01
AUTO.01 · DOCUMENTS
Invoice & document processing
Invoices, POs, and receipts arrive in any format and leave as structured, validated records. Exceptions route to a human — everything else doesn't need one.
Your operations, in.
Outcomes, out.
What happens inside is our job.
We design and run the automation layer between your messy inputs and the outcomes you actually need — reports, actions, alerts — without you having to think about the plumbing.
01 Observe every input 02 Route every exception 03 Verify every outcome
Six problems, one discipline.
02
AUTO.02 · SUPPORT
Customer-support triage
Incoming tickets are read, classified, and routed before an agent opens them. Priority signals surface automatically; routine replies draft themselves.
03
AUTO.03 · DATA
Data entry & migration
Records move between systems that were never meant to talk — CRMs, spreadsheets, legacy databases — with field mapping and validation built in, not bolted on.
04
AUTO.04 · REPORTING
Reporting pipelines
Numbers get pulled, reconciled, and shaped into the same report every cycle — on schedule, without a spreadsheet marathon the night before it's due.
05
AUTO.05 · APPROVALS
Approval workflows
Requests find the right approver, wait exactly as long as they should, and escalate on their own. Nothing sits in an inbox because someone forgot.
06
AUTO.06 · AGENTS
AI-agent integrations
LLM agents act inside your systems with defined tools and guardrails — drafting, deciding, and escalating within limits you set, not limits it discovers.
Four steps. No mystery.
- STEP 01 — DISCOVER
Discover
We map the operation as it actually runs — not the org chart version. Every manual handoff, workaround, and spreadsheet-of-record gets logged.
- STEP 02 — MAP
Map
The workflow gets redrawn as a system: inputs, decision points, exceptions, and the systems of record it has to touch. This is the blueprint we build to.
- STEP 03 — AUTOMATE
Automate
We build the pipeline — APIs where they exist, RPA where they don't, agents where judgment is needed — and test it against real edge cases before it touches production.
- STEP 04 — MONITOR
Monitor
Live systems get watched, not shipped and forgotten. Exceptions alert, throughput gets logged, and the pipeline gets tuned as your operation changes.
It's a black box from the outside. Not from ours.
job_log.sh — black box, live
$ ⇒ invoice_batch: 142 processed, 0 exceptions, 11m saved
Illustrative job log — stylized example, not client data.
Integration capability
- REST / GraphQL APIs
- Webhooks
- RPA
- LLM agents
- ERP connectors
- CRM connectors
We plug into what you already run — we don't ask you to replace it first.
You shouldn't have to think about the plumbing.
You define the outcomes. We guarantee what happens inside.
That's the whole point of a black box.
Ranges, not fake precision.
No client names, no case studies, no invented totals. These are industry-typical ranges for automation work of this kind — treat them as a starting estimate, not a promise.
20–40%
of manual hours reclaimed on automated workflows
Industry-typical range for document- and data-heavy processes — verify for your case.
60–90%
reduction in manual exceptions after monitoring stabilizes
Depends heavily on data quality and process variance going in — verify for your case.
2–8wks
typical time from discovery to first automated workflow live
Scope-dependent; a single workflow moves faster than a full department. Verify for your case.
Tell us what's manual. We'll tell you what's possible.
No discovery call script, no sales deck — just describe the workflow and we'll tell you honestly whether automation is worth it.
[email protected]Demonstration site — this brand and domain are available for acquisition.