Workflows & Automation
A process can work well and still involve repeated entry, reminders, and checking between steps. We work with your team to clarify the sequence, connect the systems involved, and automate the parts with clear rules.
Talk to UsA Situation We Hear Often
This is how the problem usually shows up, and what changes at each step of the fix. Switch to By Service to see the work behind it.
Good People, Carrying Work Between Systems
Follow one customer request in four steps: carried by hand, connected, with the data kept in step, and with changes released safely.
One Customer Request, Carried by Hand
The request arrives by email
Read by a person
The details are typed into the business system
Entered by hand
Approval is requested by email
Waits for a reply
Availability is checked in a spreadsheet
A separate file
The customer calls for an update
Waits for someone to check
Every step works, and good people keep it moving. The time goes into the handoffs between them.
What We Can Work On Here
Scope of Work
Each of these can be a project on its own or part of a larger one. We start with the one your situation calls for.
01
Define steps, routing, approvals, responsibilities, and the information each person needs.
02
Record updates, calculations, notifications, document generation, scheduled jobs, and reconciliation against agreed rules.
03
Read invoices, forms, and incoming requests with machine learning, then classify and route each one into the workflow, with anything uncertain going to a person.
04
Connect tasks and status changes across applications, with checks for missing information and failed updates.
05
Move and transform data between business systems, with field mapping, validation, scheduled or event-driven updates, and handling for failed transfers.
06
Make data pipelines repeatable and easier to maintain with version control, automated data checks, release processes, monitoring, and clear responsibility when a flow fails.
07
Make work that cannot continue visible, route it to the right person, and provide a way to correct and resume it.
08
Automated checks, CI/CD pipelines, repeatable deployment, and release controls, with security checks built into the delivery process.
Case Studies
Real projects in this area: the business problem, what we built, and what changed.
Logistics & Supply Chain
A freight settlement business moved from manual paperwork to automated extraction, evidence checks, and structured results. The supplied estimates put manual review at roughly 10% of submissions, with typical single-page processing under a minute.
Development Workflows
A client needed a better way to move everyday software requests from the business to its development team. We connected request intake, task tracking, AI-assisted code changes, and developer review, moving from a two-week sprint cycle to releases in 1–2 days.
E-Commerce & Retail
Customers phoned to ask where their order was, and orders missing information waited for someone to reach the customer. An AI agent now answers order questions by message, WhatsApp, or phone, and a second one calls customers when an order needs their attention.
How We Work
Follow one process from its trigger to its result. Include the exceptions your team already handles, then decide which steps to simplify, connect, or automate. Agree how people can see and resolve a failed action.
From what triggers it to its result, with the people who do it, and not from a diagram of how it is supposed to work.
The cases your team already handles by hand decide whether automation helps or gets in the way, so they are captured before anything is built.
Some steps should disappear, some need two systems connected, and only the steps with clear rules are automated.
Every automated step says when it fails, who is told, and how the work is corrected and resumed.
Measuring It
These questions help define the improvement with your team and the measures appropriate to the engagement.
What It Looked Like in One Project
~10%
Need manual review, down from all submissions
Read the Case StudyFor Technical Leaders
What starts each step, and how the systems involved hand work to one another.
How a record in one system becomes the right record in the next, field by field.
The checks that stop a bad record early, before it travels further.
What happens when a step fails, and how a repeated attempt avoids doing the same thing twice.
What the automation is allowed to do, and the record it leaves of what it did.
How a flow is tested before it runs on live work, and how it is undone or recovered if needed.
These are the platforms and tools we use most for this work, and we are not limited to them.
n8n
Temporal
Zapier
Make
Apache AirflowMWAA
Dagster
AWS Step Functions
Azure Logic Apps
Google Cloud Workflows
dlt
dbt
PythonAWS GlueAWS DMSAzure Data FactoryAzure Database Migration ServiceGoogle Cloud DataflowGoogle Datastream
Apache KafkaMSK
RabbitMQAmazon MQAmazon SQSAzure Service BusGoogle Pub/Sub
GitHub Actions
GitLab CI/CD
Jenkins
Terraform
DockerECS
KubernetesEKS
HelmAWS CodePipelineAzure DevOpsGoogle Cloud Build
Vapi
Claude
OpenAI
Vercel eveAmazon Bedrock AgentsAzure AI FoundryGoogle Vertex AI
Amazon Textract
Azure AI Document IntelligenceGoogle Document AI
Slack
Microsoft Teams
Linear
JiraIf your business runs on a different stack, we adapt to it and build on what you already have.
Automation executes defined steps and rules. Operational AI handles interpretation, language, and patterns within a workflow. Governance sets approval requirements that the process must follow. DevOps connects software delivery with the people running and maintaining the deployed systems.
Simplifying a process or configuring an existing tool may be enough. Automate a step when its rules and exception handling are understood.
A Useful Starting Point
One that repeats often, follows clear rules, and costs real time today, such as re-entering the same details or chasing an approval. We follow it from start to finish before building anything, because simplifying a step or configuring a tool you already have is sometimes enough.
No. Many tasks have clear rules. AI becomes relevant where a step requires interpretation or analysis beyond those rules.
Yes. Automation takes over the re-entry, reminders, and checking between steps. Approvals, review, and exception handling stay as explicit steps, with the responsible person and the context they need visible.
Failures are recorded and routed to the person responsible, with a way to correct and resume the work. For flows the business depends on, monitoring and response can be covered by an agreed service level agreement (SLA).
You do, always. The workflows, integrations, and code we build belong to your business, and they stay with you if the engagement ends.
Share the problem, its business impact, and any systems or constraints involved. We can work from the business context, the technical detail, or both.
