End-to-end AI delivery.No orphaned proofs of concept.
Most machine-learning work never reaches production industry surveys put the figure near 87%. This practice is built around the part that decides it: data readiness, deployment, monitoring and governance solid enough to survive the handover.
- 6
- Practice areas
- 5
- Phase delivery
- On-prem
- Or cloud, your call
- Audited
- Built for scrutiny
Capabilities
Six practice areas, one delivery standard
Each of these has shipped into production systems, not just into a slide.
Large Language Models
Custom LLM work from local Ollama deployments to frontier APIs. Document analysis, natural-language querying of internal data, and conversational interfaces layered onto systems you already run.
Technology
The stack we build on
Tools in daily use, plus the ones we bring in when a problem calls for them. Knowing which to reach for is the actual work.
Languages & core
- Python
- SQL
- R
- C++
- TypeScript
ML & deep learning
- PyTorch
- TensorFlow
- Keras
- scikit-learn
- XGBoost
- LightGBM
- ONNX
LLM & generative AI
- OpenAI
- Anthropic Claude
- Google Gemini
- Mistral
- Llama
- Ollama
- Hugging Face
- LangChain
- LlamaIndex
- vLLM
Retrieval & vector
- pgvector
- Qdrant
- Milvus
- FAISS
- Elasticsearch
- Weaviate
Speech & vision
- Whisper
- Deepgram
- ElevenLabs
- OpenCV
- Tesseract OCR
- YOLO
Data & streaming
- Snowflake
- Databricks
- PostgreSQL
- Spark
- Kafka
- Airflow
- dbt
- DuckDB
- Polars
- pandas
Cloud & compute
- AWS
- Azure
- GCP
- NVIDIA CUDA
- Docker
- Kubernetes
- Terraform
MLOps & observability
- MLflow
- Weights & Biases
- FastAPI
- GitHub Actions
- Prometheus
- Grafana
- Evidently
Model providers are interchangeable by design every integration sits behind an abstraction so a change of vendor is a config change, not a rewrite.
See it in action
Integration you can try before you buy.
Two running examples of the pipelines we wire into production stacks.
A thirty-minute readiness assessment, no deck required.
We look at your data, name the highest-value opportunities, and come back with an implementation route. If AI isn't the answer yet, we'll say so — our open-source work is there if you'd rather judge the engineering first.