access control.
Yes, we specialize in converting legacy systems (WinForms, WPF, ASP.NET WebForms) to modern, distributed systems built on modern .NET 8, micro-frontend architectures, and containerized Docker services running in AWS/Azure.
A typical proof of concept (PoC) takes 2 to 4 weeks. Full enterprise agent orchestration systems or multi-agent swarms integrated with your legacy APIs take about 8 to 12 weeks to build, test, and deploy to production.
Absolutely. We build React Native applications using local SQLite databases (via Drizzle or WatermelonDB) that can perform complex tasks offline and sync changes securely with the cloud server once internet connectivity is restored.
Speculative decoding uses a small, fast model to suggest draft tokens, which are verified in parallel by a larger target model. This speeds up text generation by 2x to 3x and cuts down latency without losing output quality.
Yes. All custom code, agent system designs, proprietary database configurations, and custom integration scripts developed during our engagement are 100% owned by your company from day one.
Client Impact & Success
"SHIVAM ITCS completely transformed our content workflow. Their Commander Architecture cut our monthly LLM cost by 65% while keeping quality pristine."
Partner with SHIVAM ITCS to build resilient, scalable systems. Our senior engineering teams specialize in enterprise AI orchestration, legacy modernization, and high-performance cloud architecture.
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