# Yogreet Global > Infrastructure-first product engineering studio. Yogreet Global designs and builds AI-native applications on microservices, structured functions, and right-sized infrastructure from sprint one — built to scale from 100 to 100,000 users at a cost planned for in advance, instead of discovered after launch. Yogreet Global LLP is based in India and works with founders turning a startup idea into an enterprise-grade product. Core focus areas: microservices architecture, AI token and model cost engineering, right-sized cloud infrastructure, structured backend/API design, performance engineering, and scale roadmapping. ## Company - [Homepage](https://yogreet.com/): Services, approach, cost-optimization philosophy, and case studies. - [Services overview](https://yogreet.com/services/): Index of all six engineering disciplines with links to each. - [Pricing](https://yogreet.com/pricing/): How engagements are priced — a free build audit, project-based product builds, and a monthly scale & cost-engineering retainer. - [Free tools](https://yogreet.com/tools/): No-signup tools to estimate and reduce AI/infrastructure cost. - [Case studies](https://yogreet.com/case-studies/): Real builds — Calcounti (healthtech), Sosana (AI social), Callaquest (AI voice) — and the infrastructure decisions behind them. - [LLM / AI API cost calculator](https://yogreet.com/tools/llm-cost-calculator/): Estimate monthly AI API spend from tokens and volume, compare models (Claude, GPT-4o and others), and estimate savings from model routing and prompt caching. All prices editable. - [Microservices vs monolith decision tool](https://yogreet.com/tools/microservices-vs-monolith/): Answer 7 questions to get a weighted recommendation — monolith, modular monolith, or microservices — based on team size, stage, scaling needs, deployment independence, failure isolation, ops maturity and domain clarity. - [AI cost-per-user & margin calculator](https://yogreet.com/tools/ai-cost-per-user/): Work out AI cost per user, gross margin and whether an AI feature is profitable from per-user usage and pricing. - [Token count & cost estimator](https://yogreet.com/tools/token-cost-estimator/): Estimate token count for any text and the cost to run it across models, per call and per month. - [Cloud cost-to-scale estimator](https://yogreet.com/tools/cloud-cost-to-scale/): Estimate monthly infrastructure cost from users and usage and project it at 10x and 100x scale. - [Server capacity calculator](https://yogreet.com/tools/server-capacity-calculator/): How many server instances you need for a given peak RPS and latency, with utilization headroom (Little's Law). - [Concurrency & throughput calculator](https://yogreet.com/tools/concurrency-calculator/): Convert between requests per second, latency and concurrent in-flight requests using Little's Law. - [Database connection pool calculator](https://yogreet.com/tools/db-connection-pool-calculator/): Size a connection pool from peak load and query time; detect connection starvation and database limit exhaustion. - [Caching ROI calculator](https://yogreet.com/tools/caching-roi-calculator/): Estimate monthly cost and latency a cache would save on a hot path and whether it pays for itself. - [Uptime / SLA downtime calculator](https://yogreet.com/tools/uptime-sla-calculator/): Convert an availability target like 99.9% into allowed downtime per day/week/month/year and an error budget. - [Microservices readiness scorecard](https://yogreet.com/tools/microservices-readiness/): Score operational readiness for microservices (CI/CD, testing, observability, on-call, IaC) and list the gaps to close. - [Cost-of-a-rewrite estimator](https://yogreet.com/tools/rewrite-cost-estimator/): Estimate the true cost of a re-architecture — direct engineering plus opportunity cost. - [AI & LLM cost engineering](https://yogreet.com/services/ai-cost-engineering/): How Yogreet reduces LLM and AI inference costs with model routing, prompt caching, batching and fallback tiers — without cutting response quality. - [Microservices architecture consulting](https://yogreet.com/services/microservices-architecture/): Decoupled service design and pragmatic monolith-to-microservices migration for startups — built to scale to ~100,000 users without a re-platform. - [Cloud cost optimization & right-sized infrastructure](https://yogreet.com/services/cloud-cost-optimization/): Cloud sized to real load curves, autoscaling and pragmatic FinOps that cut cloud spend without risking reliability. - [Performance engineering](https://yogreet.com/services/performance-engineering/): Caching, indexing and load testing built in from day one so apps stay fast and stable under real load. - [Backend & API development](https://yogreet.com/services/backend-api-development/): Modular, testable backend functions and stable, well-designed APIs, structured to scale without a rewrite. - [Scale roadmapping](https://yogreet.com/services/scale-roadmapping/): A phased architecture plan from 100 to 100,000 users without a re-platform — what breaks next at each threshold, and what to build before it does. - [Book a build audit](https://yogreet.com/book-a-call): Pick a time and submit project details to start a build audit call. - Contact: hello@yogreet.com ## Services - Microservices architecture — decoupled services with clear boundaries so scaling one part never requires rebuilding the rest. Details: https://yogreet.com/services/microservices-architecture/ - AI token & model cost engineering — model routing, prompt caching, and fallback tiers that cut AI spend without cutting response quality. Details: https://yogreet.com/services/ai-cost-engineering/ - Right-sized infrastructure — cloud setups sized to real load curves, not over- or under-provisioned. Details: https://yogreet.com/services/cloud-cost-optimization/ - Structured function design — modular, testable backend functions and APIs. Details: https://yogreet.com/services/backend-api-development/ - Performance engineering — caching, indexing, and load-testing built in from day one. Details: https://yogreet.com/services/performance-engineering/ - Scale roadmapping — a phased architecture plan from 100 users to 100,000 without a re-platform. Details: https://yogreet.com/services/scale-roadmapping/ ## Case studies Real Yogreet builds and the infrastructure decisions behind them: - [Calcounti AI — healthtech](https://yogreet.com/case-studies/calcounti-ai): Meal-time traffic spikes were timing out the backend three times a day; splitting food-recognition behind a cache and autoscaling to the real curve cut LLM cost ~50% and reached 99.9% uptime. - [Sosana — AI social platform](https://yogreet.com/case-studies/sosana): Personalised feeds re-called the model on every refresh; caching and smart routing flattened cost-per-user while the audience kept growing (~40% lower server cost). - [Callaquest — AI voice & calling](https://yogreet.com/case-studies/callaquest): Real-time calls couldn't tolerate latency; right-sized infrastructure and a leaner inference path made it 3× faster with a <1% drop rate. - Full index: https://yogreet.com/case-studies/ ## Engineering journal (blog) Practical engineering guides: - [How to Reduce AI API & Token Costs: A Practical Guide](https://yogreet.com/blog/how-to-reduce-ai-api-costs): The four levers that move an AI bill most — prompt caching, model routing, batching and output discipline — ranked by impact, with quality trade-offs. - [Microservices vs Monolith for a Startup: How to Actually Decide](https://yogreet.com/blog/microservices-vs-monolith-startup): When a modular monolith wins, the three signals that justify splitting into microservices, and how to migrate incrementally without a rewrite. - [How Much Does It Cost to Scale an AI App?](https://yogreet.com/blog/cost-to-scale-ai-app): The real cost drivers (tokens, infrastructure, data), why per-user cost creeps up, and how to keep it flat from 100 to 100,000 users. - [Why Startups End Up Rewriting Their Architecture (and How to Avoid It)](https://yogreet.com/blog/why-startups-rewrite-architecture): The four causes of the expensive rewrite that hits when growth arrives — un-splittable database, tangled monolith, baked-in performance limits, usage-scaling cost — and how designing clean seams early avoids it. Five case studies on how real infrastructure decisions — made early, or made too late — shaped well-known software products: - [13 People, One Server, a Billion-Dollar App: The Instagram Engineering Story](https://yogreet.com/blog/instagram-engineering-journey): How a tiny team avoided a database rewrite by designing IDs and sharding to split cleanly before they ever needed to split. - [50 Engineers, 2 Billion Users: How WhatsApp Mastered Infrastructure Efficiency](https://yogreet.com/blog/whatsapp-infrastructure-efficiency): Why choosing Erlang, built for telecom switches, let a ~50-person team serve hundreds of millions of users. - [The Three-Day Outage That Rebuilt Netflix From the Ground Up](https://yogreet.com/blog/netflix-microservices-rebuild): How a 2008 database corruption triggered a seven-year migration from one data center to 1,000+ cloud microservices. - [The Game That Failed Twice — Then Became Slack](https://yogreet.com/blog/slack-from-failed-game-to-saas): How an internal chat tool built to support a failing game studio became the actual business. - [Seven Lines of Code: How Stripe Built Infrastructure-First From Day One](https://yogreet.com/blog/stripe-api-first-infrastructure): How treating payments as infrastructure, not a feature, meant the core API never needed a rewrite. Full index: https://yogreet.com/blog/ ## Daily engineering insights Yogreet publishes a specific, niche engineering insight every day at https://yogreet.com/blog/ . Recent posts: - [The Idle-Resource Audit: Uncovering Hidden Cloud Costs](https://yogreet.com/blog/the-idle-resource-audit-uncovering-hidden-cloud-costs): Learn to find and eliminate idle resources in your cloud infrastructure to cut costs by up to 30%. - [Autoscaling Cold Starts: Maintaining P99 Latency Without Idle Costs](https://yogreet.com/blog/autoscaling-cold-starts-maintaining-p99-latency-without-idle-costs): Learn how to tackle autoscaling cold starts to keep P99 latency flat while minimizing idle capacity costs. - [Right-Sizing Kubernetes Resource Requests Without Outages](https://yogreet.com/blog/right-sizing-kubernetes-resource-requests-without-outages-2): Learn how to right-size Kubernetes requests and limits effectively to prevent outages and optimize resource usage. - [Per-Service Data Ownership: The Key to Microservices Success](https://yogreet.com/blog/per-service-data-ownership-the-key-to-microservices-success): Explore why shared databases undermine microservices and how per-service data ownership enhances scalability and reliability. - [Avoiding the Distributed Monolith Trap in Microservices](https://yogreet.com/blog/avoiding-the-distributed-monolith-trap-in-microservices-2): Explore how microservices can inadvertently become tightly coupled and strategies to prevent the distributed monolith trap. - [Event-Driven vs Request/Response: Optimizing Microservice Boundaries](https://yogreet.com/blog/event-driven-vs-request-response-optimizing-microservice-boundaries): Explore when to choose event-driven vs request/response in microservices, optimizing costs and performance for your startup. - [Defining Service Boundaries: Business Capabilities vs Technical Layers](https://yogreet.com/blog/defining-service-boundaries-business-capabilities-vs-technical-layers): Explore effective strategies for defining service boundaries between business capabilities and technical layers in microservices architecture. - [Strangler-Fig Migration: Extracting Microservices Without Outages](https://yogreet.com/blog/strangler-fig-migration-extracting-microservices-without-outages): Learn how to extract your first microservice from a monolith using the strangler-fig pattern without causing outages. - [Streaming vs Batching LLM Responses: Cost and Latency Insights](https://yogreet.com/blog/streaming-vs-batching-llm-responses-cost-and-latency-insights): Explore the nuanced trade-offs of streaming vs batching LLM responses for startups, optimizing cost and latency effectively. - [Designing Graceful Degradation for LLM Rate Limits](https://yogreet.com/blog/designing-graceful-degradation-for-llm-rate-limits): Learn how to implement graceful degradation strategies for LLM rate limits, ensuring reliability and cost efficiency in your applications. ## Daily IT News (IT World Daily) Yogreet publishes a daily, sourced summary of global technology, software, AI and acquisition news at https://yogreet.com/news/ . Recent editions: - [August 11, 2026: OpenAI Expands Cybersecurity Model Amid Rising AI Attacks — IT News, August 11, 2026](https://yogreet.com/news/2026-08-11/) — OpenAI enhances its cybersecurity offerings with a new AI model to combat rising threats, relevant for builders focused on AI infrastructure. - [August 10, 2026: AI Safety Risks and Funding Trends Shape Infrastructure Landscape — IT News, August 10, 2026](https://yogreet.com/news/2026-08-10/) — Concerns over AI safety and significant funding in chip startups highlight the evolving landscape for scalable AI infrastructure. - [August 9, 2026: OpenAI Acquires NextSlide to Enhance ChatGPT Capabilities — IT News, August 9, 2026](https://yogreet.com/news/2026-08-09/) — OpenAI's acquisition of NextSlide aims to bolster ChatGPT's capabilities, impacting AI infrastructure and development. - [August 8, 2026: OpenAI Halts Astra Model Development Over Security Risks — IT News, August 8, 2026](https://yogreet.com/news/2026-08-08/) — OpenAI pauses Astra model development due to security concerns, impacting AI infrastructure for builders. - [August 7, 2026: AI Hardware Development Accelerates — IT News, August 7, 2026](https://yogreet.com/news/2026-08-07/) — Recent advancements in AI hardware and funding highlight critical trends for scalable software and infrastructure development. - [August 6, 2026: AI Coding Tools Evolve as Meta Launches Muse Code — IT News, August 6, 2026](https://yogreet.com/news/2026-08-06/) — Meta's Muse Code introduces advanced AI capabilities for software development, highlighting trends in AI coding tools and infrastructure scaling. - [August 5, 2026: AI Models Face Scrutiny Over Security and Behavior — IT News, August 5, 2026](https://yogreet.com/news/2026-08-05/) — Concerns rise over AI model safety and cybersecurity, impacting software builders focused on scalable solutions. - [August 4, 2026: Horizon3 Valuation Hits $2B Amid Rising AI Cybersecurity Threats — IT News, August 4, 2026](https://yogreet.com/news/2026-08-04/) — Horizon3's $250M funding highlights the growing demand for AI-driven cybersecurity solutions, crucial for building secure software infrastructure. - [August 3, 2026: AI Deployment Simplified with New Startup Funding — IT News, August 3, 2026](https://yogreet.com/news/2026-08-03/) — Startup June secures funding to simplify AI deployment, crucial for builders scaling AI products. - [August 2, 2026: Cyberattacks Target US Water Facilities — IT News, August 2, 2026](https://yogreet.com/news/2026-08-02/) — Cyberattacks on water facilities raise concerns for infrastructure security; builders must prioritize cybersecurity in software and AI products. - [August 1, 2026: AI Industry Calls for Caution Amid Model Misbehavior — IT News, August 1, 2026](https://yogreet.com/news/2026-08-01/) — AI leaders advocate for a more measured approach to development, emphasizing the importance of responsible scaling and infrastructure management. - [July 31, 2026: AI Security Breaches Prompt Urgent Industry Reactions — IT News, July 31, 2026](https://yogreet.com/news/2026-07-31/) — Security tests reveal AI models' vulnerabilities, highlighting the need for robust infrastructure in AI product development. - [July 30, 2026: Meta and Microsoft Expand AI Opportunities Amid Competitive Landscape — IT News, July 30, 2026](https://yogreet.com/news/2026-07-30/) — Meta and Microsoft are pushing AI innovations, impacting infrastructure and scaling for software builders. - [July 29, 2026: AI Security and Funding Trends Shape Software Development — IT News, July 29, 2026](https://yogreet.com/news/2026-07-29/) — Exploring AI security incidents and funding trends impacting software builders today.