Large Language Models (LLMs)
We work with a variety of Large Language Models, which are the core of many modern AI applications. These models are trained on vast amounts of text and multimodal data to understand and generate human-like language, enabling capabilities such as content creation, summarization, question answering, and complex reasoning.
Vector Embeddings & Databases
Vector embeddings transform complex data (text, images, audio) into numerical representations (vectors) that capture semantic meaning. This allows for powerful similarity searches, recommendations, and clustering use cases.
- Core Concept: Representation of data in a high-dimensional space where proximity indicates similarity.
- Vector Databases: Specialized databases designed to efficiently store, manage, and query these vector embeddings at scale.
- ChromaDB
- LanceDB
- Other popular vector dbs (e.g., Pinecone, Weaviate, Milvus)
Multimodal AI & Embeddings
Moving beyond textual data, multimodal AI processes and relates information from various sources like text, images, and audio simultaneously. We utilize advanced models for creating rich multimodal vector embeddings.
- Google's
multimodalembedding
Model: Expertise in using models like Google'smultimodalembedding
on Vertex AI to generate embeddings that understand and link data across different modalities.
AI Agents & Autonomous Systems
We build sophisticated AI agents capable of autonomous reasoning, planning, and tool usage to accomplish complex tasks. This involves orchestrating LLMs with other tools and data sources.
- LangChain: A framework for developing applications powered by language models, enabling complex agentic workflows.
- Microsoft Autogen: A framework for simplifying the orchestration, optimization, and automation of LLM workflows, supporting the creation of conversational agents.
Local & Open Source AI Tools
For development, experimentation, and privacy-focused deployments, we leverage a range of local AI tools:
- OpenWebUI: A user-friendly web interface for local and external LLMs.
- LMStudio: Discover, download, and run local LLMs.
- Ollama: Run LLMs like Llama 3.2, Deepseek-R1, and others locally.
- Hugging Face: A vast repository of models, datasets, and tools for NLP and machine learning.
Cloud AI Platforms & APIs
We utilize leading cloud AI platforms for scalable, production-grade AI solutions:
- Google Gemini & Vertex AI: Access to Google's powerful foundation models and MLOps platform.
- OpenAI API: Programmatic access to models like GPT-4, GPT-3.5-turbo, and embedding models.
- Nvidia NIM: NVIDIA Inference Microservices for optimizing and deploying AI models at scale.
- Claude: A foundation model by Anthropic