Supported AI & GenAI Technologies
Our Insights hub demonstrates deep expertise across AI technologies, industry applications, and emerging trends. We share knowledge generously because educated clients make better partners, and advancing the entire AI ecosystem benefits everyone.
A unified AI platform should offer building blocks for crafting bespoke solutions. CognitiveClouds supports a wide array of AI technologies, enabling us to deliver comprehensive and tailored innovations.
Generative AI Technologies
Cutting-edge generative models and frameworks powering the next generation of AI applications
Large Language Models (LLMs)
Foundation models that generate text, code, and other content, forming the basis for many applications
Generative Models (Vision, Audio, Multimodal)
Tools to create images, videos or audio, enabling creative and design workflows
Agentic AI
Autonomous agents with memory and decision-making abilities that can plan, act and learn across complex tasks
Retrieval-Augmented Generation (RAG)
Combines language models with external knowledge bases; LLMs retrieve relevant documents and incorporate them into responses, reducing hallucination and allowing use of updated or domain-specific data
Memory Architectures
Short-term memory to manage conversational context and long-term memory to store persistent knowledge, enabling personalization and context-aware reasoning
Reinforcement Learning from Human Feedback (RLHF)
Models learn from human-provided rewards or comparisons, aligning outputs with human preferences and ethical guidelines
Traditional AI & Supporting Technologies
Proven AI capabilities and infrastructure that form the foundation of intelligent systems
Knowledge Graphs & Ontologies
Structured representations of entities and relationships to enrich reasoning and enable semantic search
Responsible AI Tooling
Fairness, transparency and explainability frameworks to ensure ethical AI outcomes
Vector Databases & Semantic Search
Index and retrieve embeddings for similarity search and contextual awareness, powering RAG and other retrieval tasks
Model Orchestration & Agent Frameworks
Tools for chaining models, managing prompts, and coordinating multi-agent systems
Machine Learning & Deep Learning
Traditional supervised, unsupervised, and reinforcement learning approaches
Computer Vision
Image recognition, object detection, and visual analysis capabilities
Natural Language Processing
Text analysis, sentiment analysis, and language understanding
Predictive Analytics
Statistical modeling and forecasting for business intelligence
These diverse building blocks allow CognitiveClouds to compose tailored solutions that address the unique challenges and opportunities across various industries.
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