Abacus.ai
The world's first end-to-end AI platform for automating MLOps, LLM development, and agentic workflows.
The unified AI platform for enterprise-grade generative and predictive machine learning workflows.
Vertex AI is Google Cloud's flagship unified machine learning platform, designed to orchestrate the entire ML lifecycle from data ingestion to model deployment. By 2026, Vertex AI has evolved into a central hub for 'Agentic AI,' integrating the Gemini 1.5 and 2.0 multimodal model families with enterprise-grade RAG (Retrieval-Augmented Generation) and grounding capabilities via Google Search. The architecture abstracts the underlying infrastructure, allowing developers to switch between pre-trained models in the Model Garden—which includes first-party Gemini models, open-weights models like Llama 4, and third-party models like Anthropic's Claude. Its technical core is built on Vertex AI Pipelines (based on Kubeflow), a managed Feature Store for high-performance embeddings, and an integrated Agent Builder that simplifies the creation of autonomous workflows. For enterprises, it offers a distinct advantage through its deep integration with BigQuery for 'Data-to-AI' workflows, enabling models to be trained directly on petabyte-scale data without egress. The 2026 market position emphasizes 'responsible AI' with built-in safety filters, data sovereignty controls, and high-performance TPU v5p/v6 infrastructure for specialized fine-tuning.
A curated repository of 150+ first-party, open-source, and third-party models (Llama, Claude, Mistral) optimized for GCP.
The world's first end-to-end AI platform for automating MLOps, LLM development, and agentic workflows.
Accelerate the path to production AI with a real-time MLOps orchestration platform.
The MLOps Operating System for Scalable, Infrastructure-Agnostic AI Development.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A high-level orchestration layer that combines LLMs with search engines and API extensions to create autonomous agents.
A high-scale, low-latency vector database service for similarity search on billions of embeddings.
A feature that connects LLM responses to real-time, world-knowledge data via Google Search indices.
Serverless orchestration for ML workflows using Kubeflow or TFX to automate model metadata tracking.
A managed repository to serve, share, and register ML features with point-in-time lookups.
Managed Jupyter notebooks with enterprise security, data governance, and VPC support.
Searching through thousands of hours of security or training footage for specific events without manual tagging.
Registry Updated:2/7/2026
Manually verifying damage from photos and matching them against policy documents is slow and error-prone.
Identifying fraudulent transactions in milliseconds to prevent financial loss.