AI That Actually Works
In Production.
We don't build AI demos. We build AI products that operate in regulated industries, handle real data at scale, and deliver measurable business outcomes. The difference is architecture, testing, and 30+ years of knowing what production actually requires.
Discuss Your AI ProjectWhat We Build
AI capabilities built for production environments — not hackathon demos.
LLM Integration & Agentic Workflows
Claude, GPT-4, and open-source LLMs integrated into your product as reliable, production-grade components. Multi-agent systems that orchestrate complex tasks with appropriate guardrails.
- ✓Claude / OpenAI / open-source model integration
- ✓Tool-use and function calling pipelines
- ✓Multi-agent orchestration (CrewAI, custom)
- ✓Structured output and prompt engineering
RAG & Knowledge Systems
Retrieval-augmented generation systems that give LLMs accurate, up-to-date knowledge from your proprietary data. Semantic search, vector databases, and document processing pipelines.
- ✓Vector database design (Pinecone, pgvector, Weaviate)
- ✓Document ingestion and chunking pipelines
- ✓Hybrid semantic + keyword search
- ✓Citation and source attribution
Custom ML Models & Pipelines
Bespoke machine learning models for your specific domain — from GPU-accelerated genomics pipelines to fraud detection to clinical decision support. We train, validate, and deploy.
- ✓Model training and evaluation
- ✓GPU-accelerated compute pipelines
- ✓MLOps and model monitoring
- ✓Model risk management (SR 11-7)
AI in Regulated Industries
AI deployment in healthcare, fintech, and other regulated sectors requires explainability, audit trails, and compliance frameworks. We build AI that meets these requirements by design.
- ✓Explainable AI (SHAP, LIME)
- ✓Immutable audit logging for AI decisions
- ✓Bias monitoring and fairness testing
- ✓FDA SaMD AI/ML compliance readiness
AI That Survives Production
Many "AI integrations" are thin API wrappers. We architect AI features as production components — with fallbacks, monitoring, cost controls, and graceful degradation when models fail.
The right model architecture depends on your use case. We choose between fine-tuning, RAG, prompt engineering, and custom ML based on your data, latency, and compliance requirements.
AI in healthcare, finance, and other regulated sectors faces specific requirements that pure AI companies don't know about. Our background means we build AI with the audit trails and explainability compliance demands.
Ready to Ship 3x Faster?
Share your vision on a 30-minute call. Get a detailed proposal within 24 hours. Start building within 48 hours.