Architect, Fine-Tune, and Deploy Frontier Transformer Models Across the AI Spectrum.
Enterprise text representation, sequence-to-sequence transformation, and generative LLM agentic pipelines engineered with BERT (Encoder), T5/FLAN-T5 (Encoder-Decoder), and LLaMA 3 / LLaMA 4 (Decoder) open-weight foundations.
Why Foundation Models for AI/ML & Data
choose precise transformer topographies: Encoders (BERT) for dense classification, Encoder-Decoders (T5) for sequence mapping, and Decoders (LLaMA) for generative reasoning
route tasks to lightweight 100M–3B parameter models (BERT/T5) for CPU-bound microservices or scale up to multi-billion parameter LLaMA models for complex agentic workflows
deploy state-of-the-art open weights in private VPCs or on-premises to guarantee total IP ownership, zero external vendor lock-in, and strict data privacy
adapt foundational capabilities to proprietary domain data using LoRA, QLoRA, adapter layers, and supervised fine-tuning (SFT) with minimal compute overhead
What We Build With
Foundation Models
Search & Intent Encoders
sub-millisecond semantic search, cross-encoder reranking, and domain-specific Named Entity Recognition (NER) systems
Structured Data Pipelines
Enterprise Generative Agents
On-Device Edge Intelligence
Custom Foundation Models
Transformer Architecture Expertise at StackDot
Where These Models Fit Best
Active Industry
LLaMA: Generative RAG, Chat & Agentic Automation
Why StackDot for Foundation Model Engineering
Architectural Mastery Across the Transformer Spectrum
selecting the exact right tool for the job to avoid over-provisioning LLMs for simple classification or token extraction tasks
Proactive GPU Compute & Token FinOps
cutting cloud AI infrastructure costs through aggressive model quantization, speculative decoding, and lightweight model routing
Airtight Enterprise Security & IP Ownership
deploying self-hosted open models within isolated security boundaries to prevent data leakage and guarantee regulatory compliance
Seamless AI Ecosystem Sync
integrating BERT, T5, and LLaMA models directly into enterprise vector stores (Pinecone, Qdrant, Weaviate), data pipelines, and orchestration platforms
Ready to Architect Your Enterprise AI Stack With Open Foundation Models?
Enterprise text representation, sequence-to-sequence transformation, and generative LLM agentic pipelines engineered with BERT (Encoder), T5/FLAN-T5 (Encoder-Decoder), and LLaMA 3 / LLaMA 4 (Decoder) open-weight foundations.