From unstructured input to a completed entry in your system of record.
Back-office work is mostly the same shape: information arrives in one place, a human reads it, validates it, and types it into a second place. We replace the human with a managed AI agent that does all three steps end-to-end. Here's exactly how that runs.
The three-step loop.
Every back-office workflow we run for a customer breaks down into the same three steps. The agent owns the full loop — we deploy, monitor, and maintain it. You only pay when a task completes successfully.
-
Ingestion
The agent monitors your inboxes, shared folders, intake forms, or legacy systems for new unstructured data — invoices, PDFs, lead lists, customer applications, document uploads, anything that arrives without a clean API. The moment something new lands, the agent picks it up.
-
Extraction and processing
The agent reads and categorises the data — without the human-error problem. No fatigue, no mistypes, no skipped checks at the end of a shift. It applies your business rules, cross-references other systems where it needs to (does this address fall inside the catchment area? does this invoice match an open PO?), and flags genuine edge cases for human review instead of guessing.
-
Execution
The agent logs into your CRM, ERP, admin panel, or database — through an API where one exists, through the UI where it doesn't — and inputs the processed data automatically. Every action is logged. Every outcome is auditable. The swivel-chair loop closes without anyone on your team in the middle of it.
A worked example: a shared-mobility operator.
A shared-mobility operator we work with needed every new rider vetted by hand: someone cross-checked the applicant's name on an intake form against a proof-of-address document, confirmed the address fell inside the operator's service area, copy-pasted the rider's details into their admin panel, and provisioned a pass. Five minutes per application. Same three steps, every time.
We deployed an AI agent on the seam between the intake form and the admin panel. The agent ingests each new form submission, extracts and validates the rider's identity and address against the operator's service boundary, and executes the pass provisioning in their admin panel — end to end, with no human in the loop. Edge cases get flagged for human review instead of processed wrong.
Running for six weeks of production. 32 of 34 applications fully automated. The two edge cases were correctly flagged and resolved by our team. 170 manual minutes removed on the first sample alone.
What this means for your stack.
You don't need to change your tools.
The agent works with what you already use. If your back-office team accesses it today — Typeform, Salesforce, HubSpot, NetSuite, SAP, a custom admin panel from 2008, an Excel sheet on a shared drive — the agent can access it too.
You don't need an API.
We use APIs where they exist because they're faster and cleaner. Where they don't, the agent operates the UI directly. Legacy systems and unsupported software are not deal-breakers — they're often where the work is.
You don't need to manage the AI.
Choosing the model, prompt-tuning, debugging when it breaks, replacing the agent when a better one ships — that's our job, included in the per-task price. You deal with us (humans). We deal with the AI.
Let's map your loop.
25-min call with Ping, our CEO. Bring one workflow your ops team complains about most. We'll have an AI agent running on it within 48 hours.
Keep reading.
Human offshore teams vs AI agents — side by side →
Frequently asked questions about AI-managed outsourcing →