AI Engineering
Intelligence, productionized.
We move AI from prototype to production: LLM-powered features, custom ML models, and computer-vision systems engineered with the evaluation, guardrails, and infrastructure that real users require.
There is a wide gap between an impressive AI demo and a feature you can put in front of customers. Most AI projects stall in that gap — no evaluation, no guardrails, unpredictable cost, and hallucinations no one caught.
We close it. We build retrieval pipelines that ground answers in your data, evaluation harnesses that measure quality before release, and the monitoring and cost controls that keep AI features reliable in production. We default to the most capable current models and design systems you can trust.
Our ai engineering capabilities
The specific ways we put this discipline to work for your business.
Generative AI & LLM Apps
Assistants, copilots, and automation grounded in your data with measurable quality.
- RAG pipelines
- AI agents & tool use
- Prompt & evaluation harnesses
- Guardrails & safety
Machine Learning Models
Predictive models that forecast trends and optimize decisions on your data.
- Predictive analytics
- Recommendation systems
- Anomaly detection
- Model monitoring
Computer Vision
Image and video analysis for automation, quality control, and recognition.
- Object detection
- OCR & document AI
- Real-time video analysis
- Quality inspection
AI Strategy & Integration
Pragmatic roadmaps and integration into the products and workflows you already run.
- Use-case discovery
- Build-vs-buy analysis
- Data readiness audit
- Cost & latency optimization
How we deliver, step by step
Discover
We identify high-value use cases and validate data readiness before committing to a build.
Prototype
A fast, measurable proof of concept against a real evaluation set — not a cherry-picked demo.
Productionize
Retrieval, guardrails, monitoring, and cost controls that make the feature dependable at scale.
Improve
Continuous evaluation and tuning as data, models, and usage evolve.
What you receive
- AI use-case & feasibility assessment
- Data pipeline & retrieval setup
- Production model or LLM integration
- Evaluation harness & quality benchmarks
- Guardrails, monitoring & cost controls
- Documentation & team enablement
Common use cases
A grounded chatbot or copilot that answers from your documents, accurately and with citations.
Document understanding and classification that removes hours of manual work per day.
Models that forecast demand, detect anomalies, or personalize experiences in real time.
AI Engineering questions, answered
Is our data safe with AI features?
Yes. We design with data governance in mind — private deployments, no training on your data without consent, and clear controls over what the model can access.
How do you prevent hallucinations?
We ground responses in your data with retrieval, add guardrails and validation, and measure quality with an evaluation harness before anything ships.
Which models do you use?
We are model-agnostic and choose per use case, defaulting to the most capable current models and optimizing for the right balance of quality, latency, and cost.
Other services
Need ai engineering expertise?
Tell us about your goals and we'll assemble the right specialists. Free consultation, clear proposal within 24 hours.