Engineering

Advanced AI engineering

For teams that need more than automation — fine-tuned models, production ML pipelines, RAG systems, and custom AI infrastructure built to your specifications.

LLM Fine-Tuning & Custom Models

Off-the-shelf models get you 80% of the way. Fine-tuning closes the gap. We train and deploy custom language models on your domain data — whether that's legal documents, medical intake forms, or financial reports — so the model speaks your industry's language with the accuracy your workflows require.

  • Supervised fine-tuning on domain-specific datasets
  • LoRA and QLoRA for parameter-efficient training
  • Evaluation frameworks with domain-specific benchmarks
  • Model distillation for cost-efficient inference
  • Hosted or on-premise deployment options
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RAG Systems & Knowledge Pipelines

Retrieval-Augmented Generation is how you make LLMs useful with your data without retraining. We build production RAG pipelines — from document ingestion and chunking strategies to vector search and response generation — with the retrieval quality that determines whether the system is trustworthy or not.

  • Document ingestion pipelines (PDF, HTML, email, databases)
  • Chunking strategies optimized for retrieval accuracy
  • Vector database selection and tuning (Pinecone, Weaviate, pgvector)
  • Hybrid search combining semantic and keyword retrieval
  • Citation and source attribution in generated responses
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ML Pipeline Engineering

Machine learning in production is an engineering problem, not a notebook problem. We build end-to-end ML pipelines — data ingestion, feature engineering, model training, evaluation, and deployment — designed for reliability, reproducibility, and continuous improvement.

  • Feature stores and feature engineering pipelines
  • Automated training and retraining workflows
  • Model versioning and experiment tracking
  • A/B testing and shadow deployment infrastructure
  • Drift detection and monitoring in production
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Computer Vision & Document Intelligence

When the data is images, scans, or video, we build the systems that extract structure from it. OCR pipelines for document processing, object detection for inspection workflows, image classification for quality control — applied vision systems built for your specific use case.

  • Document OCR and intelligent data extraction
  • Object detection and image classification
  • Custom model training on your visual data
  • Video analysis and frame-level processing
  • Integration with existing document management systems
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Applied AI & Predictive Systems

Recommendation engines, churn prediction, demand forecasting, customer segmentation — the data science capabilities that used to require a dedicated team and months of development. Modern AI tooling makes these systems faster to build, easier to maintain, and accessible to businesses that never had the budget for a data science department.

  • Recommendation engines for products, content, or services
  • Churn prediction and retention scoring models
  • Demand forecasting and inventory optimization
  • Customer segmentation and lifetime value modeling
  • Anomaly detection for fraud, quality control, or operations
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AI Agent Architecture

Beyond simple chatbots. We build multi-step AI agents that reason, use tools, and take actions across your systems — handling complex workflows that require planning, error recovery, and human-in-the-loop checkpoints. Built for reliability in production, not just impressive in demos.

  • Multi-tool agent frameworks with structured reasoning
  • Tool integration (APIs, databases, file systems, browsers)
  • Conversation memory and long-term context management
  • Guardrails, validation, and fallback strategies
  • Observability and trace logging for debugging agent behavior
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Technology

Stack we work with

Models

OpenAI, Anthropic, open-source (Llama, Mistral), custom fine-tuned

Orchestration

LangChain, LlamaIndex, custom agent frameworks

Vector & Search

Pinecone, Weaviate, pgvector, Elasticsearch

Infrastructure

AWS, GCP, Docker, Kubernetes, Terraform

MLOps

Weights & Biases, MLflow, custom evaluation pipelines

Have a technical challenge?

We work with engineering teams on problems that require more than off-the-shelf solutions. Let's talk architecture.

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