Ema

The resume changed before the recruiting stack did. Candidates now have AI-polished resumes, keyword-perfect profiles, and tailored applications for every role. On paper, everyone looks like a match. That makes recruiting harder, not easier. The real challenge is no longer finding more candidates. It is finding the right signal across resumes, work history, external context, intent, and fit. That is the shift Ema Recruiter is built for: a recruiting AI Employee that helps teams cut through the noise, unify fragmented workflows, and move from scattered hiring tools to one intelligent system of action. Because the future of recruiting will not be won by teams with the biggest stack. It will be won by teams that can separate signal from polish, faster. Read the blog. Link in comments.

Yesterday, we introduced Ema Recruiter. Today, let’s look at what changes when recruiting moves from a fragmented stack to one AI Employee. Most hiring teams do not lose time in one obvious place. They lose it in the handoffs: search to shortlist, shortlist to outreach, outreach to screening, screening to interview, interview to ATS, ATS to onboarding. Ema Recruiter connects that journey. It starts with plain-language search across 1B+ profiles and 30+ premium talent sources, helping teams find candidates beyond the usual closed networks. It evaluates candidates on skills, experience, trajectory, and role fit, not just resume keywords. Each profile is matched, scored, and explained with 360° candidate intelligence beyond the resume. It helps teams move faster with: • Personalized outreach across LinkedIn and email • Automated follow-ups • AI voice screening with role-specific questions • Structured assessments for consistent evaluation • 50+ ATS integrations, including Workday, Greenhouse, Lever, iCIMS, and Ashby • Human-in-the-loop at every decision point The result is one connected system from first search to onboarding handoff, built to cut time-to-hire by up to 70%. The economics are just as important. Ema Recruiter is designed to deliver the lowest cost-per-hire on the market, with no seat fees, no per-contact costs, and no idle licenses when hiring slows down. Ema Recruiter is here. Outrecruit everyone. Check it out. Link in comments.

Introducing Ema Recruiter. Recruiting teams are being asked to do the impossible: hire faster, improve quality, lower cost-per-hire, and create a better candidate experience, all while operating across a fragmented stack. The old model is showing its limits. • Sourcing is locked inside expensive, closed networks • Screening is still too dependent on keywords • AI-generated resumes are making surface-level filters easier to game • Recruiters spend too much time moving data between tools • Hiring costs stay high even when hiring slows down Ema Recruiter changes the operating model. It is an AI Employee built to take recruiting from job brief to day one, bringing sourcing, screening, outreach, scheduling, ATS updates, and candidate intelligence into one flow. Built for modern recruiting: • 1B+ candidate profiles • 30+ premium talent sources • 50+ ATS integrations • 360° candidate intelligence beyond the resume • Skills-based screening • Structured AI voice screenings • Human-in-the-loop at every decision point And the economics are built around outcomes, not idle seats. No per-seat fees. No per-shortlist charges. No per-contact costs. One price that moves with your hiring plan. Early results: • Artico Search cut time-to-hire by 67% • Artico Search reduced cost-per-hire by 30% • Hitachi went live with Ema in 4 weeks across 20+ systems Ema Recruiter is here! Pay for hires, not idle seats. Outrecruit everyone. Visit our website to learn more, link in comments.

Hiring great talent should not require a recruiter to stitch together sourcing tools, outreach platforms, screening workflows, scheduling links, and ATS updates. That is the gap Ema Recruiter is built to close. Our tool brings the recruiting journey into one intelligent flow, from finding the right candidates to moving them through the hiring process with speed, context, and control. It helps teams reduce tool sprawl, improve candidate quality, and cut time-to-hire by up to 70%, while keeping humans in the loop at every decision point. Ema Recruiter is coming. Outrecruit everyone.

Top talent moves fast. Most recruiting stacks do not. Today, hiring teams are switching between sourcing platforms, outreach tools, screening workflows, scheduling links, ATS records, offer docs, and onboarding systems just to move one candidate forward. The ask keeps getting bigger: hire faster, improve quality, reduce cost-per-hire, and create a better candidate experience. But the stack keeps getting heavier. Ema Recruiter is built to change that. One AI Employee to bring the recruiting journey together, from job brief to day one. Cut time-to-hire by up to 70%. Deliver the lowest cost-per-hire on the market. Ema Recruiter is coming soon. Outrecruit everyone.

Enterprise AI has moved past the demo era. The real question now is: can your AI system hold up inside real enterprise operations? On May 27, Ema CEO & Co-founder Surojit Chatterjee joins Ran Wei Baker and Cheryl Cheng for a Microsoft for Startups LinkedIn Live on what it takes to build AI for real enterprise customers. The conversation will unpack what actually matters beyond the model: workflow depth, production trust, enterprise integration, measurable ROI, and scale. At Ema, this is the work we’ve been focused on from day one: building AI Employees that don’t just assist, but execute complex work across enterprise systems with reliability, security, and accountability. The next chapter of AI won’t be defined by better demos. It will be defined by systems enterprises can actually rely on. Join the conversation on May 27. Register for the LinkedIn Live. Link in comments.

Tokens are the new unit of enterprise work, but measuring them alone is the wrong scoreboard. At the HFS OneCouncil Summit, Ema CEO Surojit Chatterjee joined leaders to discuss the shift "From Rate Cards to Tokens: The new economics of agentic AI." The consensus was clear: AI economics shouldn't be defined by consumption, but by useful work completed at quality, speed, and cost. Key takeaways for the enterprise AI journey: Outcome over Consumption: Tokens are a proxy for cost, not value. Stop optimizing for usage; start optimizing for business outcomes. The Rise of Outcome-Based Pricing: The industry is moving toward paying for useful work. Activity without ROI is just noise. Automated Orchestration: Scaling AI shouldn't require every employee to be an AI ops expert. Systems like EmaFusion™ handle model selection and task decomposition automatically. The Human-AI Synergy: The goal isn't replacement; it’s evolution. Determine what humans own and what AI Employees execute to maximize combined output. Governance & Trust: Especially in regulated industries, AI must be measured against deterministic expectations and clear operational controls. The next phase of enterprise AI won’t be won by those who spend the most on tokens, but by those who turn intelligence into governed, measurable work. It will be won by the ones that can turn intelligence into governed, measurable, outcome-driven work. David Cushman (HFS Research), Bijit Ghosh (Board Advisor), Cliff Justice (KPMG), Umang N. (JPMorganChase), Ashok Panduranga (U.S. Bank)

Hiring one great candidate should not require 10+ tools to agree with each other. But that is what recruiting has become. Sourcing in one system. Outreach in another. Screening somewhere else. Candidate notes buried across tools. ATS updates lagging behind. Ema Recruiter is built to change that. Ema replaces your fragmented recruiting stack with an AI Employee that takes you from job brief to day one. 1B+ profiles. Automated outreach. AI-led pre-screening. One candidate pipeline. One scorecard. Built to help recruiting teams search deeper, move faster, and cut time-to-hire by up to 70%. 10+ tools. 10+ logins. 10+ invoices. Or just Ema. Ema Recruiter is built to help you outrecruit everyone. Launching soon!

AI agents are no longer sitting in innovation labs. They are entering the workforce as digital teammates, taking action, making decisions, and working alongside employees. In a new episode of KPMG’s You Can with AI podcast, our CEO and Co-founder Surojit Chatterjee joins host Nathaniel Whittemore and Edwige Sacco, Head of Workforce Innovation, KPMG to unpack what agentic business transformation looks like inside the enterprise. The conversation goes beyond the hype and gets into the real operating questions leaders are facing: → What does it mean to onboard an AI teammate, not just deploy another tool? → How should enterprises redesign work when AI can reason, act, and collaborate? → How do leaders help teams adapt without increasing cognitive load? → Why does AI transformation require executives to learn alongside their workforce? This is not a future-of-work prediction. It is a practical look at the shift already underway, where AI moves from assistance to execution and enterprises rethink how work gets done. For leaders building the next operating model for work, this is a conversation worth listening to. Full episode link in comments. KPMG US