1. Foundation Models & Inference
GPT-4o / OpenAI
The industry standard endpoint utilized for high-reasoning tasks, deep-logic parsing, and highly conversational multi-modal frontends when data privacy constraints allow standard APIs.
Llama-3 Architecture
Meta's flagship open-weights models. We deploy heavily quantized or dense iterations on AWS GovCloud or private VPCs to ensure 100% sovereign data integrity for financial/legal clients.
vLLM / HuggingFace
High-throughput and memory-efficient LLM serving engines. Using PagedAttention algorithms, we host your local models allowing massive concurrent requests without crashing the GPU buffers.
2. Orchestration & Graph Workflows
LangChain / LangGraph
The backbone of our agentic execution. We code stateful, cyclical, multi-actor applications in Python that permit AI models to halt, rethink, search tools, and resume logically.
CrewAI / AutoGen
Used to simulate entire departments. We create specific AI personas (Analyst, Reviewer, Manager) that debate outputs and cross-verify code natively without human instruction.
Playwright / Selenium
Headless browser automation. We bind an LLM's logic natively to DOM elements, allowing bots to "see" your browser and execute human-like data entry on legacy CRM platforms.
3. Data Lakes & Vector Stores
Pinecone / Qdrant
Ultra-low latency vector databases. We translate your millions of proprietary PDFs and documents into mathematical embeddings, enabling the LLM to search vast enterprise archives in milliseconds.
PostgreSQL (pgvector)
When strict internal DB policies apply, we engineer your existing relational database to understand vector embeddings securely without adding external cloud vector dependencies.