Custom AI Applications Built Around Your Business
When nothing on the market fits the problem, the system gets built. AI-native applications designed around your data, your workflow, and the people who will use them every day.
When you need this
Off-the-shelf tools solve a generic version of your problem, and the gap between that and how you actually work is where all the effort goes.
Design and build AI-powered applications around your specific business requirements, data, workflows, and users.
Let's Get Started- Discovery first
The use case, the data available, and what success measurably looks like, all settled before anyone writes code.
- Full-stack delivery
Interface, application, data layer, and model integration built and shipped by one team.
- Designed to be trusted
AI features people will actually use: visible sources, editable output, and an obvious way to correct it.
- Room for the next one
Architecture that accommodates the second and third use case instead of hard-coding the first.
What we work in
The tools this work runs on, and what each one is here for.
Next.jsProduct front ends that stream model output as it arrives.
FastAPIPython services around the models, typed end to end.
ClaudeThe model at the core, behind evaluations we can rerun.
PostgreSQLApplication data, conversation history and audit trails.
PyTorchCustom models when an API model is not the right fit.
DockerThe same build from a laptop to production.
The rest of what we build
Most engagements touch more than one of these. Start wherever the problem is.
LLM Integration & AI Copilots
Integrate LLMs into existing applications and workflows to give teams and customers intelligent capabilities.
AI Workflow Automation
Automate repetitive business processes using AI, APIs, agents, and existing business systems.
RAG & Enterprise Knowledge
Build AI systems that securely retrieve and use your company's data, documents, and knowledge.
AI Architecture & Infrastructure
Design the architecture, data pipelines, model integrations, security, monitoring, and infrastructure required to operate AI systems reliably.
AI Modernization
Take existing AI work, including prototypes, notebooks, and early integrations, and turn it into a reliable production system.
Start With a Focused Use Case
ArcusScale can help identify a practical opportunity and build a focused pilot before committing to a larger implementation.