Help employees find benefits, onboarding, policy, and training answers while routing sensitive exceptions to HR owners.
We map each production workflow: where we connect the context systems, the custom workbench we build, how human operators review outputs, and the compliance metrics we deploy inside your cloud.
Custom workflow automation aggregates training guides, device policies, and team structures, drafting tailored onboarding checklists to speed up time-to-productivity for new hires.
Enterprise AI search indexes company handbooks, benefit guides, and health guidelines, answering complex employee benefits questions with precise page-number citations.
AI document processing reads incoming candidate resumes, extracts structured experience timelines, and prepares recruiter briefs without automating hiring decisions.
Custom workflow automation aggregates training guides, device policies, and team structures, drafting tailored onboarding checklists to speed up time-to-productivity for new hires.
Enterprise AI search indexes company handbooks, benefit guides, and health guidelines, answering complex employee benefits questions with precise page-number citations.
What is our corporate policy for parental leave extensions, and how do we apply?
Full-time employees receive up to 12 weeks of paid parental leave [Handbook Sec. 4.2]. Extension requests must submit via email 30 days prior [Benefits PDF p.7].
AI document processing reads incoming candidate resumes, extracts structured experience timelines, and prepares recruiter briefs without automating hiring decisions.
Each use case is linked to the services that would actually build it. Case studies appear only where the proof matches the workflow.
Guide new hires through tools, policies, team context, training steps, and common questions in their first weeks.
Answer routine HR policy questions with cited handbook sections and escalation paths for exceptions.
Extract candidate details, compare role requirements, and prepare recruiter review packets without automating hiring decisions.
The first build should have named source systems, a clear owner, realistic examples, and one measurable handoff point before expanding across the team.
AI can retrieve, draft, score, classify, and recommend. Material commitments, sensitive updates, and uncertain cases should pause for human approval.
If the process has no stable source of truth, no accountable reviewer, or no repeatable decision pattern, we recommend fixing the workflow before adding agents.
We identify the context sources, action boundaries, review gates, and launch path needed for a safe first release.
Talk to an AI Engineer