Stop paying people to move data between systems.
We automate the repetitive operational work that sits between your tools, so your team spends its time on the parts that need judgement.
The problem, in your words.
Most operational cost is not in the work itself. It is in the handoffs: copying a record from one system into another, chasing an approval, re-keying an invoice, assembling the same report every Monday.
That work is invisible on an org chart and expensive on a payroll. It also scales linearly with growth, which is why headcount rises faster than revenue in operations-heavy businesses.
You are probably here because
Someone on your team maintains a spreadsheet that exists only to reconcile two other systems
A process stalls whenever one specific person is on holiday
You have bought automation tools before and they did not survive contact with your actual data
Growth means hiring in operations rather than in the parts of the business that compound
What we build.
Workflow automation
The end-to-end paths that cross departments: intake to fulfilment, quote to cash, onboarding to first value. Built against your real edge cases, not the happy path.
AI agents and assistants
Where the work needs reading, summarising or deciding rather than just moving. Scoped narrowly enough to be reliable, with a human checkpoint wherever the cost of being wrong is real.
CRM and ERP automation
Records that update themselves, stages that advance on evidence rather than on someone remembering, and reporting that does not need a weekly export.
Document and data processing
Invoices, forms, contracts and unstructured notes turned into structured records your systems can act on.
Scoping and evaluation first
We define what correct output looks like before building, then hold the agent to it. Our team built an LLM-as-a-judge evaluation framework at Parallel for exactly this.
Automating patient or customer intake across multiple locations
Automating patient or customer intake across multiple locations is the shape of engagement this page is most often about. The others we see: turning inbound documents into structured crm records; generating recurring reports from systems that do not talk to each other; routing approvals based on rules rather than inbox archaeology; summarising unstructured clinical or case notes ahead of an appointment.
Industries where we have done this: Healthcare, Professional services, Ecommerce, Operationally complex service businesses.
How it gets delivered.
| What happens | What you see | |
|---|---|---|
| Discover | We watch the handoff happen, count how often, and price the first workflow. | The workflow map and a fixed price. |
| Design | Edge cases, stop conditions and the human checkpoints, decided before code. | A run sheet you can argue with. |
| Develop | The first workflow live against real data by week three. | Records moving on their own, in staging. |
| Deploy | Rollout, monitoring, and a month of watching it run. | The Monday the copy and paste stops. |
We run our own product, Skiprr, and we built NeuroKind for a client. Either way we carry the on-call for software we wrote.
We run our own product, Skiprr, and we built NeuroKind for a client. Either way we carry the on-call for software we wrote.
Skiprr, ours: A brand-trained content studio for agencies. NeuroKind, built for a client: Early detection and support for neurodivergent minds. Both are on the work page.
Questions people ask first
