Solution — Applied Intelligence
One workflow, automated end to end
We take a single manual process — documents read, data re-keyed, exceptions flagged by email — and replace it with an automation layer that has a model in the middle and your people in the loop. Built API-first, on infrastructure you own.
01 — The Problem
Most companies still run at least one critical process the manual way: a person reading incoming documents, extracting what matters, re-keying it into other systems, and flagging exceptions by email. The process works — which is exactly why it never gets fixed — but it consumes skilled staff hours daily and scales linearly with volume.
The usual failure mode is the opposite extreme: a broad "AI transformation" initiative that explores everything and ships nothing. We apply a one-workflow rule instead — scope a single process end to end, prove it, and only then look at the next one.
02 — How We Run It
Map the real workflow
Discovery maps the process as it actually runs — including the undocumented judgment calls your team makes without noticing — before any architecture is drawn. Those judgment calls are where automation projects quietly fail.
A model in the middle, people in the loop
Document intake, LLM-based extraction with confidence thresholds, validation against your systems of record, and a human review queue for anything below threshold. Low-confidence cases route to people by design — the goal is redirected hours, not a headless process.
Tune on your corrections
The people who ran the manual process review and correct outputs from the first week. That builds trust with the team the system affects most — and produces the evaluation data the system is tuned against.
Hand over the keys
Every capability is exposed as an API endpoint so your own team can extend it. Deployed in your cloud accounts under your access controls, with source, documentation, prompts, and evaluation datasets handed over. Nothing requires Markosh to operate it.
03 — The Shape of It
- 1 workflow
- scoped end to end — no broad AI exploration
- API-first
- every capability is an endpoint your team can extend
- owned
- your cloud, your access controls, your IP
- human
- escalation path for low-confidence cases, by design
An evaluation suite is defined before we build and reported against honestly throughout. If the workflow is a poor fit for automation, the use-case audit says so — that is the point of doing it first.