We architect workflow automation, LLM integrations, and autonomous agent systems for teams ready to operate at the next capability tier.
We map your operational chokepoints and rebuild them as event-driven pipelines. Slack triggers, CRM sync, document parsing, approval routing — removed from human hands and moved into systems that don't sleep.
Production-grade LLM deployments with retrieval, evaluation, and cost controls. We build the plumbing that turns a model API into an operational asset — RAG systems, fine-tuned adapters, structured outputs, guardrails.
Autonomous agents that own entire processes end-to-end. Multi-step reasoning, tool use, memory systems, and self-correction loops — deployed on your infrastructure with observability baked in.
A structured teardown of your stack to identify which processes belong with humans, which belong with models, and which belong with hybrids. Delivered as a prioritized roadmap with cost and capability mapping.
We spend the first phase embedded inside your stack — reviewing process flows, data systems, and human throughput. The output is a technical map of where inefficiency lives and what the intervention shape needs to be.
We specify the system: models, orchestration layer, data flow, failure modes, observability. Every component is documented before a line of code ships. You review and approve the architecture before we build.
We build, deploy, and hand off. Infrastructure lives on your cloud. Documentation lives in your repos. Your team owns what we build — no vendor lock, no recurring dependency.
CRCT was built on one premise — most companies don't have an AI problem, they have a workflow problem that AI happens to solve. We take engagements where the outcome is measurable and the path is technical.
We don't run strategy workshops, produce maturity assessments, or write 40-page reports nobody reads. We write code, deploy systems, and hand over working infrastructure.