AI systems with ML, vision, NLP and LLMs
End-to-end delivery, from the first model to a monitored production system. Automate workflows, extract insight, stay compliant.
What we deliver
AI, ML and MLOps
Predictive and prescriptive AI systems that deliver business value across the full lifecycle, from data to deployment, with automated pipelines that keep models reproducible and monitored.
- Custom ML model development
- Anomaly detection, forecasting and analytics
- Real-time inference pipelines
- MLOps: model monitoring and optimization
Computer Vision
Extract actionable insight from image and video data with state-of-the-art computer vision models.
- Object detection and classification
- Pose estimation and tracking
- OCR and image text analytics
- Edge device integration
Natural Language Processing
Enable machines to understand and act on human language with NLP powered by LLMs.
- Text summarization and search
- Conversational AI and chatbots
- Named entity recognition
- Document intelligence and semantic parsing
LLM and Agentic AI
Intelligent assistants built with LLMs, RAG pipelines and autonomous agents tailored to your workflows.
- Custom LLM integrations
- Retrieval-Augmented Generation
- Autonomous AI agent workflows
- Secure and compliant deployments
From discovery to production
A disciplined lifecycle that turns your data and goals into a deployed, monitored system.
- 01
Discovery and strategy
Understand challenges, define use cases, and assess data and models.
- 02
Data preparation
Clean, preprocess and validate structured and unstructured data.
- 03
Model development
Build and fine-tune models using TensorFlow, PyTorch and more.
- 04
Integration and deployment
Deploy across cloud, on-premises or edge systems.
- 05
Testing and optimization
Evaluate, tune and improve models for performance and scale.
- 06
Continuous monitoring
Adapt models with live feedback and evolving needs.
Faster drug discovery with smarter data
Streamline data integration, ensure compliance and accelerate insight across the R&D pipeline.
- Data collection. Ingest data from ELNs, instruments and digital health tools.
- Insight aggregation. Analyze clinical, lab and real-world datasets in one view.
- Regulatory automation. Enforce HIPAA, GxP and 21 CFR Part 11 compliance.
- Faster innovation. Reduce trial cycles and increase approval success rates.
Ready to put AI to work?
Tell us about the workflow. We will show you what a compliant build looks like.