The AI stack we use — and why.
We work across every layer of the modern AI stack. We pick tools to fit your constraints, not ours. Here's what we actually ship with.
Model Providers
GPT-4.1, GPT-4o, o-series reasoning, embeddings, realtime.
Claude Opus, Sonnet, Haiku for reasoning, coding, and tool use.
Managed access to Claude, Llama, Titan, and custom models in VPC.
Enterprise OpenAI with private networking and data residency.
Gemini, Claude, and Model Garden with GCP-native IAM.
Command, Embed, and Rerank for retrieval-heavy workloads.
Domain-tuned embeddings and rerankers.
Orchestration
Composable chains, tool wiring, and provider-agnostic glue.
Stateful, cyclic graph orchestration for agents and workflows.
Data framework for ingestion, indexing, and retrieval.
Durable, long-running workflows for agent execution.
Serverless orchestration for AI pipelines and agents.
Stateful serverless workflows on Azure.
Vector & Retrieval
Managed vector database with hybrid search.
Open-source vector DB with modular retrievers.
Vector search inside Postgres you already run.
Hybrid BM25 + vector search on AWS.
High-performance vector DB with filtering.
Agent Frameworks
Native tool calling on Anthropic models.
Structured function and tool calling.
Multi-agent collaboration patterns.
Conversational multi-agent framework.
MCP
Build MCP servers and clients in Node.
Build MCP servers and clients in Python.
Reference MCP client for local and remote servers.
Developer IDE with first-class MCP server support.
Evaluation & Observability
Open-source LLM observability, evals, and prompt management.
Tracing, evaluation, and monitoring from LangChain.
Experiment tracking, model registry, and GenAI evaluation.
Open-source tracing and eval for LLM apps.
Experiment tracking and eval dashboards.
Cloud Platforms
Bedrock, SageMaker, Lambda, ECS, Step Functions, OpenSearch.
Azure OpenAI, AI Foundry, AKS, Functions, Cosmos, AI Search.
Vertex AI, Cloud Run, GKE, BigQuery, Model Garden.
Workers AI, Vectorize, and edge inference.
Data & Ingestion
Document parsing across PDF, HTML, email, and more.
Layout-aware parsing tuned for RAG.
OCR and form extraction for scanned documents.
Layout, form, and table extraction at scale.
Analytics engineering for the warehouse behind your AI.
How we pick.
Bedrock on AWS, Azure OpenAI on Azure, Vertex on GCP. Private networking and IAM you already trust.
If your team runs Postgres, pgvector beats standing up a new DB. We default to what you already operate.
Final call goes to the numbers. We A/B models, rerankers, and chunking on your data, not vendor demos.
Ready to accelerate your tech growth?
Schedule your free consultation today and let's discuss how we can help your business scale efficiently.
