The Modern AI Tech Stack (August 2025)

Author

Technology Illumination
July 09, 2025

Presentation Layer (UI/UX for AI)

  • Chat & Agentic UIs: ChatGPT-style interfaces, RAG-driven dashboards.

  • Frameworks: React, Next.js, Flutter, Swift, Kotlin.

  • AI UI Tools: Vercel AI SDK, Streamlit, Gradio, Retool.

Edge & Delivery (Optional)

  • AI Edge Deployment: NVIDIA Triton Inference Server, TensorRT, ONNX Runtime.

  • AI CDN / Delivery: Cloudflare Workers AI, Fastly Compute@Edge, Akamai Edge AI.

Integration Layer (API & AI Protocols)

  • AI APIs: OpenAI API, Anthropic Claude API, Google Gemini API, AWS Bedrock, Azure OpenAI.

  • Agent Protocols: Model Context Protocol (MCP), LangGraph (GA May 2025).

  • Frameworks: LangChain, Semantic Kernel, Haystack.

Messaging & Async Processing (Optional)

  • AI Event-Driven: Kafka, Pulsar, Redis Streams.

  • Workflow Orchestration: Airflow, Prefect, Temporal, Dagster.

  • Agent-Oriented Queues: AgentOps, Celery (AI job pipelines).

Business Logic Layer (AI Applications & Agents)

  • Agent Frameworks: LangChain, AutoGen, CrewAI, Microsoft Semantic Kernel.

  • LLM App Backends: Spring Boot (for enterprise), FastAPI, Django.

  • Specialized AI Apps: Pinecone hybrid search + embeddings, RAG pipelines.

Data Access Layer

  • Feature Stores: Feast, Tecton.

  • Vector Databases: Pinecone, Weaviate, Milvus, pgvector (Postgres extension).

  • ETL for AI: dbt, Nomic, Gable.

Data Storage Layer

  • Traditional: PostgreSQL, MySQL, MongoDB, Snowflake.

  • Vector & Hybrid: Pinecone, Milvus, Vespa, Redis w/ vector search.

  • Lakehouse: Databricks Delta Lake, BigQuery.

Analytics & ML (Core AI/ML Layer)

  • Model Frameworks: PyTorch, TensorFlow, JAX.

  • Fine-Tuning / PEFT: LoRA, Adapters, QLoRA.

  • Evaluation & Observability: LangSmith, Humanloop, TruLens.

  • Data Science: Spark MLlib, Databricks MLflow.

  • Visualization: Looker, PowerBI + AI Copilot.

Infrastructure Layer (Hosting / Runtime)

  • Cloud AI Platforms: AWS Bedrock, Azure AI Studio, Google Vertex AI, IBM Watsonx.

  • Containerization & Orchestration: Docker, Kubernetes, Ray Serve.

  • Hardware & Acceleration: NVIDIA GPUs (H100, B200), AMD ROCm, Intel Gaudi3, Oxmiq Labs RISC-V GPU stack, MLIR + oneAPI.

  • Serverless AI Compute: Modal, RunPod, Lambda w/ GPU, Together.ai.

Key Shifts in 2025 vs. 2023–2024

  1. Agent-Centric Design: Shift from just LLM APIs to multi-agent orchestration (LangGraph, MCP).

  2. Vector-Native Systems: Vector DBs are now core infrastructure.

  3. Hardware Abstraction: CUDA lock-in is being challenged (Oxmiq RISC-V, oneAPI, MLIR).

  4. Governance Built-In: Platforms like Watsonx.governance & LangSmith provide compliance, evaluation, and observability.

  5. “Burn the Boats” Mentality: Teams adopt new tools aggressively to stay at the AI frontier.

This AI stack mirrors the layered approach in your Modern Software Stack diagram, but updated for agentic AI, LLMs, RAG, and hardware abstraction realities of 2025