Useful by design
Start with the workflow, the user, and the decision the system needs to support.
Applied AI systems
We build practical AI systems that connect models, tools, data, and users into working products.
We focus on AI agents, retrieval, knowledge graphs, evaluation, realtime voice and video AI, and low-latency infrastructure. We build systems to be useful, measurable, and ready to scale.
USEFULMEASURABLESCALABLE
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Focus areas
Seven connected areas of practical AI.
From the user interaction to the infrastructure underneath it, each layer is designed as part of one working system.
01
AI Agent Systems
Agents that use tools, follow workflows, and operate with clear human oversight.
Controlled execution
02
RAG, Memory, and Knowledge Graphs
Systems that retrieve information, remember useful context, and show how ideas connect.
Grounded context
03
LLM Evaluation and Observability
Evaluation loops, traces, and regression checks for improving AI behavior.
Measured quality
04
Realtime Voice and Multimodal AI
Speech, text, image, and interaction pipelines for natural AI interfaces.
Natural interaction
05
Video AI Agents and VMS
Video AI that turns camera streams into searchable events and clear operator workflows.
Actionable video
06
Local and Low-Latency AI Infrastructure
Local model serving, realtime backends, and latency-focused AI pipelines.
End-to-end latency
07
Scalable AI Platforms
Modular AI systems designed for growth, monitoring, safety, and maintainability.
Maintainable growth
Approach
Clear engineering. No black boxes.
The model is one component. A useful system also needs context, boundaries, feedback, and a path to reliable operation.
Measurable in practice
Define traces, checks, and evaluation loops so quality can improve with evidence.
Built to evolve
Keep models, tools, data, and deployment modular enough to change without a rewrite.
01 Observe
→02 Define
→03 Measure
→04 Improve
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