Your ops team shouldn't be doing data entry.
OpsVera builds custom AI agents that take over the repetitive work your team does by hand — reading whatever arrives, working out what it means, and acting inside the systems you already run. Purchase orders and invoices are where we start most often, not the limit of it. Every write passes a rule you set. Every action is logged.
Built by a team that has spent years designing and running the operational systems this work happens inside — not one learning your industry on your budget.
See an agent run
Live mock · loops
PO → Order entry agent
watching ops@ · 3 in queue
1 · Read
purchasing@northline-trading.com
PO 4471 — 14 lines, deliver wk 34
NL-PO-4471.pdf
scanned · 2 pages · 412 KB
Vendor sends a scanned PDF with a different layout every quarter. No template needed.
2 · Extract & check
18 fields mapped
Customer
Northline Trading Co.
99%
PO number
NL-PO-4471
99%
Line items
14 · 2,480 units
97%
Requested date
wk 34 → 2026-08-17
82%
Date written as a week number. Below your 90% threshold, so it goes to a person.
3 · Approve → Act
Held for approval
One field under threshold. Rima in Ops sees the document and the extraction side by side.
NetSuite · Sales orders
SO-118204 · draft
Order staged with all 14 lines. Nothing posts until the date is confirmed.
Audit log
09:41:02 read · 09:41:04 extracted 18/18 · 09:41:04 gate=hold(date<90) · queued → r.haddad
Four hours a day, every day, spent moving data between windows.
01
POs retyped by hand
A PDF lands in a shared inbox. Someone opens it, opens the OMS, and types 14 line items across two windows. Sixty times a day.
02
Invoices matched line by line
AP opens the invoice, finds the PO, compares vendor, totals and every line. The 5% that don't match are the only part worth a human.
03
"Where’s my order?" answered manually
The same question, forty times a week, each answer a lookup and a paragraph someone types from scratch.
04
Exceptions fall through cracks
A short shipment gets noticed a week late because nothing routed it to anyone. The cost compounds downstream.
Zapier and RPA break the moment the input is a scanned PDF or a differently-worded email. Generic AI chat can summarise the document but can't write to your system of record or prove what it did. That gap is the whole job.
Read. Extract. Approve. Act. And when it isn't sure, it asks.
Read
Watches an inbox, folder or API. Handles PDFs, scans, spreadsheets and free-text email — not just clean structured payloads.
Extract
Pulls out the fields your workflow needs, mapped to your field names, with a confidence score attached to each one.
Approve
Your rules decide what passes silently and what waits for a person. The gate loosens as trust is earned — never the reverse.
Act
Writes to your OMS, ERP or accounting system. Idempotent, so the same document never gets processed twice.
↳ Exception
Not a failure state — a visible branch. Anything that doesn't match or scores low goes to the right person with the discrepancy shown, not guessed at.
We build around how you actually work.
Most platforms in this category start generic and ask you to bend your process to fit. We start with your worst workflow, on your systems, with your field names and your approval rules — then extract the reusable pattern on our side, not yours.
The plumbing underneath — ingestion, extraction, approval, action, audit — is the same infrastructure on every build, which is why a custom agent still ships in days.
Generic platform
Configure your process into their template. Whatever doesn't fit becomes a manual workaround your team owns forever.
OpsVera
We scope your actual process, build against your actual systems, and hand back an agent that matches how your ops team already thinks.
Their roadmap
Set by whatever the largest logo asked for last quarter.
Ours
Set by which workflows keep repeating across real deployments. Build it three times, it becomes a template — cheaper and faster for the next client.
Supply chain & logistics, by people who built it.
We've spent years inside supply chain operations — building and running the order and fulfilment systems that large trading and logistics businesses depend on, and watching the same manual work pile up around them. You won't spend the first fortnight teaching us what a short shipment or a three-way match is.
Supply chain & logistics- 01Freight forwarders
- 023PLs and fulfilment operators
- 03D2C brands with real logistics ops
- 04Trade, import & export companies
How we handle your data
Isolated at the infrastructure level
Every client's data is walled off in the schema, not just filtered in application code. That decision was made on line one, not after a security review.
Every action logged
What was read, what was extracted, what confidence it carried, who approved it, what got written. Exportable, and readable by a person.
Nothing writes without your rule
You define what passes automatically and what waits. We're building toward formal certification and will say so plainly when we have it.
A pilot on your own documents, measured against your own baseline.
The first workflow runs alongside your existing process with every write gated. You judge it on numbers from your data — not a reference call with someone whose operation looks nothing like yours.
What gets measured
Extraction accuracy, per field
On your real documents, not a benchmark set. Reported field by field so you can see exactly where a human is still needed.
What gets measured
Time per item, before and after
We take a baseline from how your team works today, then compare. If the difference isn't worth the retainer, that's a real answer.
What gets measured
Exception rate, and who cleared it
How often the agent stopped, why, and how long it took a person to resolve. This is what tells you when to loosen a gate.
Bring us your worst manual workflow. We'll show it running on your real process in 30 minutes.
No slide deck. The call is a live walkthrough of the workflow you'd hand over first, with the engineer who'd build it.
Book a workflow call