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Agentic Document Operations: Achieving 60X faster processing with 15X better quality in talent acquisition reporting

Hoffman Reed and Evolve AI Labs improve traditional executive hiring research processes by leveraging Large Language Models to automate process and technical documentation to improve customer experience using quicker, consistent and actionable insights

60x

Faster documentation

15x

Less review cycles

12 weeks

Time to market

Challenge

As a global executive search firm, for decades Hoffman Reed has been helping some of the world’s top healthcare and educational firms hire their future leaders. Executive hiring operates at a fundamentally different scale and complexity than standard recruitment, involving strategic C-suite and senior leadership positions that directly impact organizational vision, direction and performance. Unlike standard talent acquisition focused on filling operational roles, executive search demands multilevel stakeholder coordination, confidential market intelligence, and comprehensive cultural and leadership assessments that can span months of intensive research and evaluation.

These high-stakes placements require sophisticated documentation that are generated by distilling information from hierarchical stakeholder expectations, job specification literature, market analysis and unstructured data from talent sourcing platforms for organizational alignment. Naturally this leads to a variety of operational documents tailored for each step of this at least 3 month process from discovery to onboarding.

Hoffman Reed’s consultants regularly have to produce multiple documents after collating reams of unstructured data from different sources like interview calls, internet, job specifications, candidate profiles, to name a few, and then edit the data into structured reports aimed for an audience of executives. Teams at Hoffman Reed currently spend a lot of effort, time and money in research, analysis, editing, formatting, reviewing and publishing these reports to impart consistency, legibility and quality that they are known for. They needed a way to reduce the substantial operational overhead while maintaining the quality of the processes they are famous for.

“So as an owner of a search firm, and probably more so in past firms that I’ve owned because they’ve been much bigger than Hoffman Reed, the biggest problem that I had was ensuring that consultants of different capability level provided a consistent product to the client. Sometimes I’m doing a quality check from one candidate, look at it, and the executive overview and the formatting was beautiful document. And then I’d pick up another, and the executive overview was, like, three paragraphs” – Joe Screnci [Chairman, Hoffman Reed]

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Goals

  • Hoffman Reed achieves consistent quality of output across all their consultants by providing standardized tone, style and formatting which can be learnt from their best of all time documents.
  • Hoffman Reed reduces workload by 30% thereby improving report and document turnaround times by reducing the complex research and analysis time to hours instead of weeks.
  • Evolve AI Lab's agentic pipelines deliver superior analysis by churning large amounts of unstructured data from documents and interviews to provide insights that were impossible in the past.

Solution

Always the first to embrace technological advancements in the executive search industry, Hoffman Reed wanted to leverage large language models to optimize their executive recruitment processes and systems. By partnering with Evolve AI Labs, they aimed to transform their document operations from a labor-intensive manual process into an intelligent, low touch automated workflow that could handle the complexity and nuance of senior leadership assessment.

Evolve AI Labs rapidly developed a sophisticated multi-stage solution leveraging AI agents based on the latest reasoning-based language models for unstructured multi source data analysis, processing, editing, formatting and intelligent report generation. The architecture intelligently processes resumes, job specifications and interview transcripts through LLM-powered analysis to extract key leadership attributes, competencies, cultural alignment factors, strategic experience, job expectations and performance indicators regardless of format or structure.

These analyzed profiles are then synthesized into comprehensive stakeholder reports, job advertisements, interview scripts, hiring insights. These complex agentic workflows are abstracted from the user with a simple, easy to use UI that the organization’s employees are used to in their ATS systems.

While the solution is built on cloud infrastructure, the solution is designed for data security due to the involvement of PII and sensitive data like call transcripts. The solution’s modular design enables Hoffman Reed to scale assessment capacity on demand and replicate the solution across their offices around the globe which follow their own regional specific documentation processes, security guidelines and variety of reports.

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Impact

Leveraging generative AI automation has revolutionized Hoffman Reed’s executive recruitment capabilities, reducing documentation time from 4 hours to 4 minutes per report, a 60x improvement that fundamentally transformed how quickly they can identify and assess senior leadership talent for their customers while maintaining consistent tone, accuracy and increased insights than what was possible historically.

This dramatic acceleration in processing speed, combined with enhanced consistency in document tone, formatting and insights, has eliminated documentation bottlenecks and reduced the back and forth conversations that previously constrained executive placement lifecycle and stakeholder decision-making.

With the solution generating comprehensive candidate profiles, consistent job advertisements, future ready interview scripts and stakeholder reports automatically around the clock, Hoffman Reed has transformed a manual, relationship-dependent process into a competitive differentiator that directly impacts their corporate clients’ leadership acquisition speed and strategic hiring outcomes.

Beyond immediate operational gains, Hoffman Reed has established itself as a pioneer in applying generative AI to complex executive assessment workflows, setting new industry standards for intelligent talent acquisition methodology. Evolve AI Labs’ rapid deployment timeline demonstrates that transformative AI adoption doesn’t require compromising the nuanced evaluation critical for executive placements, while their modular architecture design ensures scalability as search volume and complexity grow without compromising data security.

This collaboration between Hoffman Reed and Evolve AI Labs proves that innovative recruitment organizations can leverage cutting-edge technology to deliver measurable value to their corporate clients while simultaneously improving document quality, reducing search timelines, and democratizing sophisticated executive assessment capabilities across their recruitment teams without impacting data security.

“I’m checking these reports against my notes and I picked out some words from my notes around – innovation, people-centredness, shared goals etc etc; that I thought could be added in but when I look at the reports those kinds of words or references are already there. I’m feeling a bit redundant!” – C Brown [Partner, Executive Search and Leadership Advisory]
“What we’ve done effectively gives me a consistent quality across the brand; AI assessing all the information in an assignment and cohesively and concisely putting that together. SearchX provides 30 percent workload reduction, consistent quality across all consultants, superior analytical capabilities and catches quality issues that human consultants can miss.” – Joe Screnci [Chairman, Hoffman Reed]


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