AI Automation Company

Most “automation” stops at simple triggers and templates. Real operational work — reading documents, making judgment calls, reconciling messy data — needs more. As an AI automation company, Krazimo builds automation that uses AI where judgment is required and plain rules where they’re enough, layered onto the systems you already run. We’re a boutique team of ex-Google engineers, capped at ten projects, so the people scoping your workflow are the ones who build and monitor it.

AI workflow automation services

Our AI workflow automation services take a whole process end to end rather than automating one isolated click:

• Document & data automation — extracting, classifying, and routing information from PDFs, emails, and forms that used to need a human to read them.
• Operational workflows — lead handling, onboarding, reporting, and reconciliation that span several tools and steps.
• Human-in-the-loop where it counts — automation that escalates the edge cases instead of guessing, so you keep control of the decisions that matter.

Where automation pays off

We don’t automate for its own sake. The work worth automating is high-volume, repeatable, and currently eating senior people’s time — invoice processing, claims triage, customer onboarding, internal reporting. We start by finding that work, then prove the ROI on one workflow before scaling. Where the job is genuinely autonomous and multi-step, we reach for AI agents and multi-agent systems.

Our process

Every engagement defines the success metric first — accuracy, time saved, cost per item — so “is it working?” has a number. We build, evaluate against that metric, deploy on top of your existing stack, then monitor for drift. It often grows out of, or into, a broader custom AI software development engagement. If you have a process that’s drowning your team, book a call and we’ll tell you what’s worth automating.

A real automation we shipped: Arivihan

For Arivihan, an edtech company in India, we automated the evaluation of CBSE board-exam-style subjective answers and mock tests — work that is slow, high-effort, and inconsistent when done by hand. The result: a 60% reduction in grading time, more consistent and fairer evaluation across students and graders, and actionable feedback showing where marks were lost. That’s the shape of automation worth doing — high-volume, judgment-heavy work that used to need a person reading every line.

Which processes are worth automating first

We start where the payoff is clearest: high-volume, repeatable, currently eating senior time. The usual first candidates are document and data processing, claims or application triage, lead handling, customer onboarding, and internal reporting. We prove the ROI on one workflow — accuracy, time saved, cost per item — before scaling to the next.

How an AI automation engagement works

Four phases, low risk: discovery (find the workflow and define the success metric), a scoped pilot with a risk-free trial, build & evaluate against that metric, then deploy on your existing stack & monitor for drift. You always know whether it’s working, because “working” is a number agreed up front.

A real automation we shipped: JSTFYD

For restoration contractors, our JSTFYD platform automates insurance-claim defense end to end. Response time to insurers and TPAs dropped from multiple days to a few hours (including verification), settlements improved by ~6% through consistent, standards-backed defenses, and one restoration company saved about 45 hours per week — roughly $800k in projected value. That’s automation pointed at the money, not just the busywork.