cashcrown // ai.agents
extraction, classification, OCR.
You need “document agent”, but building it in-house gets stuck on integrations, maintenance and lack of time — and the result tends to be fragile and hard to scale.
extraction, classification, OCR. We deliver it as part of “Autonomous agents & automation”: a working system with observability, safety gates and documentation. Models are always reached through the router — we mask PII before it leaves for the cloud.
We break the real flow down into steps, data and decision points.
We define the scope, tools and gates; we wire in the LLM router.
Plan → execution → verification (log/test), with rollback.
Observability, alerts, a gradual widening of autonomy.
Only within the scope you set — through API contracts and permission gates. Every action is logged and reversible.
Model access goes through the router; we mask PII before anything leaves for the cloud, and we handle sensitive paths locally (self-hosted LLM + BGE-M3).
With an audit of a single process and a pilot. We show a working agent before we ask for your trust.
We work in ranges that depend on scope — the entry point is a fixed-cost pilot with one measurable KPI. If a process eats a dozen to several dozen hours a month, the deployment usually pays back in 2–4 months. Calculate the return in our ROI calculator.
Yes — we design compliance in from the start: the agent introduces itself as AI (transparency), irreversible actions pass through a confirmation (human-gate, human oversight), and every step is logged. We mask PII before the cloud; profiling or decisions about people add a DPIA.