Why this list exists
In my AI ROI research, I covered 7 directions with the highest returns. But a common follow-up question is: "Is there a case study in my specific industry?"
The problem: vendor case libraries (OpenAI, AWS, Google) are marketing materials. Vague objectives, zero technical details, vendor glorification.
Below are resources where you can find specific cases with implementation details, architecture, and metrics.
Generative AI & LLM
Evidently AI — 800 ML & LLM cases
evidentlyai.com/ml-system-design →The most convenient aggregator. 800 cases from 150+ companies with filtering by industry, task, and technology. Each case links to the original blog post or company article. Covers not only generative AI but also classical ML: recommendations, fraud detection, search & ranking. The best starting point.
GenAI & LLM System Design — 500+ cases with architecture
github.com/themanojdesai/genai-llm-ml-case-studies →An expanded library on GitHub built on top of Evidently AI. Focus on technical details: system architecture, model selection, infrastructure, production metrics. 500+ cases from 100+ companies. An indispensable resource for CTOs and tech leads designing AI systems.
ZenML LLMOps Database — 800+ cases
zenml.io/llmops-database →Built by ZenML, an MLOps platform. The largest database by record count. Convenient filtering by company, industry, and task type. Well-suited for finding cases in a specific niche.
LangChain Case Studies — high-quality cases
langchain.com/case-studies →Small but one of the highest-quality libraries. Yes, it's vendor-specific (LangChain), but cases are written with technical details, honest metrics, and architecture descriptions. If you're using or considering LangChain — essential reading.
Classical ML: recommendations, CV, NLP, fraud
ML Practical Use Cases — 650 cases
github.com/mallahyari/ml-practical-usecases →650 cases from 100+ companies across the full ML spectrum: computer vision, NLP, recommendation systems, fraud detection, search & ranking. Each case links to the original blog or article. Organized by industry and task type.
ML System Design Case Studies — 300+ cases
github.com/Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies →300+ cases from 80+ companies focused on ML system design. How Netflix builds recommendations, how Uber optimizes routes, how Spotify personalizes playlists. An excellent resource for understanding production ML system architecture.
AIMultiple — 100+ use cases with examples
aimultiple.com/ai-usecases →A catalog of 100+ AI application directions with real company examples. Convenient navigation by industry: finance, healthcare, retail, manufacturing. Also has separate sections for NLP (30+ use cases) and Deep Learning (50 use cases).
DigitalDefynd — 60 detailed AI case studies
digitaldefynd.com/IQ/artificial-intelligence-case-studies →60 in-depth breakdowns of how specific companies (JPMorgan, DHL, Spotify, Netflix) implemented AI. Each case is a full article with context, solution, and results. Great for studying best practices from market leaders.
Research and consulting reports
McKinsey — The State of AI
mckinsey.com → The State of AI →Annual global survey: adoption trends, ROI, barriers. 400+ generative AI build-outs across sectors. Free access.
Deloitte — State of AI in the Enterprise
deloitte.com → State of AI →Detailed report with data on ROI, budgets, and AI maturity in large companies. Focus on enterprise deployments.
World Economic Forum — 32 cases with business impact
WEF MINDS Initiative →32 selected cases that have passed the experimental phase and demonstrated measurable results at scale. High quality threshold.
Filtered — Top 100 GenAI Use Cases
filtered.com → Top 100 GenAI Use Cases →100 most popular generative AI use cases ranked by frequency of application. Regularly updated.
Code and prototypes
Awesome LLM Apps — open source examples
github.com/Shubhamsaboo/awesome-llm-apps →A collection of LLM applications with open-source code. RAG systems, chatbots, agents, pipelines. Useful for rapid prototyping: take ready-made code and adapt it to your task.
Deloitte AI Dossier — business ideas
deloitte.com → GenAI Use Cases →A structured list of generative AI application ideas by industry and function. Not case studies, but rather an opportunity map. Useful during brainstorming: where can AI be applied in your business.
Russian resources
Yandex Cloud — cases with implementation details
yandex.cloud/ru/cases →One of the best Russian libraries. Includes architecture details, stack descriptions, and results. Covers not just YandexGPT — also ML, data platforms, and infrastructure solutions. Downside — no AI/ML filter, manual search required.
Generation AI (JustAI) — conversational AI
generation-ai.ru/cases →A quality, compact library from JustAI. Focus on conversational AI: chatbots, voice assistants, communication automation. Good business problem and results descriptions. Ideal for those considering bot deployment in support or sales.
GigaChat Cases (Sber)
developers.sber.ru/portal/cases →Cases for GigaChat and the Sber ecosystem. The library is still small and mostly marketing-oriented — few technical details and specific metrics. But growing.
Yakov & Partners — Russian AI market analytics
yakovpartners.ru → AI 2025 →An analytical report on the state of AI in the Russian economy. Not case studies, but macro data: potential of 13 trillion rubles by 2030, adoption barriers, industry trends. Useful for strategic planning.
Computerra — Russian corporate AI reviews
computerra.ru → Corporate AI →Journalistic reviews of notable AI implementations in Russian companies: Sber, Yandex, Tinkoff, X5, and others. Not a technical library, but a good landscape overview.
How to use these resources
- Define the task — not "implement AI", but "automate incoming request processing" or "reduce support response time"
- Find analogues — start with Evidently AI or ZenML, find cases from similarly-sized companies in your industry
- Study the architecture — for your technical team: GenAI System Design on GitHub shows how production systems are built
- Calculate ROI — use our ROI calculation framework and benchmarks from discovered cases
- For the Russian market — Yandex Cloud + Generation AI + Yakov & Partners report provide local context
These resources will help you move from "we want AI" to "here's how company X solved problem Y and achieved result Z" — with specific numbers and architecture.