Services

AI Engineering Services

We implement cutting-edge machine learning research for production systems. From foundation models to agentic systems, we build AI that works at scale.

Foundation Model Engineering

LLM Fine-tuning & Deployment

Custom fine-tuning of large language models using Constitutional AI, RLHF, and DPO. We implement parameter-efficient methods like LoRA and QLoRA for enterprise deployment.

Research Foundation

Constitutional AI (Anthropic '22) · DPO (Rafailov '23) · QLoRA (Dettmers '23)

Capabilities

  • Constitutional AI training
  • RLHF & DPO alignment
  • Mixture-of-experts architectures
  • LoRA/QLoRA fine-tuning
  • Multi-modal model integration
  • Model compression & optimization

Agentic AI Systems

Autonomous Reasoning & Tool Use

Build autonomous AI agents using ReAct, Tree-of-Thoughts, and self-reflection architectures. Multi-agent systems with advanced planning and memory.

Research Foundation

ReAct (Yao '22) · Tree-of-Thoughts (Yao '23) · Reflexion (Shinn '23)

Capabilities

  • ReAct agent framework
  • Tree-of-Thoughts planning
  • Multi-agent coordination
  • Tool-calling systems
  • Long-term memory integration
  • Self-reflection mechanisms

World Models & Simulation

Neural Digital Twins

Implement world models using diffusion transformers, neural ODEs, and physics-informed networks. Digital twins that understand causality and temporal dynamics.

Research Foundation

World Models (Ha '18) · Neural ODEs (Chen '18) · DiT (Peebles '23)

Capabilities

  • Neural world models
  • Physics-informed networks
  • Causal inference models
  • Temporal dynamics learning
  • Counterfactual reasoning
  • Real-time simulation

ML Infrastructure

Production ML Systems

End-to-end MLOps frameworks for training, deployment, and monitoring. Scalable pipelines with feature stores, vector databases, and real-time inference.

Research Foundation

Feature Store patterns · MLOps best practices · Continuous training systems

Capabilities

  • ML pipeline orchestration
  • Feature store design
  • Vector database integration
  • Real-time inference systems
  • Model versioning & registry
  • Automated retraining pipelines

AI Safety & Governance

Responsible AI Deployment

Enterprise AI governance using alignment research, interpretability techniques, and safety frameworks. Constitutional AI principles for responsible deployment.

Research Foundation

Interpretability (Olah '20) · AI Alignment (Christiano '17) · Constitutional AI

Capabilities

  • AI safety frameworks
  • Mechanistic interpretability
  • Bias detection & mitigation
  • Model auditing systems
  • Compliance automation
  • Risk assessment protocols

How We Work

A systematic approach from research to production

01

Discovery

We analyze your problem domain, existing systems, and business objectives to define clear success metrics and technical requirements.

02

Research

Our team surveys the latest research to identify the most promising approaches, running rapid experiments to validate feasibility.

03

Development

We build production-ready systems with clean APIs, comprehensive testing, and proper documentation for your team.

04

Deployment

We deploy to your infrastructure with monitoring, alerting, and optimization for real-world performance at scale.

Have a project in mind?

Let's discuss how our AI engineering expertise can help solve your most challenging technical problems.