Establish the baseline.
We map the current workflow, owner, systems, decision points, exceptions and measurable baseline before changing anything.
We take a repetitive, high-friction business process from diagnosis to production — inside your existing stack, with human control, acceptance testing and a clean handover.
Every engagement starts with the current baseline: owner, workflow, systems, bottleneck, KPI and risk. We automate only after the operating logic is clear.
We map the current workflow, owner, systems, decision points, exceptions and measurable baseline before changing anything.
We define AI responsibilities, permissions, human checkpoints, guardrails, acceptance criteria and what should remain manual.
We connect the approved workflow to the systems you already use and implement up to two production automations within scope.
We test agreed scenarios, record exceptions and failure modes, train the team and hand over the operating logic — not a black box.
We target repeatable workflows with clear owners, measurable stakes and enough operational friction to justify redesign.
Qualification, research, proposal support, CRM updates and controlled follow-up workflows.
Classification, response drafting, knowledge retrieval, escalation and QA.
Candidate intake, summaries, structured fit support, recruiter review and communications.
Extraction, summaries, action routing, recurring reports and owner notifications.
Research, repurposing, approvals, QA and publishing handoff.
We start from operational reality rather than force-fitting a generic automation template.
We assess fit first. If accepted, the scope, acceptance criteria, dependencies and payment are confirmed before implementation starts. Best fit: a repetitive workflow with a clear owner, real operational friction and a measurable outcome.
We’ll assess whether AI should automate it, assist it — or stay out of it. If there is a real implementation fit, we define the operating outcome, controls and exact build before work begins.