Three disconnected systems: one consultant could be recommended for four deals undetected. Now conflicts surface before deals close.
A 155-person AI consulting firm where people are the product, deploying consultants across client engagements that each require matching specific skills, seniority levels, and availability.
Staffing decisions required pulling from three siloed systems before anyone could propose a team, forcing a full prep meeting before every staffing...
“Those were three completely different systems that don't talk to each other, don't have any way of giving us visibility in real time.”
DevOps and AI consulting partner for enterprise software delivery.
HR, payroll, and IT management platform for global workforce operations.
Liatrio's Staffing recommendations is part of this use case:
Related implementations across industries and use cases
Comp data across five systems meant Taylor was a retrieval mechanism. One prompt built a live dashboard; four workflows run without her.
Every hiring target was a guess. A chain of AI prompts built the first real capacity model in an hour — surfacing a 63% offer-to-start rate.
Managers split between guiding 78-question calls and typing notes, losing context at handoff. AI transcribes calls; they focus on the match.
Managers split between guiding 78-question calls and typing notes, losing context at handoff. AI transcribes calls; they focus on the match.
Spreadsheets slowed staffing to eight weeks. AI agents now screen talent and automate contracts, cutting cycle times by 50%.
Manually updated profiles left skills stale. The first prototype took two hours per 1,000 consultants—now the agent covers 130K in minutes.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.
Three disconnected systems: one consultant could be recommended for four deals undetected. Now conflicts surface before deals close.
A 155-person AI consulting firm where people are the product, deploying consultants across client engagements that each require matching specific skills, seniority levels, and availability.
Staffing decisions required pulling from three siloed systems before anyone could propose a team, forcing a full prep meeting before every staffing...
“Those were three completely different systems that don't talk to each other, don't have any way of giving us visibility in real time.”
DevOps and AI consulting partner for enterprise software delivery.
HR, payroll, and IT management platform for global workforce operations.
Liatrio's Staffing recommendations is part of this use case:
Related implementations across industries and use cases
Comp data across five systems meant Taylor was a retrieval mechanism. One prompt built a live dashboard; four workflows run without her.
Every hiring target was a guess. A chain of AI prompts built the first real capacity model in an hour — surfacing a 63% offer-to-start rate.
Managers split between guiding 78-question calls and typing notes, losing context at handoff. AI transcribes calls; they focus on the match.
Managers split between guiding 78-question calls and typing notes, losing context at handoff. AI transcribes calls; they focus on the match.
Spreadsheets slowed staffing to eight weeks. AI agents now screen talent and automate contracts, cutting cycle times by 50%.
Manually updated profiles left skills stale. The first prototype took two hours per 1,000 consultants—now the agent covers 130K in minutes.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.