Founder-led AI implementation for one practical workflow
BaristaLabs works with owners, operators, and technical leaders who need to improve one recurring workflow. The senior people who assess the work also make its architecture, risk, and implementation decisions.
Use this page to decide whether the people, engagement, proof, and fit match your workflow.
You work with the people who make the key decisions
Sean McLellan leads architecture and implementation and joins discovery and build decisions. Stilson Greene adds creative strategy and client-experience work when clear messaging, humane interfaces, or repeatable content are part of the job.
BaristaLabs also makes independent software products. About explains the company model and gives the full biographies.
Each engagement stage must support a decision
Use only the engagement stage needed for the next decision.
20-minute assessment
Name the workflow, owner, systems, bottleneck or risk, and decision. The call identifies the next useful step. It is not a quote, technical design, or commitment to build.
Scoped discovery, when useful
When uncertainty prevents a useful scope, BaristaLabs reviews representative examples, data boundaries, risks, assumptions, and reviewers. The result is a bounded recommendation and rough implementation scope.
Scoped pilot or implementation sprint
After the parties agree on scope, access, test cases, reviewers, dependencies, exclusions, and acceptance evidence, BaristaLabs can estimate a pilot or sprint. The work leaves named deliverables, evaluation evidence, known limits, implementation notes, and handoff materials.
Choose the service by the decision you need
- Review Strategic AI Consulting to choose among candidate workflows.
- Review Process Automation & Integration for an established manual process.
Published evidence has clear limits
Each record supports a different claim. The records do not show that every project used the same method, and they do not predict a new client's outcome.
A repeatable video workflow
BaristaLabs built a generative-video workflow for recurring promotion of Stilson's Themed Music Hour, a weekly radio show.
Read the video workflow case
Client-facing delivery after stalled vendor attempts
After earlier vendor attempts stalled, BaristaLabs delivered a customer-facing website and app for CartWheels with an intuitive interface and customer communication channels.
Read the CartWheels case
An AKS upgrade with no application downtime
BaristaLabs resolved subnet and virtual-machine capacity constraints before it migrated node pools and upgraded Kubernetes. The published case reports zero application downtime.
Read the AKS upgrade caseAnother implementation path can be the better choice
BaristaLabs fits one focused workflow that needs senior builder access, custom engineering, clear boundaries, and a defined handoff. Choose another path when a tool works as-is or your contractor or internal team can own architecture, deployment, and support.
Choose a large consultancy for multi-department change and enterprise-scale integration. BaristaLabs is not a fit for a year-long transformation office, hundreds of consultants, or a generic product with no customization.
Review approval and data boundaries before implementation
If a workflow touches customers, sensitive data, regulated work, money, public content, or access, review the method before implementation. Responsible AI covers approval and rollback. Data Security covers access, vendor exposure, retention, and credentials. These pages describe methods, not client results.
Bring one workflow and one decision
Name the recurring workflow, people, systems, main risk, and decision. A 20-minute assessment can identify the next useful step.
Request a 20-minute workflow assessment