Stack
AI & Intelligence
LLMs, machine learning, and automation embedded in production workflows.
AI & Data
AI Integration
LLMs, RAG, and agents wired into existing products and workflows.
We integrate practical AI into existing products and workflows—document intelligence, semantic search, assistants, and automation where they reduce real operational work. That includes RAG pipelines with proper retrieval and guardrails, LLM API integration with evaluation frameworks, and AI features embedded into support, ops, and knowledge workflows. The goal is production reliability, not demos.
Capabilities
- LLM API integration
- RAG pipelines
- AI assistants & copilots
- Document Q&A
- Semantic search
- Workflow automation
When teams need this
- Manual document handling at scale
- Knowledge locked in unstructured data
- Repetitive support or ops queries
- Search that misses context
Our approach
Map the workflow, identify high-value touchpoints, then build with retrieval, guardrails, and evaluation built in.
Technologies we work with
Typical deliverables
- AI feature integrations
- RAG systems
- Document intelligence
- Support automation
AI & Data
Machine Learning
Models for classification, prediction, and intelligent automation.
We take machine learning from experimentation through production—prediction, classification, recommendation, and anomaly detection with engineering discipline. That means validated training pipelines, reproducible experiments, model deployment with monitoring, and APIs that downstream systems can depend on. We focus on problems where data quality and success metrics are clear enough to justify the investment.
Capabilities
- Classification models
- Prediction systems
- Recommendation engines
- NLP pipelines
- Anomaly detection
- Model deployment
When teams need this
- Need forecasts from historical data
- Manual classification at volume
- Personalization requirements
- Anomalies going undetected
Our approach
Validate data readiness and success metrics first, then build reproducible training and deployment paths.
Technologies we work with
Typical deliverables
- Trained models
- Prediction APIs
- ML pipelines
- Monitoring setup