Applied AI Studio

Applied AI, shipped.

We build and deploy production-ready AI products that solve real-world problems. From medical logbooks to intelligent stock analysis, we ship the future of work.

4+Active Apps
99%Uptime
ShipCulture
MEDICAL LOGBOOK
STOCK-AI
LEARN-AI
/apps · portfolio

Focused apps, not platforms.

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/method · how we build

A short loop. Evidence over opinions.

01
Frame

Find the smallest user job an AI app can own end-to-end. Skip the platform talk.

02
Retrieve

Hybrid retrieval — BM25 + dense, then rerank. Grounding before generation, always.

03
Evaluate

Offline goldens, online traces, human review loops. Evals are the moat.

04
Ship

Ship in days, harden in weeks. Latency is a feature; we treat it like one.

/agents · architecture

Planner-executor splits, with evals at the seams.

Single LLM calls fall over once you need real tools. We split the model into a planner that proposes a graph of steps and an executor that calls retrieval, screeners, and writers.

Between steps we run lightweight evals — schema, citation, and self-consistency — so a bad hop never silently rolls into the final answer.

planner executor retrieve guard.evals
agent.graph.svg running
user.goal/inputplannerplan(graph)executorcall(tool)retrievescreenwrite
input
reason
output
/contact · start a thread

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