The internal work nobody wants, handled.
We deploy AI agents that take on the operational drag inside your business, ticket triage, invoice approvals, helpdesk Q&A, data reconciliation, scheduled runbooks. Reliably, auditably, around the clock.
Where we automate
most often.
Not every workflow is an AI problem. We start with the highest volume, highest friction work, where automation pays back fastest and the failure modes are knowable.
Ticket Triage & Routing
Inbound tickets classified, prioritized, and assigned to the right team in seconds, with deflection of common issues at first touch.
Invoice & Approval Flows
OCR + reasoning to extract, validate, and route invoices through approval chains, with policy checks at every step.
Internal Helpdesk Q&A
Employees ask in Slack or Teams; the agent answers from your policies, runbooks, and Confluence, with citations.
Data Reconciliation
Cross system matching across CRM, billing, and finance, flagging discrepancies a human can resolve in one click.
Scheduled Runbooks
Recurring ops, onboarding, offboarding, monthly reports, audit prep, running on a schedule and reporting back when done.
Anomaly & Escalation
Continuous watch for outliers in your operational data, with smart escalation to the right human, with full context.
Five signs your operations are running on heroics.
Nobody searches for "operations automation" on a good day. They search after the third month end that slipped, the RPA bot that broke again, or the realization that headcount doubled and throughput did not. Here is what each of those looks like from our side.
Headcount Grew, Output Did Not
The classic mid market trap: every new customer adds manual work, so every growth spurt adds hires who spend their days moving data between systems. Research puts the cost of manual data entry around $28,500 per employee per year, before counting the errors. We instrument the workflow first, measure where the hours actually go, and automate the highest volume steps, so the next growth spurt gets absorbed by software instead of a job posting.
The Exception Pile Your RPA Cannot Touch
If you already run RPA bots, you know the pattern: the bot handles the clean 70 percent, and a human team handles the pile of exceptions, odd formats, and edge cases the bot throws back. That pile is where the labor cost actually lives, and it is exactly what reasoning agents are built for. We do not replace your working bots. We put an agent on the pile they leave behind, which is usually where the fastest payback on this entire page hides.
The Inbox That Secretly Runs Your Business
Orders arriving by email. Supplier confirmations buried in threads. Status requests answered by whoever notices first. When operations run through an inbox, nothing is measured and everything depends on someone being at their desk. Our agents read the inbox, extract what matters, act in the systems of record, and reply, and organizations automating email based operations report the majority of those interactions handled without a human touch.
Month End That Takes Two Weeks
Reconciliation across CRM, billing, and finance, chasing approvals, assembling the same report from the same five exports every single month. We automate the matching, flag only the genuine discrepancies for one click human resolution, and run the close as a scheduled sequence that reports back when done. When the numbers live in your ERP, the agent works against it directly, so finance stops being a spreadsheet assembly line for one week in four.
Onboarding and Offboarding That Always Slips
The new hire whose laptop and accounts arrive a week late. The leaver whose access quietly survives them. Joiner and leaver workflows touch a dozen systems, which is why they slip, and why they are perfect agent work: triggered by HR, executed everywhere, verified, and logged. The access side of this runs on the zero trust identity foundation, and together they close one of the most common security findings we see.
Sometimes the Answer Is a Script, Not an Agent.
A model reasoning over a task that a twenty line script could do is expensive theater. Part of our workflow audit is sorting the work into three buckets: deterministic steps that get plain automation, judgment steps that get an agent, and steps that should simply be deleted. Clients are sometimes surprised how much lands in bucket one and three. Their invoice is smaller for it, and the automation that ships is the kind that does not need a model to babysit.
Write Access Is Earned, Not Granted.
Every automation we deploy starts in shadow mode, recommending actions while your team still executes, and we measure the agreement rate between agent and human before anything flips to autonomous. Documents that need understanding first flow through our document AI layer, and the whole pipeline runs under the guardrails our enterprise AI agents practice builds as standard. Autonomy is the reward for proven accuracy, never the starting point.
From workflow audit to live automation.
We pick the right workflow first, prove it works in shadow mode, then roll it out, with kill switches and rollback at every stage.
Workflow Audit
We shadow the team and instrument the workflow. Volume, time per step, error rate, escalation paths, all measured before we touch a thing.
Build Order
We rank automation candidates by ROI and risk. The first build is always the one with the cleanest payoff and smallest blast radius.
Shadow Mode Pilot
Agent runs alongside the team for two weeks, recommending, not executing. We measure agreement rate before flipping it on.
Phased Production
Rolled out by team or volume bucket, with monitoring, kill switches, and weekly review of escalations and edge cases.
Automation economics, and what to do with the RPA you already bought.
This market sells transformation and delivers maintenance contracts. Here are the real numbers on cost, coverage, and the awkward question of the bots you already own.
A focused single workflow automation typically runs $8,000 to $30,000, and complex multi system workflows with approval logic and compliance requirements run $30,000 to $60,000 and beyond. Entry level implementations for smaller teams start around $5,000 to $8,000. The honest cost driver is not the AI, it is the number of systems the automation must read from and write to, and the messiness of the inputs. That is why our audit measures the workflow before anyone quotes it, and why per workflow pricing beats platform licensing for most mid market teams.
No, and be wary of anyone who says yes. RPA that runs stable, structured, high volume work should keep running; ripping out working bots to chase a trend is waste. The honest industry picture: 30 to 50 percent of RPA projects miss their objectives, maintenance consumes 60 to 75 percent of typical RPA budgets, and bots break whenever a screen or format changes. Agents fix exactly those failure modes, handling the exceptions, format changes, and judgment calls your bots escalate. The right architecture in 2026 is usually hybrid: your bots keep the assembly line, our agents take the exception pile, and the maintenance treadmill finally slows down.
For simple, linear, low stakes flows, yes, and you should. The line appears when the automation touches money, compliance, or customer promises, because then the real product is not the workflow, it is everything around it: error handling when a system times out mid transfer, audit trails an auditor accepts, retry logic that does not double pay an invoice, and someone accountable when it breaks at 2am. DIY automations tend to work until their builder changes jobs. If your workflow can fail quietly without damage, build it yourself with our blessing. If a silent failure costs real money, that is what you are hiring us for.
Less than the vendors imply and more than the skeptics fear. A realistic target for a well chosen workflow is 60 to 80 percent of volume handled end to end, with the remaining exceptions deliberately routed to humans, and McKinsey's estimate is that agents can automate 15 to 40 percent of knowledge work that was previously unautomatable, not all of it. Our own stat above, 60 percent plus of tickets resolved without humans, sits inside that honest range on purpose. Anyone promising 100 percent automation is describing a workflow that will fail silently, which is worse than one that escalates loudly.
Model and infrastructure spend scales with volume and typically lands in the hundreds to low thousands per month per workflow, a fraction of the labor it replaces. The comparison that matters is maintenance: traditional RPA maintenance consumes most of its budget because bots break on every change, while agents absorb format and interface drift by design, so upkeep is a tuning retainer rather than a repair contract. Every proposal includes a projected cost per task at your volumes, next to the measured cost of the human handling it today, so the margin is visible before you sign.
You do, entirely and usefully. Workflow definitions, prompts, integration code, and runbooks live in your repositories, run under your cloud and model accounts, and are documented for an engineer who has never met us. The audit data from stage one, your workflow volumes, error rates, and costs, is yours too, and it is valuable even if you never automate anything. We are confident enough in the biweekly tuning to make leaving easy, because retention through lock-in is just churn with extra steps.
Pick the workflow your team complains about in every retro. The audit will tell you what it truly costs today, what an agent would change, and whether the honest fix is a script, an agent, or a process change that costs nothing.
Questions about
Operations Automation
High volume, rules driven, and well instrumented work with clear inputs and a defined outcome. Ticket triage, invoice processing, and internal helpdesk Q&A are usually the first wins.
Action allowlists, dollar value approval gates, rate limits, and a shadow mode pilot before any write actions. We also build a kill switch you can hit from a dashboard at any time.
It replaces the repetitive work. Your team stops doing the same triage 200 times a day and starts working on the cases that actually need their judgment, and the work the team didn't have time for before.
Yes, Jira, ServiceNow, Zendesk, Slack, Teams, Confluence, NetSuite, SAP, Workday, custom internal tools. If it has an API or a webhook, we connect to it.
For high volume workflows, payback is usually inside 90 days post launch. We share a measurement plan during scoping so you know exactly what you're tracking against.
Stop experimenting.
Start deploying AI that works.
Book a free discovery call. We'll audit your workflows, scope a working prototype, and tell you honestly which ones are worth automating first.
info@croncore.com