Business automation services — Engineering automation around your business.
Five ways we remove repetitive work. Most engagements combine several—the process decides which tools are used, not the other way around.
Workflow Automation
Replace repetitive multi-step work with reliable automated workflows.
The problem it solves
Many routine processes are a chain of small, predictable steps: check a value, update a record, send a message, create a task. Each step is easy, but together they consume hours every week and depend on someone remembering to do them in the right order.
Example processes
- Routing new requests to the right person or queue
- Creating tasks and folders when a project is approved
- Sending scheduled reminders and follow-ups
- Moving records between stages as conditions are met
How Lorryn approaches it
- 01Map the process as it runs today, including the exceptions people handle informally.
- 02Separate the predictable steps from the ones that need a decision.
- 03Build the workflow on the platform that fits your systems and reliability needs—an automation platform, scheduled jobs, or custom code.
- 04Add logging, retries, and alerts so failures are visible rather than silent.
What stays under human control
- Approvals and sign-offs
- Handling of anything that falls outside defined rules
- Decisions about when to change the process itself
AI-Assisted Operations
Use AI where software needs to understand documents, emails, requests, or unstructured information.
The problem it solves
Traditional automation needs structured input. A lot of operational work starts with something unstructured—an email, a scanned form, a free-text request—so a person has to read it before anything else can happen.
Example processes
- Classifying incoming email by type and urgency
- Extracting fields from invoices, forms, and PDFs
- Drafting replies to routine requests for review
- Summarizing long threads or documents into structured records
How Lorryn approaches it
- 01Use a language model only for the step that requires interpretation; everything around it stays deterministic.
- 02Validate model output against rules and source data before it touches a business system.
- 03Set confidence thresholds so uncertain results go to a person instead of moving forward.
- 04Measure accuracy on your real examples before deployment, not on a demo.
What stays under human control
- Review of low-confidence or unusual results
- Anything sent to a customer, unless you explicitly approve automatic sending
- Judgment calls the model is not designed to make
Systems Integration
Connect applications that currently require employees to manually transfer information.
The problem it solves
When two systems don't talk to each other, people become the integration—re-keying data, exporting and importing spreadsheets, and reconciling differences. It is slow, error-prone, and invisible in most reporting.
Example processes
- Syncing customer records between a CRM and an accounting system
- Pushing form submissions into a project management platform
- Keeping inventory, order, or scheduling data consistent across tools
- Consolidating data from several systems into one report
How Lorryn approaches it
- 01Identify the system of record for each piece of data so there is one source of truth.
- 02Use official APIs and supported connectors wherever they exist.
- 03Design for failure: idempotent updates, conflict handling, and a clear audit trail.
- 04Document every integration so your team knows what moves where and why.
What stays under human control
- Resolution of conflicting records
- Access permissions and credentials
- Changes to which system owns which data
Custom Automation Engineering
Build purpose-specific software when standard automation platforms are not enough.
The problem it solves
Automation platforms cover a lot, but not everything. High volumes, complex logic, strict security requirements, or unusual systems can push a process beyond what a no-code tool handles reliably.
Example processes
- Services that process large batches of documents or records
- Connectors for systems without an off-the-shelf integration
- Internal tools that give staff a simple interface to an automated process
- Validation and reconciliation logic too complex for a visual workflow
How Lorryn approaches it
- 01Write focused services in Python or JavaScript with tests and version control.
- 02Keep the footprint small and the architecture easy to hand over.
- 03Deploy to infrastructure you control or that fits your security requirements.
- 04Provide documentation your team—or another engineer—can maintain.
What stays under human control
- Ownership of the code and infrastructure
- Release approval for changes
- Business rules encoded in the software
Managed Automation
Monitoring, maintenance, optimization, and ongoing support after deployment.
The problem it solves
Automations run inside systems that change. APIs update, fields get renamed, volumes grow, and edge cases appear. Without ownership, a working automation slowly becomes an unreliable one.
Example processes
- Monitoring runs, failures, and exception queues
- Updating automations when connected systems change
- Reporting on volume, exceptions, and time saved against the baseline
- Tuning rules and thresholds as real-world data accumulates
How Lorryn approaches it
- 01Set up alerting so issues are caught before they affect your team.
- 02Review performance against the original baseline on a regular cadence.
- 03Prioritize improvements by measured impact, not by what is newest.
- 04Keep documentation current as the automation evolves.
What stays under human control
- Priorities for what to improve next
- Approval of changes to live processes
- The decision to retire an automation that no longer earns its place
Not sure which service fits?
Most organizations don't need to know. Describe the work that's taking too long, and we'll work out the right approach together.
A free 15- or 30-minute call with the people who build it. No platform commitment. No obligation to build.