UndoLabs designs AI-enabled workflows that help teams reduce repetitive work, coordinate information across systems, and handle routine decisions more consistently. We begin by mapping the process and its exceptions, then define where automation is useful, where a person should stay involved, and how the result will be measured. The goal is not "AI everywhere"—it is a reliable system your team can trust and maintain.
Automation pays off when it removes coordination cost—not when it adds another dashboard to check. These are the patterns we assess first.
Requests arrive by email, forms, or chat. A workflow can classify them, extract the relevant fields, and route each one to the right owner with the context attached.
Extract specific fields from invoices, applications, or attachments and register them in the destination system—with validation rules and a review path for exceptions.
Leads, approvals, and requests that stall get polite, rule-based follow-ups until a human makes a decision. Nothing silently disappears.
Pull together numbers from scattered sources on a schedule, flag anomalies, and deliver a readable summary instead of a pile of exports.
Answer common questions from approved knowledge, then escalate sensitive or ambiguous cases to a person with full conversation context.
Condense long threads, documents, or call notes into structured summaries so reviewers can decide faster—with links back to sources.
Not every process needs a language model. Some need deterministic rules; some need judgement on unstructured input; most real workflows need a practical mix.
| Dimension | Rule-based automation | AI-enabled automation |
|---|---|---|
| Best for | Structured data, fixed logic, exact repeats | Unstructured input: emails, documents, free-text requests |
| How it decides | If-then conditions you define | Context, classification, extraction, drafted responses |
| Predictability | Fully deterministic | Probabilistic—needs validation thresholds and review |
| Failure mode | Visible: the rule does not fire | Subtle: a wrong classification or extraction |
| Controls needed | Testing, logging, error handling | All of that, plus ground-truth checks, escalation rules, and periodic quality sampling |
A demo that works once is easy. A workflow your team depends on every week needs structure. This is the path we follow.
We watch the work as it really happens: inputs, tools, handoffs, edge cases, and the informal steps people never document.
Which steps can run unattended, which need a human checkpoint, and what the escalation rules are when confidence is low or data is missing.
One workflow, end to end, connected to your approved tools—not a platform migration. Small scope, real usage, fast feedback.
Execution logs, failure alerts, duplicate protection, and an owner for exceptions. See how we approach monitoring and observability.
Cycle time, manual effort, error rate, or response time—compared with the numbers we recorded before anything was automated.
If the first workflow holds up, we extend to adjacent steps. If it wobbles, we fix the weak link instead of adding more surface area.
Automated work needs the same discipline as hired work: right access, clear scope, and a supervisor for the risky parts.
We work with the platforms your team already runs on—including n8n, Make, and Zapier for orchestration, plus native APIs where connectors fall short. Every connection uses the minimum permissions it needs.
Sensitive actions (payments, external replies, deletions) run behind an approval step. Ambiguous cases escalate with full context. You decide the autonomy boundary—we make it visible and adjustable.
We document what data each step touches, where it flows, and what is retained. Where privacy matters—healthcare, legal, finance—we design for minimal data movement and clear retention rules.
Every workflow records what ran, what failed, and why. When an automated run cannot safely continue, an owner gets a specific alert—not a shrug from a dashboard three weeks later.
Services rarely live alone. These are the parts of the system this service most often plugs into.
Bring one repetitive process—intake, follow-up, reporting, or document handling. We will map it with you, mark what can run unattended, and propose a focused first release with a clear success measure.